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Entrepreneur Blackjack: 21 Startup Buzzwords Defined
Your guide to surviving startup cocktails while you dream up that billiondollar venture.
Acknowledgements to my parents,and the friends who pitched in a hand to help edit thisAmanda, Mehdi, Abhishek.
A code(love) publication
code(love): Entrepreneur Blackjack: 21 Startup Buzzwords Defined 1
Table of Contents Preface THE FUNDAMENTALS
MVP Pain Point Pivot Agile Lean LTV/CAC
THE TACTICS Growth hacking The datadriven mentality Technology Stack API Early Adopters Traction Venture Capital
THE OPPORTUNITIES Internet of Things Big data Open Source Cloud computing Crowdsourcing Sharing Economy Design Thinking Cryptocurrency
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Preface
It’s a beautiful thing being an entrepreneur.
Your path can be filled with pain, and failure, but in the end its your own path.
It’s something I never forgot when I was struggling through my first enterprise.
ThoughtBasin was about getting students to contribute solutions to corporate and
societal problems. We thought we had identified a large source of waste: students were
constantly given theoretical problems to test their abilities, but this sandbox model of
education never led to any tangible results.
So much brainpower was committed to coming up with new ideas, but the results
would often languish in some professor’s trashbin.
This led to a number of problems.
The first was that the value of the work students were producing was being
degradedand subsequently, so were the students. Students given nothing but
playsets to work with might perceive that their ideas were too dangerous or immature to
have any effect outside of the confines of the assigned problem set.
The second was that it gave students a false sense of what it meant to
problemsolve. When it wasn’t solutionseekers evaluating solutions but a professor with
strict guidelines, students learned quickly that it was conformity to strict norms (including
arcane formatting requirements) that ruled the day.
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They learned that it wasn’t the quality of ideas and the words they used that
mattered, but rather the quantity of them. To this day, I receive pagelong emails from
students that could be condensed to a beautiful few lines, but I always tell myself that
the senders were told that less than 1000 words meant your paper wasn’t going
anywhere.
Blaise Pascal put it best. 'I have only made this letter longer because I have not
had the time to make it shorter.’
'I have only made this letter longer because I have not had the time to make it
shorter.’ Blaise Pascal
In a comfortable environment where routine rules, those who would take risks,
and think outside of the box are discouraged from pursuing innovation. The essay
assignment becomes a canvas where ideas are encouraged to squish into a
comfortable box for the sake of convenience. The utility of the idea doesn’t matteronly
the fashion in which it is expressed does.
The third and final problem we thought we were solving was the thread left
hanging by the first two. Students were being trained in universities, but to what end?
The sandbox they lived in could tell them little about the challenges of implementing a
solution from starttofinish. They had little sense of the actual feedback on their
ideaswould customers have used it? Would organizations have adopted it?
Nobody would ever know. And therein lies the most troubling aspect of
ThoughtBasin’s problems: a huge amount of work was being done in a university
context, but there wasn’t much within that canvas that truly allowed a student to
differentiate themselves, and demonstrate to others that their solutions were
wellthought out, and able to make an impact.
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Even the professors who evaluated them might never know. Perhaps the piece
of paper they glossed over could have changed the world.
Weren’t Microsoft and Facebook born out of college dorms?
We saw this, and we, as students ourselves, set out to change the world by
building a platform that connected our fellow students with real companies and
organizations, and real problemssetting their creativity loose to answer questions that
were in dire need of solutions.
We wanted to give them a platform where they could differentiate themselves as
real problemsolvers, free from the requirements bestowed upon them by education en
masse. We wanted to let them know that their answers had value, and could make a
difference. We were incredibly idealistic about it alland though ultimately, we failedI
still believe it is an idea worth pursuing.
I failed this endeavor. But I learned a lot along the way, things I wish I had known
about from the beginning.
An idea never truly dies. When a startup dies it’s because the founders think
there are better uses of their time, or because they do not have the heart to continue.
As long as an idea has one practitioner, and there is one person driving that startup
forwardit can be said to be alive so long as that one person keeps on pushing it
forward. All it takes is one person with a belief.
Our team ended up seeing a competitor that did it better than us, and realized
that our experiment wasn’t getting the results we wanted. We figured out that if
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somebody was doing it better than we were, there wasn’t a point of continuing on this
idea. We no longer had that fire of belief within any of us.
Were we right or wrong? I suppose we’ll never know. But what I do now know is
that, had I known more about what I was doing, I would have had a higher rate of
success, or been more willing to move onto a different angle rather than giving up
altogether.
I entered the startup life with zero knowledge of what it would take to succeed. I
was seized with delusions that passed as strategies.
If I had known the terms I’m about to relate to you, and what they truly meant, I
would have been a stronger entrepreneur. I would have been a stronger builder. My
enterprise would have grown better. I would have known what heading a startup really
meant, rather than nodding off at the first mention of an oftrepeated buzzword.
Even if I didn’t want to build ventures, I would have been a stronger digital
citizen, able to relate better to how the world is evolving before me. I would have been
able to fully participate in the intersection between technology and society. I would have
known the truths of our new digital age.
Buzzwords hold a deceptive powerthey are there because they hide profound
truths in a way only the initiated can truly understand. They’re an annoyance because
they are the easy way out, a mindnumbing and exclusive set of words that mean so
much to so few, and so little to so many.
Inside them however, lie grains of truth I wish I had access to. They are the same
grains I want to illuminate for you so that you can build the ventures of the future, and
thrive in the new collaborative, digital economy.
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In other words, learn from my mistakes. Learn the buzzwords: they matter.
I’ve spent the last year or so writing about startups, and their truths, at my
personal publication code(love), on TechCrunch, The Next Web, and Techvibes, and
VentureBeat. I’ve been doing it because I truly believe the buzzwords I missed can
make a difference in the ventures of the future.
Here’s to hoping that you use them to build something beautiful that will last, and
create impact. Here’s to hoping you can be the change you want to see in this world.
I’ll be building with you.
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THE FUNDAMENTALS
Building startups is an art and a science. There are things you can do that help
you increase the odds, but the truth is that most startups die.
If you want to be one of the unlikely survivors, you have to know the
fundamentals behind startups. Hidden within these buzzwords are the difference
between life and death for many startups.
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MVP
The minimum viable product is an art, and not a science.
It’s when you finally decide your product is good enough to test out your original
experiment. It is the bare minimum needed to get data about the market you’re in, and
how customers will actually react to your idea.
A good MVP is a vehicle for your hopes and dreams.
As with any first car, there are a few rough patches to deal with.
When Twitter first started, they were not the Twitter you know and love. Twitter
revolved around users texting messages with their phones,posting those messages on
a publicly accessible web platform.
Netflix’s first rough version wasn’t even delivering movies online: it was about
delivering movies through mail.
It’s important to realize that way back when they were getting started, those
companies didn’t command the billions of dollars they do now. Their resources had to
be focused on one narrow test, and that test had to be delivered under the simplest
conditions possible.
Twitter was testing whether or not people wanted to be part of an organized
universal message board, somewhere where you could post your thoughts simply, and
see them displayed for all to see. The largest unorganized cocktail party on Earth
ensued. It was only afterwards that Twitter worked on refining the experience. The
Twitter you know now that allows people to post directly on the platform through mobile
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applications, and allows them to easily find out what is happening around them through
hashtags, and curated accountsthat was a Twitter that took years to evolve.
Netflix was trying to test a simple theory: would people be willing to pay for
convenient access to movies? Instead of going to Blockbuster or anywhere else, would
they prefer getting it shipped to their homes? If they did prefer that, it naturally followed
that they would like to have video streamed to them ondemand with the web. After all,
instead of dealing with the messiness of physical tapes, imagine instead a service that
could deliver to you the media you wanted whenever you wanted it.
Netflix certainly imagined it. They executed on it masterfully.
The test for instant ondemand online access to media was validated.
Consumers accepted it en masse. Along the way, Netflix learned a great deal about the
pain they were solving, and how they could go about delivering video to their consumers
in the best way.
Netflix decided to move to external servers after an internal data center failure
almost wiped out their ability to deliver videos on the webwhich at the time was an
experimental feature. By moving over to a more secure solution, Netflix ensured that the
experimental feature that would become the centerpiece of its business would always
be reliable.
The minimum viable product allowed for these large giants to test ideas cheaply,
and make sure that when the time was right to spread their product like wildfire,
everything was on a solid foundation.
It is through the minimum viable product that you first collect the data you need to
establish if you have an idea worth pursuing. It is here where you determine whether or
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not you might need to pivot. It is here that your idea becomes something tangible that
can be shared throughout the web, rather than a figment of your imagination. It is here
that you see whether or not you are solving a real problemand whether or not you
have real customers who need your idea to exist.
Pieter (aka Levels.io) is an entrepreneur who has committed to doing 12 startups
in 12 months. He’s constructed a series of minimum viable products that have been
featured on Wired, the Next Web, and a whole host of publications, and been used by
hundreds of thousands of people.
His latest venture, NomadList, focuses on sorting the cities of the world so that
you can distinguish how friendly they would be to remote workers, from climate
conditions all the way to how LGBTfriendly the cities were.
The idea has gone on the top of Product Hunt and Hacker News, two popular
directories for startup ideas that will drive incredible traffic to new ideas. NomadList has
received over 100,000 visits in less than a month.
Pieter is the perfect example of somebody who gets what a MVP should be
about. When he talks about his ideas, he talks about building them as simply as
possible, and just getting them done.
He started NomadList, a venture that was profitable from day 1, through creating
a shared Google Spreadsheet, nothing more. He didn’t need to create a website or
anything fancy to test the theory that people needed a guide to help them figure out
cities where they might want to work remotely.
It can take you or me, or anybody less than five minutes to set up a Google
Spreadsheet.
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Soon after Pieter shared it, the list was getting populated with new information
and new categories. Somebody filled in how LGBTfriendly each city was, rounding out
the NomadList to its’ final form.
Demand for Pieter’s idea was established in the simplest fashion possible.
Perfect is the enemy of done. Done is when you can begin testing your theory
that your idea is something people will use.
It is here where an idea becomes a startup.
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Pain Point
Startup entrepreneurs have a funny affliction. They are good at solving problems:
they just don’t often happen to be problems that most people would have.
The problems entrepreneurs solve often happen to be the problem that the
entrepreneur happens to have at the momentand given how most digital
entrepreneurs are currently drawn from certain gender, demographic, and cultural
threads, the new digital economy is filled with solutions for the problems of a very select
few.
There is an apocryphal tale of the programmers who set out to solve
homelessness. They were going to program an application that was so clever that it
could figure everything out for the homeless. They could find the nearest shelter, or the
nearest food source. They could start budgeting for themselves, and start acquiring
knowledge so as to better themselves, with only a few button clicks.
When it came time to actually see how this application could be delivered to the
homeless, the app makers came to the realization that the homeless don’t readily
possess smartphones, or tablets.
Their daytoday wasn’t spent looking for more efficient information on their
cellphones, it was spent surviving as best as they could. This simple fact confounded
the good Samaritan app builders.
I don’t know if this story is true.
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Yet, I wish it were. It symbolizes everything wrong with looking for solutions
before looking for problems. You have to consider what people go through in their daily
lives in order to effectively create solutions that will improve people’s lives.
An entrepreneur must create solutions that solve the pain others are going
through to succeed. The more pain solved, the better. You’ll be doing more good, and
helping more peoplewhich means you’ll deserve more profit.
A framework many entrepreneurs use to evaluate this is the “vitamin or aspirin”
questionis your solution something nice to have like a vitamin, or is it something that
will cure a glaring pain straightaway like an aspirin?
A solution that does credit card processing for a software company is an aspirin:
it’s businesscritical, and if that solution stops working, then the company as a whole is
threatened as there is no way for the company to collect payments.
Something that helps employees of a startup manage their time productively: it’s
something nice to have. If the solution failed, performance would suffer, but the
company would not die.
Your startup should be focused on finding actual problems, pressing pains being
suffered by actual people who need help.
If you can create a solution that makes sense for those people, your business will
grow.
When those people in pain find your solution, they will use it, and they will use it
consistentlyand bring others to come on board. You won’t need to spend much on
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marketing: the Internet and your set of new evangelists will do a lot of heavy lifting for
you.
Much of the first phase of your startup will be finding exactly what pain the
customer is suffering, and how you can best solve that pain. That will become the basis
of your value proposition, the reason why your company exists.
Your minimum viable products will quickly determine exactly who is suffering
from pain you can solveand how you can go about fixing that pain.
Think of all of the largest organizations in the world.
Coca Cola wants to sate your thirst wherever you are in the world: they have
oriented themselves to be a mere arm’s length away for almost everybody on the planet
by investing heavily in a cuttingedge logistics system. Your pain point of thirst?
CocaCola has it handled.
Stock exchanges exist to pair people who want to buy shares in companies with
those who want to sell them: the exchange is optimized for the speed and security of
transactions. The process helps eliminate all of the pain that would be a part of the
process: finding somebody who was willing to trade shares with you, ensuring that they
were trustworthy, and doing it all in a matter of instants.
Because these organizations make it easy to solve real problems for people,
they’ve grown monstrously large. It’s something to keep in mind as you look for the pain
you’ll solve.
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As a startup with few resources, you will have to focus on a narrow pain point,
something simple you can solve well with a combination of new technologies, and
innovative thinking.
Don’t let that think that you will accomplish less if you keep it simple.
Netflix had one simple reason for existing, one simple test: they wanted to
displace video rental stores. They thought that movies were something people wanted
instantaneously, and that there had to be a better model than Blockbuster. Mailing
movies workedthen, as we saw, they soon migrated to providing movies online,
available at a click of a button.
By focusing on one narrow pain point, Netflix has become a company worth
$28.50 billion.
To find the pain point you are solving, you will have to struggle through change
after change, and embrace the agile and lean philosophies that have underpinned
startup success. You may have to pivot along the way.
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Pivot
The strongest entrepreneurs are often those that can change their convictions
rapidly.
Every startup idea is a hypothesis, a test. Nobody really knows what will work or
not. To say that your idea is a good idea is to believe in a sense of destiny that requires
personal conviction, but flies in the face of reality.
The ones that have been through it all know that there is a balance between
seeing an idea through to its proper end, and flogging a dead horse.
AirBnB is a lynchpin of the new collaborative economy. Instead of renting out a
hotel for your next vacation, you can rent out a resident’s spare flat, and get hosted by
them. This collaborative view of the hospitality industry helps hosts make some extra
money off of what had previously been illiquid assetsand allows renters to save a bit
of a money, while getting a more personal view of the city. Once described as a quaint
and quirky ideait is now a $10 billion business.
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Picture source: Rachel Botsman, Author & Founder, Collaborative Lab.
When AirBnB first started, they were going to focus on offering extra rooms for
conference attendees. They ended up being a service that connected people who
wanted to rent out extra rooms from citytocity with those who needed a space to sleep,
and live. AirBnB changed focusfrom a narrow one tailored to conferences, to a broad
idea that could change the hospitality industry.
It has paid off with a handsome ten billion dollar valuation.
Charles Darwin is often misquoted as saying that “It is not the strongest of the
species that survives, nor the most intelligent that survives. It is the one that is most
adaptable to change.” It was a professor of management studies, Leon C. Megginso
who penned this quote, but that doesn’t make this insight less truthful.
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“It is not the strongest of the species that survives, nor the most intelligent
that survives. It is the one that is most adaptable to change.”
Entrepreneurship is about adaption. One of the only advantages you have when
you’re faced with corporate giants, and you’re two people in a garage, is the fact that
you’re just so much more nimble than a corporate behemoth.
You can test out different variations of things, test out different facets of your idea
without going through the PR department, or levels of bureaucracy. You can find out
what your consumers want, since you can go through crazy ideas without batting an
eyelash.
Any hunch you have can be quickly converted into an actionable experiment,
sometimes in instants. You can go from garage to experiment in a manner of seconds,
constantly refining your approach until you get it just right.
While the Fortune 500 are thinking quartertoquarter, you’re thinking daytoday,
and sometimes hourbyhour. And when conditions change, you can change quickly as
well.
The pivot is just an extension of this experimentation. It can happen naturally:
you may find out that as you’re moving through your space, you adapt your strategy to
what works well, and without even knowing it, you have a whole different business in
your hands.
The pivot is a drastic change in strategy that uproots a very large part of the
original idea.
It can mean switching your venture to a feature that works particularly well, and
focusing on just that, known as zoomin.
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Instagram started as a locationbased service where you could check in to
different spots, similar to Foursquare. When the founders of Instagram realized that it
was the photos people took at the locations, and the modifications they were pulling on
them that was keeping their business going, they tailored their focus to that: allowing
their users to filter their photos ondemand instead of forcing them to register into
different locations.
It was a classic zoomin pivot, and soon after,they were bought out by Facebook
for a cool billion dollars.
A pivot could also mean changing your narrow focus on a feature to a broader
product with the notion that more features will add more value, and get you a broader
set of usersthis is known as zoomout. Maybe you were building a platform that
helped automate recruiting processesbut then you realized all of your clients needed
a fullservice HR platform that also allowed them to automate their internal employee
needs such as benefits processing, and tracking vacation days.
When you go from creating systems to track applicants for jobs, to a fullservice
platform that handles both applicants and current employees, you are zooming out.
A pivot could also mean a change of business modelinstead of making money
putting advertising on the side of your service, you might charge users for using that
service.
You could change the technology that you’re using: let’s say you were building a
web platform to crowdsource toxic waste sources. Maybe what you’ll realize is that a
streamlined application on your users’ mobile phone makes it much easier for people to
do that then requiring them to bring their laptop to every dump site.
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A pivot can also happen deliberately. When ThoughtBasin started, we tried to get
money to students for their solutions. Unfortunately, we understood very quickly that we
could only be a social enterprise: nobody was willing to pay enough for the solutions of
students to sustain a business venture.
I had a team of engineers onboard who thought it was forprofit. I worked with
them for days to see how we could change the idea to fit something that could sustain
the teamperhaps a recruitmentbased model. We were thinking of changing our
business strategy to fully test the original idea that there was value in what students
created.
We were thinking of pivoting.
A pivot is nothing more than questioning the original test your startup was
created to try out. If you founded a network to connect dog walkers with dog owners,
you’d have a theory that people would be willing to pay dog walkers to take care of their
dogs for them online, at a high enough pace to sustain a business.
If it turned out to be the case that this wasn’t true, then any rational entrepreneur
would move on to change ideas. You shouldn’t fight the market.
You should embrace it to improve your business. You may find out that people
aren’t willing to pay for dog walkersbut they’re willing to pay for dog food delivered to
their place! Once you fit the business to this demand, you will have pivoted. You will
have more sales, and a stronger startup.
It can also mean moving onto a new experiment, a new test.
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I’ll always remember when I let my first startup go. It hurt, but the reality is that it
was what made sense at the time. It still stings to this dayI think the loss of what you
might have had pains more than most other painsbut it’s manageable.
One fact I always remind myself of is that nobody knows with 100% certainty
what will succeed or fail. Even top investors often get it wrong: about threequarters of
venturebacked startups never offer any return on investment.
It was hard ending something I devoted my life to, but in the end it was
necessary. Our experiment showed that companies were not willing to pay enough for
the thoughts of students for it to be worth our while. We didn’t have enough time to test
further.
So we moved on.
Startups are experiments. They’re trials. And when the data tells you to change
your assumptions
You adapt. You change.
You pivot.
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Agile
The agile philosophy is one where software development focuses on iteration,
rather than building a set of software features outright.
Rather than focusing on creating documentation, and aligning everybody to
building some huge software project somewhere far off in the future, the agile
philosophy focuses on getting working code and a workable product in the customer’s
hands so that their feedback will dictate where the software will evolve.
Its ethos is centered with the agile software manifesto.
Rather than depending on your own theories about what people need from your
software, the agile approach fixates on how your customer uses your software to
determine where to go next. It breaks software development into rapid cycles of
development where a functional product that continually improves to suit your users’
needs is the key to success.
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Picture Source:
http://upload.wikimedia.org/wikipedia/commons/1/1c/Agilevsiterativeflow.jpg
It is a methodology behind software development, one of several that can be
used by teams of programmers to ship great products.
The old methodology of the waterfall methodology is often the approach used to
contrast with the agile philosophy. Observe the graph above.
Instead of focusing on flexible iteration, waterfall proponents will argue for larger
releases that go through the entire product lifecycle in order to evaluate and learn more
fully. What this looks like in practice is a longer cycle where software is shipped at
longer intervals, allowing for fewer experiments, and more risk per experiment.
In waterfall, you’ll spend a lot of time gathering documentation at the beginning,
coding and designing in the middle, and performing testing and fixing later.
This means that there is higher risk that the end consumer is unhappy with the
nearfinished product. Instead of constant iteration, waterfall focuses on delivering an
end product and then testing itleaving a lot of room for error if initial requirements for
the software were illdefined, or in hindsight, not exactly what the user wanted. You’d
have to start all over again if that were the case: a huge amount of waste.
The waterfall method does it make it easier to plan and ship software without a
high amount of involvement from the end consumer, if that is impossible to obtain. It can
be a much smoother process to go from the beginning of documentation to the ending
of delivery.
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Yet Agile is built for constant communication between the user and designer of
products, which certainly helps craft products that are built for how the user will actually
use the product versus how they think they will.
The debate between these two methodologies rages on. While agile has seen its
fortunes rise, and “traditional waterfall” approaches seem to lose their dominant toehold
over software development, the choice between the two is still one that is actively being
made by many.
A friend working at a startup told me of their startup’s “extreme” implementation
of agile. Every day, every programmer and engineer would literally stand up and report
on what they were doing, where they were stuck, and what they needed to advance.
These daily standup meetings were meant to reinforce the iterative and rapid nature of
agile, to the point where daytoday progress mattered.
Agile philosophy is an overarching philosophy. There are different ways of
implementation. One way is the scrum method of implementation, where small
crossfunctional teams get together and daybyday, go over what they’re working on,
and what they need to get their part done.
The team works towards getting a working demo up by the end of the day, then
reflects on what happened between that initial meeting, and the product they crafted.
This is known as a sprint, and it’s a fixed time block where a team will go through
all of the phases of software development, from inception to final documentation, to
deliver a workable product by the end of that sprint.
It fits in well with the startup mentality where resources are very scarce, and
teams cannot often afford to create anything too large. Just as we saw with the
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concepts of a MVP, and pivoting, the advantage of being a startup lies in how rapidly it
can build.
The agile philosophy embeds flexibility and adaption to every level of how an
organization builds itself. It perfectly executes on what it means to build first, and get
data later. It is a finely fashioned way to build where it isn’t documentation that matters,
but results.
Agile focuses on continual improvement, and customer validation of real
products. Instead of focusing efforts on predicting what will be a massive wave of
chaotic changes, the agile philosophy is one of adapting to change. You focus
resources on being as flexible as possible, rather than trying to anticipate every change
possible. Instead of building a massive dam to keep all water out, you build a boat so
that you can navigate through it.
With the agile philosophy, startups can actually leverage the large amount of
resources corporations have against them.
By utterly rejecting the dangerous thought that everything can be controlled for,
startups can use their rapid ability to change to find insights, and create meaningful
solutions, instead of spending time encumbered in bureaucracy.
By conceding the strategic planning to the giants, and focusing on learning by
doing, you can beat large corporations by changing the rules of the game to suit your
strengths.
You can turn the strengths corporations pride themselves on into leaden
anchors holding them back. Instead of burdening yourself with strategic planning, you
can focus on building quickly.
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It is with nimble quickness that startups will build themselves rapidly into the
future, while corporations remain entrenched in the past.
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Lean
What does the lean philosophy mean?
It was Eric Ries who first wrote the Lean Startup, summarizing his findings after
the Great Internet Bubble of the early 2000s burst.
It was a time of great chaos where the worth of technology companies
evaporated overnight. Whenever the value of technology companies seems too highly
priced on the stock market, people reference that longago chaos.
Back then, building a website seemed to take an inordinate amount of money.
The infamous Pets.com lost $147 million in the first nine months of 2000. In contrast,
Facebook’s first seed investment by Eduardo Saverin was $15,000, and its first round of
financing from angel investors was $600,000. The startups of today have been built
much cheaper than the startups of yesterday. What has changed?
The environment has changed. The Internet itself has matured, with enough
users onboard to support largescale advertising models. The infrastructure and critical
mass is there: before, the Internet may have been home of a few forwardlooking early
adopters. Now, it is very much a part of the mainstream, comfortable to millions if not
billions of human beings.
Naval Ravikant, the cofounder of AngelList, an interactive directory of startups
where entrepreneurs can connect with investorsnotes that in 1999, it would often cost
millions of dollars to launch a software product for an audience of about 30 million
serious Internet users.
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Nowadays, it costs a fraction of that, maybe a couple thousand dollars to reach
three billion people. The ratio of how much cost it takes you versus how much people
you can reach has grown at an almost unbelievable rate of 100,000x+.
The way startups are built has changed because entrepreneurs and investors
have learned from the past, and embraced it. Any high in valuations now sparks
discussions about whether or not there is another bubble.
Investors are a lot more concerned about actual sustainable businesses, and
there are a lot more case studies of those. Youtube used to be very unprofitablenow it
is a major part of Google’s growth engine, able to sustain itself on an advertising
business model that makes sense now.
External conditions have changed for the better, but it is internal philosophy that
is making a key difference.
The Lean Startup mentality is based on the lean manufacturing approach
espoused by Japanese carmakers in the 1980s, which argued that any expenditure that
didn’t lead to direct value for the end consumer was wasteful, and needed to be
eliminated in order to maintain an efficient organization.
For a company with such limited resources as a startup, finding the value that
you provide to consumers, and focusing on that one aspect is the difference between
survival, and failure.
You could argue that the entire process described above is all about what lean
espouses: finding exactly what adds the most value to the consumer, and then reducing
or stopping actions which don’t.
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As an example of this philosophy: consider the creation of a business plan.
What are you really trying to do when you create one?
If your answer was to put as many words on a paper as you can, until it can
serve as a suitable paperweight, then by all meansgo ahead.
If your answer was that you wanted to flesh out your business vision, and see
where it could take you, then in order to think lean, you’d eliminate all of the fluff around
that.
Instead of creating massive 20page business plans that go nowhere, the lean
philosophy focuses on important value differentiators in the form of a lean canvas, an
alternative to the business plan that takes a fraction of the time to do.
The lean canvas is filled with simple points. It takes 20 minutes to complete.
Importantly, it delves to the heart of what a business is all about: what problem are you
solving? Who are you solving it for? How are you solving it, and why is that different
from anything that’s been done before?
In being flexible, and creating small iterations that test the consumers’ pain
points, you will eventually have the information you need to find exactly how to help
your consumers resolve their problems in the most efficient way possible. If all of your
resources are directed in that focus in a lean fashion, you will find that it will take a
minimal amount of resources to reach important insights.
If you know who and what you’re building a product for, you will succeed.
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Instead of learning that through putting as many words as you can on a paper,
you should learn it by executing in the real world.
Instead of building out a huge platform filled with features, occupying a huge
office with a massive team of engineers, you should choose instead to test small
experiments with a tiny team of cofounders. When you find something that works, you
can go allin and build on top of that insight, building along the way a sustainable
business that relies upon insights gleaned throughout the lean experimental period.
Eric Ries calls this validated learning in his seminal work on startups, the Lean
Startup. It’s learning by doing, and figuring out exactly what your marketplace needs so
you can build a sustainable venture that solves the pain of others.
It’s important here to establish what success means.
You should establish a baseline of metrics and then create a growth engine
based on growing the metrics that are important to you as a business. Choose the
numbers that matter to you, then find the system that works to increase those numbers.
Lean Analytics is a book that will help you get there.
If you’re a social network, maybe your focus will be on the number of daily active
users, a sign of how engaged your network truly is. If you’re an ecommerce site, maybe
your focus will be on sales, and profitability.
By defining the right accounting for your key performance indicatorsthe right
metricsto determine the current health of your startup, you can quickly determine if
what you’re doing will get you the results you need.
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If it isn’t, you can quickly change to tactics that will grow your numbers. You can
use your speed to your advantage, minimizing waste along the way.
Through the creation of minimum viable products, rapid pivoting, and learning by
doing, a startup aims to learn as much as it can about the market and the users that will
propel it forward. Once that learning helps build a solution that efficiently solves a pain
point many people have, a startup will grow beyond reckoning.
In other words: build quickly to learn. Learn quickly to improve. Build on that
improvement until you are ready to expand tenfold.
This is what the Lean Startup is all about. This is the superpower that has
elevated twoman garage outfits into the forces that will shape our collective future.
Does that mean that there are no unsustainable startups these days? No. Far
from it. Even if lean enterprises are stronger than their predecessors, they still have to
create business models that make sense.
This is where the numbers come in. How they balance will determine the fate of
your startup.
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LTV/CAC
This is the section where you get two buzzwords in one. The reason why is that
because their relationship may be the most essential element for a startupyet also,
curiously, one of the most neglected.
LTV stands for lifetime value of your user. Imagine that you are selling ebooks
on your website on a subscription basis: a monthly price of $10 gives them access to all
of the ebooks you have.
User A comes to your site once every month, and buys an ebook subscription
worth $10. They do this for a year, meaning that you get 12 months of $10 sales, or
$120. After that year, they decide to leave forevera process known as churn. If you
calculate it out, their lifetime value is that $120 in sales they gave you while they stuck
around.
You want to calculate churn, the number of users who are leaving your service
after using it, and make sure you find ways to keep it low. A simple measure of churn
would be the number of people who abandon you in a month versus the total amount of
users you have. Imagine that you have a recurring base of 100 people who are buying
your ebook subscriptions, and only User A leaves that monthyou have a 1% churn
rate for that month.
Most subscription software models, otherwise known as SaaS businesses, have
an annual churn rate under 10%about 70% of them in fact.
Your yearly churn rate in this case would be 12% (1% times 12 months), so you’d
actually be doing quite badly.
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You’d want to focus on making sure that people like User A don’t leave
youperhaps you could create an automated email every time somebody cancelled to
try to get them to give you feedback on why they’re leaving, and make one last pitch as
to why they should stay.
Perhaps you should focus on better customer service, and making sure your
product is doing the best it can for your usersa high churn rate would indicate
something is wrong with what you are offering, and that you should reevaluate your
product, or how you are treating your users.
You want to make sure churn is as low as possible, because it’s always better to
keep your existing customers, rather than spending tons of money acquiring new ones.
Instead of having a treadmill business where one new customer replaces others that are
rapidly departing, you want to have something stable that consistently grows with
satisfied users.
The cost of acquiring that new customer is abbreviated CAC. In this case, let’s
imagine that you had to spend some money on Facebook advertising to lure your
ebook customer in. Let’s say that on average, it costs you $120 per ad, and that you
drive twenty clicks for each ad. Of those twenty clicks, let’s say about five people make
it past the registration processand out of those five people, two people actually start
buying ebooks (among the two is good old User A).
Your cost of acquiring that customer would boil down to $120 divided by twoin
this case $60.
Then you do the ratio. Take the lifetime value you derive from the customer, and
divide it by how much it cost them to get there. With our example, that comes out to a
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ratio of 2xthe lifetime value of our customer is $120. The cost of acquiring that
customer was $60.
In other words, for every consumer you get spending money on your site, they’ll
give you 2x the return.
What does that mean for a startup idea as a business? Many people forget the
notion that they’re running businesses when it comes to startups. A valuation boom has
certainly not helped matters, but it almost appears as if the fundamentals of business
have been lost in the fray. Startups have lost the plot. The race has been on to acquire
user after user without too much thought as to the sustainability of the startup.
Whether or not your startup idea is a viable business rests within that ratio
number. Many investors have been on record as saying that they prefer a 3x LTV/CAC
ratio because that gives the business enough room with which to power explosive
growth. Left unsaid is the notion that there are a whole bunch of ideas that do not obtain
this benchmark, and some that are actually losing money for each user they pull in.
It’s important to consider a startup’s burn rate, or how much money you’re
spending each month on building out your dream. If you spend too much, you will
quickly find out that your business model is unsustainable.
That’s when noted investors will tell you to worry.
There’s always time to test your idea, and refine it, and those numbers can
always improve, but you have to ask yourself in the long run if you will ever hit those
metrics.
You also have to ask yourself if you’re running a business or a fantasy.
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It’s an issue of having a viable business model. Reid Hoffman, founder of
LinkedIn, has said that it is generally only one business model that drives the business.
A lot of entrepreneurs have this “and” tendency. Their idea has to have layers upon
layers of features and ways they can make money because they want to maximize their
opportunities, and make it sound to everybody that they have everything figured out.
In reality, even a behemoth like Google relies heavily on one business model:
display advertising. Advertising was responsible for $42.5 billion in revenue in 2012, the
main source of Google’s $50.2 billion in 2012 revenuea whooping 85% of all the
money Google made.
What business model will you choose?
Will you become a social network that depends on advertising to its users? A
mobile application that helps people order tshirts ondemand? A marketplace of ideas?
In the long run, any forprofit idea has to get more money from its users than it
spends on them. That should be common sense, but people don’t often account for the
time and money they spend driving people to their idea when they are busy thinking
about the hypothetical billions they will earn.
They often think of themselves as investing in this great, billiondollar opportunity,
and will stop at nothing to get there. Time and money are forgotten. I know when I was
running ThoughtBasin, I was dreamchasing: to be an entrepreneur, you have to be
doing so.
Within this dreamchasing, you do have to choose exactly how your venture will
grow.
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Using advertising is often a crutch, but many of the Internet’s giants rely upon it.
The Internet’s currency is now time, rather than money because of it. Consumer
applications often bank on the ability to convert engagement into money. Certainly, that
approach worked with Youtube and Google.
What these metrics do is ground you to your approach, and whether or not you
and others can scale this idea of yours. Remember that you are the probably the person
who is most passionate about your idea. Your belief in yourself is a superpower, and not
one that will transfer itself 100% to the people you bring onto your dream.
You will need those other people eventually to grow your idea. You cannot count
on them to work for free, or to deliver amazing results consistently without some form of
material reward.
If your numbers don’t work, and if you are losing a lot of money getting users to
believe in your idea, while envisaging little potential in getting any of that money back, it
may be time to pivot.
Remember, anybody can chase their dreams. The real challenge is in making
sure that dream makes a sustainable impact, and can carry other people along for the
ride. The LTV/CAC ratio will go a long way towards framing that thinking.
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THE TACTICS
The fundamentals are important, but in a world where an idea is not worth nearly
as much as its’ execution, how you go about pursuing your dream idea matters much
more than the idea itself.
These are the tactics that will help propel your startup to success.
Growth hacking
Growth hacking is a buzzword. As soon as somebody says it, the fury of meaning
nothing, but signifying everything envelopes any situation you place it in. It’s mysterious
and ambiguous, but it doesn’t have to be.
It’s always been hard for me to figure out this term, and yet it’s been a necessity
because I’ve always wanted to work in the field. I think part of what compelled me to get
into building and scaling web platforms was the mystery of understanding what growth
hacking was about: even the mysterious bits I could get out of it sounded cool. Some
sort of marketing meets technology was something I thought would be ideal for me.
So, what I did was take a target list of everywhere I thought growth hackers might
be, from mentoring sites, to tech entrepreneur networking sites—most notably
FounderDating—to good old LinkedIn.
I got familiar with the big names in the field. I reached out to many of them
systematically, seeking the same insights: what exactly is growth hacking, how do you
go about growth hacking, and how can I go about growth hacking? I then recorded the
answers, and compared them, looking for some sort of pattern that defined the concept.
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In doing so, I realized that what I was doing embodied what growth hacking was
all about. Trying out new approaches, and then measuring whether or not it was more
efficient than what I had been doing before is the core of growth hacking. Every one of
the answers pointed me to a direction, a direction that I can sum up in one line.
Growth hacking is being creative and trying new tactics to acquire new website
users, measuring the effects of each individual outreach, then determining whether it’s
more efficient than what you were doing before on a monetary and time basis, and if so,
piling as many of your resources as you can into those new channels.
To summarize even further: To growth hack, try new tactics, and measure
whether or not you’re being more efficient driving users to your webpage. If you are,
keep piling resources forward.
There are hives of resources for the kind of experiments you can conduct and the
tools you can conduct them with. You’ll find a lot of good material on what exactly to
write on Copyblogger. You’ll find a lot of information on how to spread your content with
Buffer and their blog. You’ll find good growth tactics on the various blogs associated
with Neil Patel from his KISSmetrics blog to his QuickSprout blog.
Josh Elman, Twitter’s head of product, and the designer of Facebook Connect,
has an interesting overview of both the mentality and tactics in play when it comes to
growth hacking. He’s approached it from an engineering point of view that reflects the
growth hacking mentality, where tactics evolve during time depending on what you want
to achieve, what’s working, and what users you want to attract.
He’s got some good insights on the process, including reallife examples of how
changing Twitter’s product turned temporary users into steadfast users.
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Twitter inserted instructions into a tutorial for every new user to follow a certain
number of people, and get enough content fed to them. By doing this, Twitter ensured
that everybody that went through their mandatory introduction was set up, and fed
enough content so that they would understand what Twitter was aboutsomething
would click and get them to use the product.
Josh and the Twitter team had found out that once Twitter users followed a
certain number of users, they were more likely to become active users themselves. So
they focused on making sure that you started off your Twitter experience
This process did have some minuses: it was longer, and some people would
inevitably leave before it was done. Those that would stay, however, would have a
much higher chance of using the service for a long timeand that’s what really
mattered to Twitter.
People who just registered would have a reason to stay.
It was the difference between having somebody visit the platform, and somebody
becoming a Twitter user. To this day, Twitter still makes you follow a whole bunch of
suggested accounts before you get started, a perfect example of a tactic that was found
with a growth hacking mentality, and carried out well.
Sean Ellis (the originator of the term “growth hacker”), and Morgan Brown have
compiled an excellent series of case studies that tap into how the most successful
startups in the world have experimented their way to greatness.
Growth hacking is all about that: being creative and coming up with out of the box
solutions, and having the analytical capability to see what is working or not. Seeing who
your best users are, and how to replicate the process to get more of them.
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This is an important distinction to make. Brian Balfour, the VP Growth of
marketing analytics company HubSpot, one of the premier software products for
technologyminded marketers, has got a set of great slides about the whole process of
growth.
Good growth hacking isn’t one or two marketing tactics tried in isolation, even if
those tactics end up creating incredible amounts of growth. Good growth hacking is
installing a solid growth engine: a process of choosing, implementing, and evaluating
different marketing techniques in order to be able to drive data about users. Use that
data to acquire, retain, engage, and ultimately, monetize people using your service.
Dave McClure, the founder of 500 Startups, an incubator for startups, and the
former Director of Marketing for PayPal has come up with a system to describe how this
process works. Termed the pirate metrics, the system is abbreviated as AARRR.
First, you acquire visitors to your sitethis might have happened because you
were really sharp on optimizing your site for search engines so that you’d pop up first.
Or maybe your visitor saw your link on their friend’s Facebook. Then you activate them:
through a welldesigned website, the visitor starts clicking around. Maybe you have an
email registration form that then allows them to sign up with your service.
Now you’ve effectively converted somebody who was looking at your website into
a user. Now you focus on seeing if you can retain them by sending off an email to see if
they come back to the site. Then you focus on referral: getting all of the users on your
site to bring their friends onto your site, whether that’s through social sharing buttons or
word of mouth.
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Finally, you’ll seek to make revenue off of your visitorsturnedusers. Maybe your
solution is an ecommerce platform: once a user has visited your site long enough, and
if all works well, they may just take the leap and buy something from you.
It’s your job to ensure that you maximize the number of people who go through
this process, focusing not only on quantity but quality. The process to turn a visitor into
a paying user takes a long time: any flaw in the product can turn somebody off. Your job
is to make sure the highest percentage of people go through each step successfully,
thinking along each step of the process to ensure it is the best way forward.
Using this kind of thinking will mean the difference between a product with a
shallow user base that never comes back, and one that has a thriving community of
millions that will pay for your platform, and help spread it.
It’ll mean the difference between having an interesting feature, and being able to
build out the next great enterprise of the future.
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The datadriven mentality
How do you build that thriving community?
Be datadriven.
The datadriven mentality is embodied by the infamous A/B Split
Testsomething everybody says they’re doing, but few actually are.
The A/B Split Test merits inclusion in this book because the term is everywhere,
and because it’s a popular tactic that can be at the tip of good decisionmakingwhen
done right.
The theory behind A/B split testing is very simple.
Show two separate audiences two different versions of your website. Website
Version A gets displayed to User Group A while Website Version B gets displayed to
User Group B.
Then gauge each audience’s reaction to the website they’re shown: how many
times they click, how long they stay on the page. Each time they do something that you
desire, call it a conversion. In this case, we’ll say that our website is an ecommerce
platform that sells ebooks: a conversion occurs when one of our websites sells an
ebook.
If User Group A clicks more on Website Version A, and subsequently Website
Version A sells 20% more ebooks than Website Version B does when it is shown to
User Group Byou might be able to say that Website Version A has been more
effective than Website Version B.
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We can say that Website A has had more conversions than Website Bbut we
cannot conclude anything until we test for the significance of our results.
In statistics, the notion of significance comes down to whether or not our results
are extreme enough that they could not have happened under normal circumstances. In
this example, in order to be forced to conclude that something is happening, the sample
sizes of the user groups must be large enough, and the difference between the two
must be extreme enough that any variation could not have happened by chance.
There are different methods to determine significance. Many A/B split testing
platforms such as Optimizely will do most of the work for you, but if you want to do it on
your own, there are plenty of calculators that simplify the math using established
statistical methods such as the ChiSquare distribution. All you have to do is click a few
buttons. Here is one example of that.
If our A/B test satisfies the significance criteria, we can safely say that Website
Version A is more effective than Website Version B at driving conversionsi.e driving
people from becoming viewers of your website, to clickers onto different buttons, and
ultimately, to purchasers of ebooks. In this case, we would stick with Website Version A
because it is better at accomplishing our desired goalit turns more visitors into
purchasers.
This is a very important concept in digital marketing. The path between having
people visit your site and actually interact with it is one that is fraught with meaning.
You can visualize the process as a funnel. Let’s say that 100% of people come
into your websitethen about 3% of these click the button to buy to an ebookthen of
that 3%, a further 10% actually check out with itthis ultimately means that 0.3% of
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people who come to your website are converted into purchasers of your ebooks. You’d
have a 0.3% conversion rate.
If Website Version A causes 0.3% of visitors to purchase vs 0.1% of visitors who
would purchase on Website Version B, over the long run that slight margin can mean
the difference between a million dollars in profit, and three million.
This is the power of the datadriven mentality. Companies like Server Density
have used A/B split test experimentation to drive a doubling of revenue.
Server Density tested two different ways of pricing a product, one predetermined
in packages by the company, and the other where the user could configure it
themselves, and pay for what they saw themselves using. In other words, one package
was curated, while the other was chooseyourown.
The company aimed to test a theory: would the increase in the value of each
curated orderthe preassembled packages determined by the company were in
quantities above what the average consumer had ordered at the timeoutweigh the
decrease in clicks that came when customers were forced to accept a package they had
not made themselves?
In other words, would customers leave in high enough numbers to undercut the
increased revenue Server Density would get from configuring packages at increased
prices? Would the company lose sales by effectively increasing their price in this
manner?
The answer, after an A/B split test, was a conclusive nothe version where the
company determined packages, and increased the price decreased the number of
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sales, but overall revenue increased as the heightened price took effect and more than
balanced the loss of quantity of customers.
Revenues doubled. Quality outweighed quantity.
Server Density set out to change its pricing structure to the predetermined
package that worked so well in A/B split testing, ensuring that the doubling in revenues
would continue.
This is the basis of web analyticsfinding funnels between users coming to your
site, and desired results.
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What a web funnel looks likesource: Wikimedia.
Finding ways to make these funnels work best for you is the challenge every web
entrepreneur will face. Testing experiments, and seeing what leads to better results,
continually refining what happens when somebody visits your web or mobile
productthat is the key to success in digital entrepreneurship.
Progress is measured in small ticks of percentage points going up. Eventually,
through the growth hacking mentality of experimentation, and a set of tests to measure
the results of that experimentation, we can find which tactics work best, and which don’t
work at all. It becomes a matter of repeating what works well until it stops working. Then
the experimentation begins again.
Just like the Lean Startup prescribes, you’re learning by doing rather than holding
a whole bunch of theories.
The learning never stops. You experiment, test, measure, experiment, test,
measure and do it all over again to search for that next elusive growth factor. This is
what means to have a growth hacking mentality. This is what it means to be
datadriven, and lean.
The data will tell the tale of the tape. It’ll tell you if you’re going in the right way.
Whenever people ask me for advice, I say a bunch of stuffbut at the end I
always remind them: it’s the data that will tell if I’m right or wrong. If something I said
caused you to grow a lot then I was right, and I’m happy, but if something I said has
decreased conversions, well then I was probably wrong: and I’ll be the first to admit it.
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You have to be agnostic when it comes to the data, but also nuanced.
There are mitigating factors: numbers are not everything.
The numbers are only as important if you are measuring the right things, and
make them relate to your core businessremember that when you’re looking at
numbers, you are really looking for signs of how well your business is doing. Make sure
that you have the right growth metrics defined.
There can be a murkiness, reasons to do things that the numbers wouldn’t lend
themselves to. Sometimes things do make sense regardless of the numbers you have
now: the value of your brand might be hard to measure, but that doesn’t mean you
should ignore it. You might get away with giving out products for freeand that will
boost conversions for you for a very long timebut think of the brand image of
somebody that constantly hawks something for free. You may just find that your product
will be devalued in the eyes of your user.
That said, most of the time, you’ll find that if you’ve chosen the right set of
numbers, then you should follow them. They are the confirmation of your hypothesis, or
the rejection of your faithbased assumptions. Just don’t be blind about what the
numbers actually mean, and get a sense for when you should use both numbers,
intuition, and longterm objectives.
Don’t chase shortterm numbers at the expense of longterm strategic vision.
Numbers are the tale of the tape, the scoreboard for what works and what
doesn’t work, but they can miss things.
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If you listen to them in the right context, your startup will have an advantage. If
you act on those numbers in an intelligent and rapid manner, that advantage will only
grow larger.
Again, in a startup, the number of your advantages are small. You must take
every one you can get.
We already talked about the importance of being nimble and flexible, and here
with a datadriven mentality, you can draw an advantage from how the results of your
experiments can be considered rationally by a selective group of people.
In large corporations, any experiment that is run typically involves a large amount
of resources, and buyin, such that a lot of people can feel personally attached to it.
Once you start something in a megacorporation, it’s hard to stop it, even if it doesn’t
look like it’s working.
Who can forget Coca Cola’s New Coke debaclewhen Coca Cola saw Pepsi
gain the largest sales growth in a month while the company fumbled with a disastrous
transition from the classic Coke formula to a new one. The marketing flop cost Coke
dearly, and months later, it was forced to retreat back to the traditional formula.
In a startup, you have nowhere near the resources, and nowhere near the
commitment. If you’re in a leading position, you have to be able to swallow your pride,
and change tactics if what you envisioned isn’t happening. You don’t have months to
burn on a wrong idea.
If you can manage to adapt quickly, your startup will be nimbler, and much more
used to going from failuretofailure to successtosuccess. You will be able to explore
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exponentially faster than your competitorsand if you explore well, and get all of the
data you needthen you will be much closer to accomplishing your goals.
You’ll be able to take the time and sit down with users of your product, querying
them about their experience via email, social media, or other channels of
communication. There won’t be so many that you’ll be overwhelmed just managing
them all: you’ll be able to have indepth conversations with everybody on what might
have gone wrong and what is going right.
With the ability to care, you’ll be more easily forgiven then the giants who don’t
seem to like dealing with individuals, and you’ll learn a whole lot more about the people
who are using your product.
Surveys that collect data from these users and offer them discounts and prizes to
reuse the product are some of the most effective ways I’ve seen to interact with users.
You collect data on a variety of users, and get them pumped to use your product all
over again now that you’ve shown that you care what they think.
By finding out what makes frequent users tick, you’ll more easily find ways to
attract and retain the same type of user. Knowing who your product helps can help you
immeasurably.
Incorporating your users into the building process is one of the most important
things you can do.
If your startup is a David to the Goliaths of the world, your ability to run nimbly
through data, and the ability to care about your users and learn from them intelligently:
these will be your slingshots.
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Technology Stack
One of the most daunting questions most entrepreneurs face, especially
nontechnical ones, is which technology should I use to build my platform?
Many nontechnical founders have no idea where to begin. Sometimes, the
choice is almost made haphazardlywhoever picks the first language wins. The first
technical person on the team runs the show.
Yet the choice of coding language, and the team members present can make a
huge difference in the startup’s potential. It should not be chosen by the first contractor
that you can lay your hands on.
The right technology stack can be one more slingshot for David. The wrong one
can sink a startup.
By the end of this section, you should be fluent enough to understand the basic
technology that powers startups, and get a handle on the right programmer to contact.
You need to have a methodical approach to choosing what technology your
startup is built on, and who is implementing it. We can start by discussing some of the
most popular options, and some terminology.
The most popular languages among billiondollar startups is Javascript. This is a
language that has always seemed to be aroundin fact, it was created in 1995. It has
recently seen its star rising rapidly because of the rise of frameworks that allow for
Javascript to build web applications very rapidly, and seamlessly, and become a
programming language capable of doing much more than the simple web scripts it was
originally designed for.
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Frameworks are large blocks of code that you can call on with simple directives
in the language that the framework is built around. JQuery is the most famous
framework for Javascript, with one or two words in JQuery being enough to create
applications that can pick dates for you, and autocomplete certain words. The one or
two words in JQuery call upon many lines of code in Javascript, doing work
behindthescenes that makes your life easier as a programmer.
So many frameworks have evolved for Javascript now that Javascript can
become a full technology stack.
That means that every function you would need to build a web application can be
built endtoend with Javascript. You can use Angular.JS to control what the user sees
on your website, and to make it more interactive. You can use Node.JS to host a web
server that can keep your content connected to the Internet. You can use Express.JS to
decide how and where to transmit information between your different Javascript
components. Finally, you can use Mongo.DB to store all of the data you want to display
to users, and all of the data you collect from them such as login credentials.
Here, some common terminology comes into play. What your user sees is
typically termed as clientside, or frontend. Angular.JS would be the framework
responsible for controlling the frontend in this case, or what is displayed to your users.
The backend, or serverside, are data processes that are hidden from users, and they
happen when your web server is processing informationin this case, you might be
using Node.JS to manage those processes.
A perfect example of what would be managed on the backend would be the
login credentials that your server has to passit’d be deadly if users could see them
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pass through your data process on the client side, since it’d be trivial to steal passwords
and other confidential information!
When a user interacts with the user login form, they are working with the
frontend or clientside. When the information passes through to your server, and is
validated, you are now working with the backend or serverside: importantly, this
process happens on your secured server, something that the user and hopefully nobody
else will ever see! When the information comes back, and the user sees they are logged
in, you are once again dealing with the frontend.
The data that passes through frontend to backend is crucial to animating
websites, and making them interactive. They dictate what happens when a user clicks
anything on the site.
In many ways, the web can be conceptualized as a giant trove of data, collected
from human and machine input. The information that is carried travels back and forth
through many portals, eventually ending up on a monitor, whenever an internet user
requests it. Think of a photo that you took of your friends, tagging it with their names,
and transmitting that across physical borders, and oceans.
The Internet, at its core, moves data.
A standard format for transmitting data across the web is Javascript Object
Notation. We will discuss this further in the Big Data section, but for now, we can say
that it is a lightweight dataexchange format that is readable by machines, and able to
be manipulated by Javascript code.
Mongo.DB, a handy Javascript database solution, works in a format similar to
JSON called BSON, and it can interact with JSON and your web application through a
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service known as Mongoose. This allows you to pass data easily from your web server
to a database that holds all of the information you need. You can create, manipulate,
remove, and move data entries in Mongo.
All of this can be done in Javascript. It’s what has become known as the MEAN
technology stack, an endtoend technical solution that can build whatever application
you need with one coding language.
The Meteor.js framework promises to be even quicker, giving people the ability to
build web applications in a fraction of the time it used to take, even with MEAN tools. It
too is built on Javascript, and relies on Node.JS and MongoDBsomething where with
one language you can build something rapidly from the ground up. Interestingly, it loads
resources without any need for a serverside, promising even quicker display of
websites, though it still remains in an experimental stage.
If you want to understand the basics of Javascript, here are some resources.
Beyond Javascript, Ruby on Rails is a popular web framework that is designed to
get websites up as quickly as possible, and to make maintaining them easy. It’s based
on the intuitive language Ruby, which was meant to be as close to the natural
languages you read and write in as possible: in some respects, Ruby resembles
English, and its intuitive fashion of commanding machines is meant to be understood by
people with very little programming experience: in fact, there is even a children’s book
focused on learning Ruby!
With only one programming language and a little bit of learning, you can build
something workable within a few days or even within a few hours.
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This wasn’t always the case. A lot of older, more established companies, and
some startups today still use the full LAMP technology stack. The appeal of LAMP is
that all of its components can be free because they are open source, something we will
discuss in more detail later on, but the LAMP stack was very much about mixing and
matching these technologies, instead of having a consistent language from one end to
the other.
You can use HTML/CSS and certain Javascript libraries to power the frontend,
and then the backend can be managed with languages such as Python or PHP,
opensource languages that are used by scientists to analyze data, and by startups to
build massive web platforms. Your web server can be hosted with Apache. You can
store your data with opensource MySQL.
The choice of whether to go with a new stack like MEAN or a old one like LAMP
will make a lot of differences. New experimental stacks offer the ability to store data
more quickly, and have more interactive websites, but they’re not as triedandtrue as
old technologies.
You will find a lot of startups use new technologies: that is the point of having a
cuttingedge enterprise. They will take on more risk, and hire programmers of a certain
type because they’re looking to cut fresh ground. Yet there is much to be said about
having testedandtrue frameworks.
You can use a CSS framework such as Bootstrap or Foundation to manipulate
the front end, and change the appearance of your website.
HTML dictates the structure of your page: how elements of your page are placed.
Tags of HTML languages such as <b> </b> determine that all of the text within those
tags is bolded. So <b>code(love)</b> would be code(love).
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HTML tags called <div> dictate the placement of elements of code that can be
augmented with CSS for style or JavaScript for interactivity. CSS, known as cascading
style sheets, are a way to modify the style of HTML elements at a global level. For
example, if you attached CSS font size requirements to HTML paragraph tags, every
paragraph will have that same font size. Ditto for color, font format and anything else
that can be selected with CSS.
JavaScript can then help create events that help pop up forms, and interact with
the user once they’ve done certain things with your HTML: for example, if your user
clicks a button, Javascript can ensure that a popup with the right message is enabled
afterwards.
Now, with the world moving to mobile devices, you will also have to consider how
your platform will look across all sorts of different screen sizes. CSS frameworks offer a
degree of responsiveness, which means that across different screen sizes the HTML
and CSS reflects differently to fit everything into a smaller cell phone or tablet.
Mobile applications are the square icons you can download directly onto your
phone to access technology on the go. They allow you to access native capabilities
embedded into different phonesin many ways, the digital economy has been
characterized as the rise of the app economy, thanks to stalwarts such as notetaking
app Evernote, taxihailing apps Uber and Lyft, and communication apps such as
Snapchat.
In order to build a mobile application for the iOS ecosystem of Apple products,
you’ll need ObjectiveC or Swift programmers. The Android ecosystem will require Java,
but will allow you to program applications for a wide variety of smartphones and smart
devices such as Samsung products.
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There are so many tools out there for you to build with.
The tools you use will determine the builders you take on board, and what you
can build to a certain extent. The newest singlepage applications with different views
happening in the same page are often based on Javascript. Pinterest and Instagram are
run partly on Python’s triedandtrue DJANGO framework.
It is important that you have a role to play in this decision, even if you’re
nontechnical. Any technical venture you build will become infused, and strengthened
by the technology you use, and it will very much form a part of the culture of the team.
It’s also important to know when you need technology, and when you don’t.
Jeff Atwood, the founder of StackOverflow, a Q&A forum specifically designed to
answer programming questions (and a great resource if you’re unclear about all of this)
does make an astute point that programmers tend to create software just because they
want to create software.
Remember, you don’t need a technical solution just because you think you need
one. Are you thinking of building a blog? You don’t need a programmer to build you one,
you don’t need to build one yourself you can get acquainted with the intuitive what
you see is what you get content management system that is Wordpress, and build a
blog with it yourself, without any programming knowledge.
For the ventures you want to build outside of established frameworks, knowing
what each technology enables, and the limits of each one, will be crucial to staking out
your place in the new digital economy.
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It will be essential to your ability to be part of or direct teams of technical and
nontechnical people into crafting the digital experience of the future.
I often write about the programming skills you need to understand to do this at
code(love) because I truly believe that knowledge is power.
Now that we’re familiar with the technology that goes into building a startup, you
should also know about the team that typically builds it.
One of the staffing issues I had at ThoughtBasin was that I hired a designer only
for his illustration skillsbecause I thought that was all designers did.
In reality, the role of a designer on the front end involves a mix of code, user
experience, and design. The ideal candidate to handle all of your frontend would be
some ace coder who knew HTML/CSS and animations very well, while knowing
Javascript and the Javascript libraries to make it fully interactive. They would be able to
get images and designs ready on Photoshop, and be able to think from a user
experience point of view to make it as simple as possible for users to use the product.
The ideal candidate is, in summary, a magical unicorn.
You will most likely have to split the roles at some phase in your startup, perhaps
even the earliest, if only because people who can do everything well are very rare and
expensive. You still have to be careful though.
One of the biggest mistakes I made at the beginning with ThoughtBasin was
thinking that I could get my designer to only take care of how the site looked, and have
somebody else integrate it. Big mistake. The designer was very talented, and the
person doing the integration was very hardworking, but there was a mismatch between
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the two that made it harder to get the details just right, a mismatch between two people
with very different styles.
Ideally, you want a designer that can code very well so that there is no mismatch.
Good luck finding that person.
For the back end or your server side, you’ll most likely get an experienced
fullstack engineer who can, in a pinch, make things look relatively nice on the front end,
but isn’t specialized at doing so.
This handy person will most likely be the most senior person on your team,
somebody responsible for passing data back and forth between the server and the
interface that faces users. They will have earned the title fullstack because they will
know how to deal with every component of the technology stack in some way, at a
proficient level.
That person will lead technical teams on both the front end and back end.
Eventually, if you are successful, you will start hiring more and more specialists to round
out a team of versatile “Swiss Army Knife” team members, the jackofall trades types
you will need to keep your startup chugging along.
Your new specialists, from growth engineers to user experience consultants, will
ensure that the data you need to pass between your client and your server continually
moves the direction it needs to in order for your idea to flourish.
API
If one thinks of the Internet as a way to pass data back and forth, then the next
question naturally becomes: what paths must that data take?
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The modern web uses a set of standards known as the application programming
interface, or API for short, to define how software parts interact with one another.
You can access the data of other applications with an API: an example of this is
the Twitter API, which you can use to make remote calls to display, on your blog, a
dashboard of your most recent tweets.
The API in this case is a set of instructions that defines how the data is
communicated: in this case, the Twitter server will be sending you information that your
server will process, and then on your side, you will determine how you display that
information.
You can build on top of the data that Twitter is assembling about its users.
This wasn’t always the case. In fact, APIs in the past used to be designed for
internal company use, standards hidden away from the public that helped programmers
within its’ walls move data, but excluded those outside.
APIs such as Twitter’s API used to be designated as “open APIs”.
Now, the term open is unnecessary.
Companies like Flickr, the original photosharing application that first made photo
uploading intuitive, revolutionized how we approached data.
Flickr shared its API, and data standards, hoping that people would use it and
build upon the photos they had assembled. It worked. Bloggers adopted it en masse
back when photo uploading was a significant pain point, and the API revolutionized how
Silicon Valley thought of information.
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Instead of hoarding it into a proprietary standard, the default became sharing it
with the public so that they could make use of it, and grow different applications out of
the data Flickr was providing.
Stewart Butterfield, the previous founder of Flickr, and the current founder of
Slack, a tool that reimagines chatrooms and communication for the companies of the
future, has an interesting take on why he pushed for open standards when it came to
Flickr’s API.
As a child, he grew up on a commune with his parents. He was a philosophy
major who took on Silicon Valley. With a different upbringing and mentality than most of
SIlicon Valley, his way of approaching problems was different from the norm, and he
sought to bring that mentality to everything he saw around him.
As he puts it: “The idea that we should be open and interoperate with our data
resonated with me.”
Sharing is the new default of the digital economy. It is the open API pushing
forward that mantra, and making it live through the open sharing of valuable data, the
currency and lifeblood of the new digital economy.
From being able to instantly pull up addresses and locations from Google Maps,
to being able to push important data to the new smart watches of the future, the open
exchange of data has changed the way we behave, both online, and offline.
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Early Adopters
Thank you to Rapheal from Hashtag Consulting for proposing this term.
As much as data passing back and forth is the lifeblood of the Internet, the
innovation that makes the Internet magic starts with new ideas that are built on this
data.
These new ideas often require different ways of behaving.
They require a special set of users that are willing to try new things, and that are
willing to evangelize for you, and spread the word about the hot new product they’ve
tried.
Those users are your vaunted early adopters and innovators.
Source: Wikimedia
As you can see from the graph above, they’re not so easy to find. The people
willing to take risks and try out new things are few in number in comparison to the
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mainstream. An early adopter is a risktaker, somebody that is comfortable putting their
name behind something unproven, and raw.
You won’t be able to find a lot of these early adopters loitering around.
One of the things reddit, the online community of communities, and now a site
that draws millions of people, used to do was fake a number of users just so that it
looked like there were a bunch of people who were early adopters. It lent legitimacy to
the platform: at least some people were using it, making it much easier for other users
to join the fray.
At ThoughtBasin, it took us weeks until we got actual responses to any of the
proposed case studies. Weeks! Even then, it was really hard to retain people who did
make a response, and get them to do anything else on the site.
It is Geoffrey Moore’s book Crossing the Chasm that originally focused on the
difficulties associated with marketing bold new hightech products. This is based on the
diffusions of innovation theory espoused by Everett Rogers, the same concept as we
see in the chart above. The basic theory is this: a minority (Everett Rogers claims about
16%) are the early adopters you have to convince before you get to the mainstream.
The chasm is based on the notion that you have to convince one group at a time,
and the most difficult transition is between the early visionaries who are used to trying
new things and the early majority of adopters who are used to playing it safe.
The division between the two groups is the chasm. How you cross it will
determine how your startup will grow among mainstream adopters, and ultimately, grow
into something that will be used by thousands, if not millions.
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To cross the chasm requires knowing how to get early adopters enthused, and
then switching over to get the mainstream to adopt, knowing that these are two different
groups with different traits.
To do so, you have to build an innovative solution that gets people hunting for
new things excitedand then tailor that innovation to the larger public. You have to
realize these are two different groups.
Twitter started as a solution for people to text message in snippets of their lives
with their cell phones.
When Twitter first started, it wasn’t very obvious what it was meant forthe
famous prompt for Twitter was “what are you doing?”so it became a
streamofconsciousness prompt for early adopters who were so enamoured with their
phones that they would message what they were thinking at any given time, and see it
posted on a public web platform.
Despite it being the norm now, it wasn’t quite something that people were used to
in the late 2000s.
Twitter went on a ferocious campaign of getting celebrities onboard, and getting
them to post their thoughts, and interacting with the platform. They made onboarding
tutorials to get new users used to Twitter, and built in features such as hashtags in order
to make content more relevant, and easily searchable. They switched the input device
from SMS text messages to direct messages to the platform, then created a mobile
application, all so that mainstream adopters would feel comfortable with Twitter.
Facebook started as a virtual yearbook for Harvard students, possibly one of the
narrowest group of early adopters you could fathom.
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The earliest version was of a platform where you could evaluate the
attractiveness of everybody in the university. It was a crude system that garnered plenty
of wellwarranted criticismbut it shut down the university network due to its
overwhelming popularity.
From that early base of rabid adoption, it soon evolved into a platform for
different university students to interact with one another. By taking the lessons they
learned from that early Harvard base, they managed to connect with university
campuses all around the world, eventually making the leap to convincing mainstream,
middleaged adults to make the jumppropelling Facebook from dorm rooms to board
rooms across America.
Both Twitter and Facebook crossed the chasm, and got mainstream adopters to
try their product. They survived long enough on a rabid base of early users to make it to
the next step of the product life cycle. Through all of their experimentation with early
adopters, they figured out how to cross the chasmand ultimately, how to get the
traction they needed to become billiondollar enterprises.
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Traction
This is one of the most powerful startup words there are, yet also one of the most
ambiguous. When a startup finds traction, it suddenly becomes something investors
need to put money into. Before that, it’s an idea searching to be a product, an ugly child
that commands neither respect or admiration.
When a startup gets traction, blood rushes through its veins. It grows to
something strong, and magical that distinguishes it from traditional companies.
I’ve worked for several startups now, and I’ve seen the magic of high growth.
Every hour, you can feel new users coming in. Weekly growth rates about 10% were not
unheard ofin fact, sometimes, they became the norm.
Paul Graham has been on record as saying that in his prestigious Y Combinator
accelerator, home to some of the brightest startups in the world, a good growth rate to
shoot for would be 57% weekly. At that rate, a small twoman garage outfit can very
quickly become a multimillion dollar outfit in a few years. In a decade that can become
a billiondollar company.
The man knows what he’s talking about. Y Combinator has graduated startups
such as Dropbox, AirBnB and Reddit that drive millions of users, and are worth billions
of dollars.
In this post that defines what a startup is, PG (as he is affectionately known in
startup circles) drives forward the point that a startup isn’t just any company that has
just been created. It isn’t a new barbershop, or a new grocery store. It’s a very special
type of model that is designed to grow from idea to business at a monstrously fast pace.
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When it hits that pace, a startup uncovers the mysterious traction everybody
wants, and becomes a mythical unicorn.
Traction is what happens after you achieve “productmarket” fit, meaning you’ve
finally figured out an effective way to solve your users’ problem. Your users have
responded by adapting your product en masse.
Naval of AngelList describes that fit as “quantitative evidence of market demand”.
‘Traction is quantitative evidence of market demand’ Naval Ravikant
From a Lean Startup point of view, it’s when you’re starting to outperform your
key performance indicators, and you’ve seen notable growth in what matters for you:
profitability, number of users, revenue, or clients. You have a sustainable base of users
that proves that the idea you have solves a very real pain point.
It’s when after all of your experiments, you will have hit something that works,
and can be replicated. You are finally in the stage of finetuning and expanding your
growth engine.
Now you’re in a race against time to put your validated solution in front of as
many potential users as possible. When you’ve hit the stage where you’ve figured your
product out, this should be much easier, as users will bring in other users, and you’ll
often be the talk of the town.
You are beginning to hit scale, and the glories and problems associated with it.
At the beginning, you might have been able to manually onboard everybody to your new
solution: you might have been able to meet every one of your users either facetoface
or virtually. You might have been able to solve everybody’s problem for them, applying
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the David’s slingshot of individual relationships, and quick, nimble decisions. Now
though, your growth curve has changed from spurts of activity to a consistent explosion
that is bending forward, looking a bit like a hockey stick of exponential growth.
World population: an extreme example of exponential “hockeystick
growth” https://www.flickr.com/photos/mplemmon/3203403780/
You’ll have to deal with the scale of your operations. Instead of having one or two
individual users to deal with at a time, you’ll quickly find that with explosive growth,
those few users will become a cascade of dozens.
Perhaps you will need to hire more team members to shoulder the work. Perhaps
you will need to develop automated ways to contact your userssolutions like Hubspot
or Intercom.io that do just that.
Your growth will build on itself, as more and more people know about your
solution, and more of them talk about it, getting you new users through organic word of
mouth without you having to budge a finger.
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Being the talk of the town will grab you media attention that matters, as incoming
users will find themselves easily using your refined product. They in turn will become
adopters of your product and drive more and more people to it. There is a virtuous cycle
of wellearned attention turning into users who will spread the word for you, creating
more and more users of your product.
You will have crossed the chasm.
You will have gotten the traction you need to grow.
Now it’s on you to take that traction to dominate your field.
Venture Capital
The beauty of software ideas is that they’re often cheap to test, and they’ll be
quick to grow if they’re in the right place at the right time. Sooner or later, however,
you’ll hit a wall on what you can do for free.
Remember, software ideas may be cheap to testbut that also means that you’ll
have plenty of competitors around you. When push comes to shove, the superior
solution often wins over a marketplace. If you’re not the superior solution, you often
have to fight over the crumbs left over from the winner.
Nobody likes fighting for crumbs.
You’ll need to win the race with all of your competitors in order to avoid that. At
this point, you will either have to fund the idea yourself, or look to external funding to
accelerate your growth.
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Most people start off an idea with it being selffinanced, and that can be quite
sufficient for a while, but the reality is serious user acquisition can only go so far with a
small team, and little money. If you’re looking for millions of users, you’ll need some
serious money.
This problem manifests itself in different ways depending on the nature of your
business.
If you’re a businesstobusiness solution (often abbreviated as B2B) such as
time management software that helps other businesses optimize their schedules, you’ll
eventually figure out that you have a long sales cycleit takes a long time for
companies to agree to try your new solution, and then adopt themselves to using it.
Adoption requires a cultural shift. You can have a whole lot of leads, but it’ll take
a long time for them to convert into recurring revenueand in the meanwhile, you’ll
have engineers and sales teams to pay.
For the next killer consumer application that records videos in 30 minute spurts,
you need to create a strong network. There’s no point in having a content network if
nobody is producing content.
There’s a rule of thumb herethe 90/9/1 rule. 90% of your users are passive
spectators, looking for new content to consume. 9% of users will look around for
content, and organize it in a coherent way for the 90%. 1% of users create most of the
content, and assemble huge followings. In order to get to that 1%, your network has to
have a strong enough userbase so as to support the need for visibility for content
creatorsand to support enough content being built so that those spectators come in
the first place.
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What this often means is that consumer applications must acquire users
monstrously fast, which often requires paid advertising through Facebook, Google and a
whole bunch of social outlets.
There are organic ways to grow very quickly: Dropbox, a storage solution for files
hosted on the web offered free space if you invited your friends to come in. Uber, a
mobile application that can hail you a cab at the click of a button, will give you a promo
code you can send to your friends if you use the product. You can also use it for
yourself, ensuring that you and your friend both benefit from your generosityand that
Uber gets two users for the price of one.
Still, there’s a limit to what can be achieved with just those tactics. Eventually,
you will have to pay for customers to find you through search engine or social media
advertisements, and you might even have to pay to reengage them through ad
retargeting if you want to create a massive user base of active participants.
Ad retargeting ensures that people who have visited your site will be served ads
in order to hopefully turn those onetime visitors into frequent returning users.
Retargeting gives your visitors a sense that you’re everywhere, and that you’re a larger
company than you actually are, great ways to convince visitors to become engaged
users.
It is also something that will become quite expensive, with rates above what it
would cost you to serve ads in the first place.
You will have to pay for a rockstar team to build your product out. This will
probably be your greatest expense from the beginning to the end of your startup’s
ascent. Your ability to pay your team members consistently will determine whether or
not your startup will survive.
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You won’t have the money to do all of these things at the level of billiondollar
startups. If you can bootstrap, or fund the startup by doing consulting or side jobs, or
drawing money from the business itself to fund itthen take that route. If you can build
a business without relying on external funding, then you’ll have the best of both worlds:
control over a great business you built yourself.
There are many who have gone this route. Grubhub, a business that does online
ordering for restaurants and takes a cut of of those online sales was able to grow by
building on its own revenues. The founder, Mark Evans, has written about his path to
doing that, and Grubhub is now a publicly traded company on the New York Stock
Exchange. It is entirely possible to start with one person, one idea, and absolutely
nothing to creating one of the largest corporations in the world. It’s just much harder.
Maybe you’ll want help along the way. Maybe you’ll need it.
Perhaps you will take a tour of startup incubators, organizations that shelter
startups through their early stage by offering them mentoring, some funding, and office
space to shelter the team as they work. These will prepare you for future funding
rounds, giving you enough time to test out your product and get your first users
onboard.
The Montrealbased example of a startup accelerator is FounderFuel. The most
prestigious in the world may be the aforementioned Y Combinator and 500 Startups
based in Silicon Valley. All of them operate under similar conditions: they’ll take a small
percentage of your company (usually under 10%) for an amount of money that will help
you make and market the first proper version of your product.
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Consider it like an audition for whether or not your business has the bones to
make it at a mass scale.
You will need more money to determine that if you don’t get revenues streaming
in after to replace your expenses.
This is where venture capital comes in.
Your first round of financing typically comes from yourself and the F&Ffriends
and family who believe in you and your idea.
You’ll then want to search around for organizations around you that give grants,
and other training to young entrepreneurs. In Quebec, my first external funding came
from the SDEVM, through a grant program known as the Jeunes Promoteurs program,
which gave me a hefty amount of money for being a young entrepreneur looking to start
things.
The search engine Fundica led me to that solutionand it has a whole host of
other grants available for entrepreneurs. Make sure you exhaust all of your options and
need money to grow before you give up chunks of your company.
After grants are exhaustedyou might take a tentative look at loans. Loans will
only work if you have a personal history with a bank. A startup, even one that is
incorporated, will be forced to place any creditworthiness on their founders.
It might still be a viable option, certainly better than giving up large chunks of
your startup for paltry amounts of money if investors are getting you bad terms.
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You should have hit some amount of traction before you raise money from
anybody who wants a piece of your company. I’ve seen too many people give up more
than 50% of their company for less than $100,000, a huge detriment that will mark that
company for failure. It’ll mark the founder as somebody who sold out too early, and it
will give basically all of the upside of the venture to the investor, and not the
hardworking entrepreneura terrible formula all around.
You should be at the point where you’ve figured out your idea is a business, and
you have a path forward for more growthand that path forward has to be paved with
money.
Once that’s the case, you should search out angels: a stage of financing outside
of your intimate circle of friends. Angel investors are people who fork up a small bit of
cash (about enough to cover a programmer’s salary for half a year or so) for a small
percentage in the company. They’ll also bring their experience and advice to the table,
helping you make the right decisions.
These investors are called angels because they will often take less equity and
give more help because they believe in the entrepreneur. They can be friends or family
members of yours elevating their informal stake to a professional relationship.
It’s important at this stage to seek out investors who know what they’re doing in
the space you’re in. If you’re a startup focused on recruitment, but you get a lot of
investment from somebody who got rich selling fitness goods, it might not be the best fit.
An angel who has worked in recruitment for decades will bring experience and a
network of HR professionals who can buy your product.
Nowadays, there are networks of angels who dedicated to supporting
entrepreneurs. Angellist has a list of individuals and groups looking to invest into
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entrepreneurs, and bring their knowledge and network to bear. Their new feature,
syndicates, allows for there to be money pooled under one influential investor, giving
noted angels the financial clout they need to make a significant difference.
There is also equity crowdfunding, recently legalized in America under the JOBS
act. We’ll discuss this more in the crowdsourcing section later on, but for now, consider
it an alternative where you take money in for shares in your companybut instead of
pitching it to individual angels, you pitch it to the general public and a larger crowd that
invests less individually, but gives you a significant war chest in aggregate.
Once you’ve figured out your business model, you’ll want to look for institutional
venture capital, money that comes from firms specifically made to invest in more mature
startups. You might take a short journey through a startup incubator while you get there.
Venture capital firms will typically be formed of general partners who run the
operations, and limited partners such as hedge and pension funds that provide most of
the funding. The general partners are the ones that you’ll have to convince on the merits
of your ideaand they’ll be very wellversed in the art and science of building great
startups.
If you do convince them that you have a scalable idea that is growing well, and
could grow even further with their money, then you will receive either equity financing
(money in return for shares in the company) or convertible debt from them.
Convertible debt means that you’ll take on a loan that will change into shares of
the company for your investors given a set of conditions. This is most often triggered
when you begin raising another financing round. A lot of investors will prefer this model
of financing because a loan will accumulate interest if left unpaid, and because it avoids
the trickiest aspect of startup financing: valuing a company.
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Valuing a startup, especially one that hasn’t made any money yet, is probably
one of the hardest financial mindtwisters imaginable.
You might be able to take earnings, if there are any, and follow a plausible
hockey stick of growth, projecting future earnings with some reasonable growth
assumptions. You might take a look at the number of users and the time they’ve spent
on the service, and what money you could eventually drive from that behavior. You
could value it by the team members who are part of the startup.
Given that so many startups go through acquihires, or acquisitions driven solely
by the value of new hires from the old startup (which is then promptly shut down), an
acquihire valuation that sums up how much everybody on the team is worth might be
reasonable.
The reality is that some investors want to avoid the headache of startup valuation
altogether. And maybe you do too. If you take a high valuation for your first round, and
then another set of investors takes a look and gives you a lower valuation, that could
create the kiss of death known as a “down round”or in a world of constant, explosive
growth, how your startup actually ended up shrinking in value.
Convertible debt is the solution. It ties up all of that messy scenario in a neat little
bubble by leaving the valuation to a later round of financing, one where the investors at
hand might be better at gauging exactly what the nowmature startup is worth.
Let’s start at the beginning.
You will typically raise a seed round first then the lettered series beginseries A,
series B, series C all the way until, if you make it, an initial public offering where all of
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your private shareholders will get rewarded for seeing the monetary value they placed in
your company being reflected in public markets where anybody can trade your shares.
This process takes much longer than many people expect. A lot of people who
are just getting into the startup game expect startups to be a very quick gamea quick
in and out.
The reality is startups are a very long adventure. Conventional wisdom says that
it takes up to ten years to test if your idea is a viable business. There are only two
successful “outs”either you get acquired by somebody else, or you go public.
Twitter took 6.4 years to go from its first round of serious angel financing to going
public. Nearly a decade passed before the founders got together to think this idea
through, and then saw their efforts rewarded on the public stock market.
This is a section that can go on forever, with even more buzzwords thrown out
there. At this point, it’s good to stop and get some perspective from both sides of the
table. EntrepreneurturnedVC Mark Suster runs through the process both from his
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angle as an entrepreneur, and what he sees as an investor: an informative read that
delves deep into the broad themes of venture capital, as well as the smaller but
indispensable details.
Brad Feld, one of the most respected venture capitalists in the world, has written
a series on the terms you’ll find on a term sheet, an offer to you from venture capitalists,
that goes much more into the details of what the negotiation of raising money looks like,
with every detail there sketched out from experience.
Remember though, that money is not the endall and beall of it. It is a part of the
trip, but nowhere near the final destination. When you start a venture, you’re not doing it
to raise money: you’re doing it build something and take advantage of the opportunities
the future will offer.
“Money is like gasoline during a road trip. You don’t want to run out of gas on your trip, but you’re not doing a tour of gas stations.”Tim O'Reilly
Don’t ever miss the opportunities of the future.
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THE OPPORTUNITIES
Ray Kurzweil, noted futurist and the current director of engineering at Google
once noted: “I'm an inventor. I became interested in longterm trends because an
invention has to make sense in the world in which it is finished, not the world in which it
is started."
In the spirit of that quote, these are the longterm trends that will shape the world
of tomorrow.
They are by no means the endall and beall of the future, but rather a sample
primer meant to inspire curiosity for more. Let’s begin.
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Internet of Things
When Kevin Ashton first termed the phrase, he must have had a small inkling of
where it was going to gobut with the evolution of this buzzword into physical reality,
even the wildest of visionaries might have never seen all of this coming.
Make no mistakethe Internet of Things is going to change how we interact with
the physical world around us.
Imagine if we could embed software principles into every device around us,
allowing software to collect data on everything around us without being confined to the
bulk of a laptop, or even a smartphone. Imagine machines that could sense when
conditions were changing, and adjust themselves accordingly without humans
managing every step of the process. Imagine a network of smart sensors that could
communicate with one another seamlessly.
This is what the Internet of Things offersand more.
The datadriven mentality that will drive the 21st century will see the beginnings
of an explosion of information, collected from a variety of devices. The way that
information is going to be structured and communicated will be left to the designs of
decentralized software designers. As we pass from physical space to another, the range
of possibilities afforded to us will be exponentially expanded, both as consumers of
data, and as people looking to tinker and build with the world around us.
We have had the ability to make sensors communicate with one another for quite
a while. Bluetooth, a wireless communication standard, has been around since 1994.
What has changed is how we can manipulate that data and build on top of it. The
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standards being set to define how people and machines can interact are being crafted
right now.
Montrealbased Reelyactive is a startup that focuses on creating a new type of
hardware that can track you through space. It is a radiofrequency tag that can vivify a
community by indicating exactly who is in a space at any given time. By tagging your
personal identity to a piece of smart hardware, the startup allows your physical
environment to adapt to you.
Their software can be used to track a car for parking reasons, giving a parking
application a way to know which parking slots are currently occupied. It could also be
used to build a system that can transcribe the properties of Google Analytics and other
digital tools to the physical worldand with that, the possibilities are infinite.
A grocery store could track exactly where their consumers go, and where they
tend to congregate within the store, creating the opportunity to optimize sales by
clustering their highestmargin products right where there is the most foot traffic.
You could also use Reelyactive to personalize every space. Imagine walking
back to your housethe lights dim to just the right level, your favorite song starts
playing, and your smart furniture activates. The heating is just right. You haven’t done
anything, yet you feel completely in your element.
Reelyactive’s founder, Jeff, describes this as the concept of “smart
spaces”turning everything around you in the physical world to a personal level that
has only been seen in virtual networks.
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The algorithms and methods that serve you exactly the right movies you like on
Netflix are now working with the physical world to deliver perfect tailored experiences for
you.
Marc Andreessen, a noted venture capitalist who played a huge role in the
creation of the Netscape internet browser has often been quoted as saying “software
will eat the world”. That has, in many ways, become the banner of the rise of startups,
the rallying cry of a new revolution in technology.
‘Software will eat the world.’ Marc Andreessen
Nowhere will his words ring truer than in the Internet of Things.
Locked inside this word is a raft of entrepreneurial possibilities. With every
physical device open to smart augmentation, and a system assembling to make sense
of all of the data created, the sky is the limit. Everything from smart watches to smart
lamps can now intelligently interact with their owners.
Software has even been linked to smart thermostats to help save on energy.
Nest fits itself to your habits, shutting itself off when it knows that you are going off to
work, automatically saving you energyand saving energy in aggregate. By intelligently
managing energy habits for individuals, Nest saves on energy billsbut also offers the
possibility of a smart grid that will automatically adjust for energy consumption patterns
across entire cities.
You may have heard of the term “smart city”. A large part of that is taking
connected devices and creating a network of data that helps policymakers and citizens
come together to make smart, datadriven decisions. It is a manifestation of how the
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Internet of Things will change things for the better. Nest can not only help individuals
save money: it can help societies be more efficient with their resources.
Urban.US is an accelerator focused on furthering the smart city.
Among its portfolio companies are Dash, a hardware solution that plugs into any
car and turns it into a smart car. The car will steadily collect information on driver habits
such as their speed and gas usage. This helps drivers realize the safety and
environmental effects of their driving habits, creating a safer city that is more
energyefficient.
SkyCatch uses the power of drones equipped with software to help industrial
partners capture the information they need on temperatures and mapping to make
smarter decisions. An aluminum smelter that requires temperature levels to be at a
certain level for safety reasons can easily deploy SkyCatch to ensure that they are
operating under the right conditions.
You or any other entrepreneur will be able to take physical devices just like the
Urban.US startups have, and imagine them into greater capabilities for more intelligent
societies.
‘The Internet of Things has the potential to change the world, just as the
Internet did. Maybe even more so.’ Kevin Ashton, originator of the term Internet
of Things.
You will be able to trace the path between what that device is doing now, and
what it will do in the future.
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You will decide what data it will be able to communicate to anybody who is
looking.
You will add to the amount of information we have on the world around us,
creating a more informed world with the potential for better decisions across the board.
These better decisions will lead to better results, better lives, and ultimately, a better
world.
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Big data
Big data is anything that can’t fit into the data tools that have been around for
decades. If you can handle it in Excel or in Oracle databases, then it isn’t big data.
Big data is a catchall buzzword for the tools nobody has ever heard of, or
needed until recently.
This is a function of the Internet being able to collect data at an exponential pace.
Eric Schmidt, chairman of Google, has said “there were 5 Exabytes of information
created between the dawn of civilization through 2003, but that much information is now
created every 2 days.” In reality, about 23 exabytes of data were created in 2002 alone,
but the premise that in a few days, we are creating more information than at any other
time in human history rings true.
The Internet of Things plays with this trend very well. With so many more sensors
deployed to capture data around them, the amount of data available for processing will
explode once more. Conventional solutions can never hope to hold the amount of data
millions of devices around the world will be beaming to one another, in realtime,
especially given that this data is often not organized in a coherent manner, and will
often have missing pieces.
The new big data solutions will involve processing massive amounts of
information across several servers, taking seconds to get insights from massive heaps
of chaotic information. Apache Hadoop, the open source framework that is most popular
for such processing, allows for people to map where data should go to be
processedand then maps and reduces data so that it can be processed across
multiple servers and then be reassembled for analysis.
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How will big data look?
Instead of the linear tabular form of data we are used to from the world of old, the
new world of big data will be much more nonlinear. The language of choice may be
JSON, Javascript Object Notation, a keyvalue pair assortment that looks like this
Source: https://c2.staticflickr.com/8/7234/7185560283_102f6b753d_z.jpg
As opposed to SQL which is typically organized like this in a tablelike fashion
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Source: http://upload.wikimedia.org/wikipedia/commons/f/f9/Session_MySQL.png
With NoSQL, you can select a value with its’ key without any tabular columns or
constraints on the data. With SQL, data has to be organized in a table: there have to be
columns, and each column value is paired with another column value.
With large amounts of structured data, SQL will be slowed to the point where it
becomes hard to process data.
Using the lessons Google learned dealing with vast realms of information,
NoSQL solutions are built to deal with the vast amount of information that the Internet is
communicating from one point to another in a keyvalue structure rather than a tabular
one, a direct contrast to SQL.
NoSQL is directly named for a variety of data formats that are structurally
different from SQLnotSQL data formats.
NoSQL alternatives are wellequipped to handle the explosion in the quantity and
variability of information the connected devices of the Internet of Things will bring us.
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NoSQL and Hadoop are the direct result of opensource communities building
something that will deal with the information closed solutions cannot, a testament to
open communities of builders getting together, and building out entire new industries.
It is a testament to the power of open source software.
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Open Source
The largest cost for a startup is the amount of minds and hands that can be
dedicated to work towards an idea.
The great thing about a software business is that it can be almost infinitely
scalable. The reason startups have such high growth potential are the economics of the
marginal cost of zero.
Every piece of software you ship should cost you next to nothing to deliver for a
user. Imagine if Facebook were a physical product that cost dozens of dollars to
produce and ship to each user (let’s say in this case an ebook that actually contained
photos of your face)it would not be very long before Facebook would have to incur a
whole lot of cost to deliver their product to millions of users.
The magic of software, where the costs of processing and sending information
are nearly zero on a peruser basis, has allowed Facebook to become the behemoth it
is now.
Other than hosting costs, Facebook incurs a large amount of its expenses on the
programmers, and thinkers that help shape it. In the three months ending June 2014,
research and development costs were equivalent to 62% of Facebook’s net income.
There is a very smart rule at the center of programming methodology.
This is the rule of “DRY” or Don’t Repeat Yourself.
Taken on an aggregate level, that means not replicating something that has been
built before. Open source ensures that software modules that have been designed
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before are accessible for reuse and for edits, with the implicit assumption that you will
pay it forward by making your code open once you are done with it, so that others can
build on the work you did.
Open source code ensures that you minimize the largest of your costs: labour. It
ensures your engineers can create faster, and ensures that they spend more time
creating unique solutions that haven’t been built yet, rather than being bogged down
trying to reinvent the wheel.
Instead of holding code into small proprietary silos, open source code hews to
the original principles set by TimBerners Lee and the creators of the Internet.
TimBerners Lee was overseeing what might have been the most lucrative
invention in the history of mankind.
He and his fellow architects set out to make sure that it was open and inclusive,
elevating the network to its fullest social potential. In doing so, they eschewed making
tons of money off of closed interconnected silos of communication they could have built
only for large private corporations.
Thier decision is why the Internet has evolved into a global system of
communications, with innovation slipping freely through most borders, rather than a
closed set of silos where information passed freely to a privileged few.
The open Internet has allowed communities of truly global scope to grow, and
prosper. It is what has unleashed the full potential of individual programmers to build
something great, and build a foundation that empowers others to build.
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When we mentioned the LAMP technology stack before, we talked about how all
of its components could be open source. The Apache hosting solution is built by the
Apache Software Foundation, one of the bastions of open source code.
Linux is famed for being the open source operating system.
SQL, a special coding language used to access databases built according to a
relational, tabular model (think Excel spreadsheets) is sponsored by the Oracle
Corporation, and has many proprietary strains and uses, but MySQL is a database that
has been made open source, and can be accessed for free with SQL without
purchasing a license from Oracle.
Finally, both Python, and PHP are backend programming languages that are
opensource, and hold large communities of programmers working together to create
software modules and programs that can make the language stronger, more efficient,
and ultimately, more useable.
Tim O’Reilly, the founder of O’Reilly Media, a publishing entity that organizes
conferences about technology, and publishes media that focuses on making the
knowledge of technology accessible to all, notes that all of us have used open source
products in our daytoday lives.
In his essay on the open source paradigm shift, he notes how the Internet was
built on open principles, and that despite our notion of it being a proprietary battle
between large giants such as Microsoft and Google, the reality is that the Internet is a
longsteeped recognition of the open source mentality.
All of us have used Google. Google uses Linux servers. We have all used open
source technologies.
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The HTML language that is the foundation of all webpages is a fascinating
example of open source technology we always use, yet tend to ignore.
The fact that we have a view source button on most modern web browsers is due
to the thinking of the original creators of the Internet, including Sir TimBerners Lee.
By allowing people to easily see what went into building websites, the HTML
language spread easily with different ways of using it popping up every day. Importantly,
people could easily access and learn from those examples, building a foundation for
their own experiments. To this day, you can see the HTML of various websites because
of the original insight that it is better to build and learn together.
Similarly, all of the components of the LAMP technology stack are united by the
principle that builders should work together to make building easier for all, and that they
should learn together to build together.
This has seeped into the realm of physical devices, with open source hardware
projects such as the Arduino board and Raspberry Pi making it possible for anybody to
build their own tablet, and become a maker.
You should embrace the DIY maker mentality as an opportunity: it is something
that will help you grow stronger ventures.
By building off of the foundation of others, and then in turn contributing back so
that others can build on top of your work, you will not only create a stronger web of
technology that will resonate beyond your companyyou will create a culture that is
more attractive to engineers, one based on simple collaboration contributing to a greater
vision.
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By attracting brighter minds, you will be able to save countless costs with a
smarter,and more efficient organization that can solve truly great problems.
By opening up your industry to the greater benefit of collaboration, you will be
able to be part of a movement that grows yearuponyear. There are safe proprietary
benefits to keeping things close to the vestbut so much of the foundation of the web
was built on the idea that when people come together, and are tapped to build
something togethergreat things emerge.
The results have spoken for themselves. From the communities that power most
modern programming languages, to the building of Wikipedia, the Internet is a testimony
to the power of the open source philosophy. As Elon Musk breaks his Tesla patents to
foster a more collaborative ecosystem for electric cars, one cannot help but think that
the opensource movement is justifiably gaining steam.
Focus the great minds you work with to solve new problems, rather than
problems solved before, and you will save time, and moneyand be able to build great
new solutions easier, quicker, and more effectively. Contribute back to the web that you
build on and you will see growth flourish both individually and collectively.
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Cloud computing
The open source mentality has continued to thrive because of a sea change in
how we access software, and computing resources.
Back in the days of old, you had to install software manually on hardware that
you owned. That often meant getting around to each computer terminal you owned and
installing Windows and different software packages. For many companies, this is still
the case.
The old mentality with software had a host of issues.
Every time you had to do a major update, you would have to undergo major
maintenance in order to shift from different versions of software as you had to manually
load them onto different computers.
It was also very difficult for software providers to know exactly what the needs of
their consumers were and what exactly they were doing with the software itself. The
closest proxy to this was a focus group that collected facts miles away from when they
actually mattered. In later versions, you might have volunteered some information to the
software providers over the Internetbut it was much too little, much too late.
Cloud computing changes the game. With login access to other machines,
computing resources and software that is elsewhere physicallybut connected to you
via the magic of the Internetcan help power your business.
You pay to access what you want. When there are major updates, these are
pushed through nearly seamlessly on other serversyou only have to log in.
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In 2008, the global cloud computing industry was estimated to be around $46
billion. Now, at the end of 2014, the industry is worth more than $150 billion, a growth of
326%. In five or ten years, many have predicted that the majority of all information
technology will be hosted on the cloud.
You can now store your data and run your servers on the cloud, asking Amazon
or other providers to ramp up your processing capacity as you need it, rather than
maintaining a local data center.
Jeremy Edberg, the first paid employee of reddit, one of the Alexa Top 100 sites
in terms of web traffic, mentions that reddit saved up to 29% in monthly costs by taking
this approach, and it saved them a bunch of hassle dealing with physical equipment. To
this day, reddit is mostly hosted on the cloud. Jeremy maintains that if you’re not a
hardware startup, you’re doing it wrong if you don’t start on the cloud.
It is this insight behind how some of the largest companies in the world have
coped with variable and explosive demands on their servers that is in turn, driving
extraordinary growth in the cloud.
This explosive growth has allowed for a host of speciality services to spring up,
unconstrained by the need to have massive sales and maintenance teams to go about
hawking their product, and helping out with onpremise installation.
While onesize fits all packages are still appealing for some companies, they are
no longer essential. In this new cloud environment, hyperspecialized services that
focus on one very specific element of a business can thriveand you can benefit from
the extra effort they have put in to tailor their solution perfectly to the problem at hand.
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We talked before about renting out software by subscription in the LTV/CAC
section, otherwise known as SaaS or software as a service: it is the notion of storing
software in the cloud that has made it possible to access software online, and rent it out
per month.
This has created the hypertargeted software for rent ecosystem. Unburdened by
physical installation, onestop shops for accounting software such as Freshbooks focus
expertly on your invoicing needs. Hipchat has perfected the business of chat. Box has
specialized beyond Dropbox in meeting enterprise data storage needsand solutions
like Kissmetrics boil down to a very specific element of business intelligence: who
exactly your incoming users are.
Each one of these cloud services can be accessed with a few mouse clicks, and
be available companywide without installing anything specific on pieces of hardware.
Each one knows exactly what you need because they have been tracking how other
users use their product. This is the power of cloud applications.
As more and more startups and giants rush into providing the best cloud
infrastructure, the cloud ecosystem will evolve into something entrepreneurs and
builders cannot ignore while building their own ventures.
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Crowdsourcing
Crowdsourcing was the basis behind ThoughtBasin, the spirit behind my idea.
We wanted to take crowdsourcing, an alternative approach to problemsolving, to
students, an alternative audience. The lessons we learned doing this confirm to me the
great possibilities afforded by getting great minds togetherbut also the risks one takes
on working on something like this.
Crowdsourcing is throwing a problem out to a selected crowd, or the general
public, and asking for open innovation: asking for people who are traditionally outside of
the confines of a problem to approach it with their solutions.
We were certainly doing that by approaching students.
One initiative I was proud about was getting together a bunch of students to
brainstorm about social good problems with leading nonforprofits. This took place in a
classroom. While we were never quite able to catch that spark online, the open
discussion of ideas still keeps my heart light.
We brought the Canadian branch of the nonforprofit Movember together with
topnotch students from McGill Universitythey brainstormed a bunch of great
ideasincluding novel advertising campaigns, and ways to make the Movember
experience funner and more meaningful for students.
The connections made, and the energy generated from that session are
something I will always remember.
Was it something that could be monetized and become a viable business?
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We couldn’t manage it for our platform, but a competitor of ours had found a
clever way. They targeted R&D departments of technology companies, a process which
got them hundreds of dollars in order to be a more efficient form of idea generation than
paying a department of engineers thousands of dollars to sit around and think.
The engineers could then focus on optimizing ideas provided by students rather
than going through the whole process of ideation then iteration. They proved there was
monetary value in the ideas students generated.
There has always been some money involved with crowdsourcing.
Innocentive, the grandfather of large crowdsourcing competitions, has hosted
challenges with prizes in the millions: but it has to be noted that their solvers tended to
be top technical experts in their fields, noted PHDs who collaborated together to
contribute topnotch polished technical results.
It is easier to frame value in that case.
Kaggle, similarly, crowdsources highly technical matters: the platform issues data
algorithm challenges to a highly technical audience of data scientists, challenging them
to come up with accurate models to predict patterns in the data set that are hidden from
them.
This distributed mode of innovation has worked wonders. Kaggle has solved
problems for NASA, and helped map out research on HIV/AIDS, and dark matter.
Crowdsourcing isn’t just rewarding ideas with money. It’s about applying an open
mentality to how and where solutions can appear.
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Udemy is an online platform that takes crowdsourcing, and applies it to
distributed education. Instead of the traditional expert model where only certain
designated individuals can teach what they know to others, Udemy is about creating a
platform where anybody can create a course on what they know, and distribute it to
willing learners.
I sat down, and talked briefly with one of the founders, Eren Bali.
His story sheds light onto why Udemy is built the way it is.
Eren was raised in a rural part of Turkey, a place where there was only one
teacher, and scarce access to education.
He started teaching himself mathematics through online resources, eventually
learning enough to win awards in the field.
Udemy was started with this spark in mind, the guiding idea that anybody could
learnand that anybody, under the right circumstances, could teach.
Him and his cofounders started Udemy in Turkey, but soon moved it to San
Francisco. Through the Founder Institute, an accelerator program that helps guide
startup founders through the business side of new ventures, Eren and his team were
able to build out of the largest platforms for education.
Udemy has raised $32 million as a result, and helped teach up to three million
students.
Udemy’s story is everything the open web is about: given enough diverse minds
coordinating together, magical solutions will be built. Once you make it easier for
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individuals to imagine, and create, the potential for the human spirit to achieve amazing
results will actualize.
Good ideas can come from anywhere.
You don’t even need to build material incentives in to build out great projects.
The open web has proven that this is possible. Github, a place where
programming projects are assembled and made public has proven that by allowing the
crowd to work together, building up such projects as the aforementioned Bootstrap, the
front end CSS framework that organizes how webpages look.
Originally given out by Twitter as opensource software after they had used it to
organize their web platform’s appearance, it is programmers around the web who
contribute to its active development and maintenance, a crowd that assembled
organically, and was never actively hired.
It doesn’t end there. Crowdsourcing has evolved from just contributing ideas and
solutions, to also providing funding for new ideas.
Kickstarter is a crowdfunding platforma way for supporters of an idea to
contribute to it monetarily, in return for perks from project creators that range from thank
you emails to discounts on the completed project.
It’s gotten a reputation for funding creative projects such as the Pebble smart
watch, a futuristic smart device that can beam text messages from your phone straight
to your wrist, where you can take a look even if your mobile’s stashed away.
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Kickstarter’s all or nothing modelif you don’t hit your funding goal, everybody’s
money is refundedand strong time constraints of 45 days or less for a campaign has
helped push projects to incredible, multimillion dollar heights.
Having a crowd of people connected by little other than interest in the project
has led to the successful funding of projects like the Pebble, which can use the $10.2
million it raised to manufacture its completed product en masse to a crowd of new
clients that never would have known about Pebble before.
This dynamic has propelled forward a movement of hardware ideas that can
innovate as quickly as software. The power of crowds contributing money to ideas they
believe in has been made possible by the open web making communication and the
spread of ideas effortlessnow the funding of them can in turn, be made much easier
through the power of the crowd.
Crowdfunding has also impacted the diffusion of social innovation. Indiegogo,
another large crowdfunding platform with flexible fundingeven if you don’t meet your
stated funding goal, you can get most of the money you raisedhas helped fund
projects such as Solar Roadways, an initiative to put solar panels over roadways to
create solar energy.
It has never been easier for a creator to come up with an idea, and execute on it
for the benefit of all.
As if to reinforce this trend, equity crowdfunding has recently come to the fore.
The traditional model of crowdfunding as donation, or crowdfunding for Kickstarter or
Indiegogo perks such as early access to the sweet new hardware project or movie has
been pushed even further with equity crowdfunding.
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The model has crowdfunders take shares in startups in return for their cash,
opening up an avenue of funding that had often been reserved for experts in the field:
the angels and VC firms previously discussed.
This has opened up room for the average startup enthusiast to invest in the
hottest startup opportunities, an opportunity once solely reserved to the most
wellheeled venture capitalists.
EquityNet is an example of a equity crowdfunding platform, one that has claimed
to connect about 45,000 investors and entrepreneurs with each other for about $243
million in funding.
It has never been easier to come up with an idea, and get others to believe in it
enough to support you.
This is the power of crowdsourcing and crowdfunding, of getting a diverse crowd
of perspectives together to craft something beautiful. It’s something at the heart of how
the Internet works: sharing beautiful ideas until they have real impact.
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Sharing Economy
Sharing is the default of the new digital economy.
From sharing our homes with AirBnB, a $10 billion business, to the ugly copyright
wars being fought over content sharing, this new rule has shaken society to the core,
and opened up a vista of opportunities.
Many startups have come of age in the new ethos of the sharing economy.
AirBnB required a cultural shift: the company rented out a stranger’s home
instead of a hotel to stay in, something your parents would be aghast at doing. Even
AirBnB’s own investors considered it to be a strange, niche activity: as Paul Graham of
Y Combinator put it, he considered AirBnB to be a bad ideabut funded it anyways
because he liked the founders.
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Source: https://c2.staticflickr.com/8/7385/14069508264_1e2286db2d_z.jpg
This cultural shift hasn’t just taken place in the realm of ideas. It has had
significant impact on the material economy.
Rachel Botsman, the author and founder of the Collaborative Lab, and an expert
who authored What’s Mine is Yours, a primer on the collaborative economy, points out
that the consumer peertopeer rental market is worth $26 billion just by itself.
Fortune Magazine has estimated that states would lose out on a minimum of
3.4% in annual tax revenue or about $23.4 billion in 2010 dollars because the sharing
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economy has progressed to the point where many don’t buy vehicles, but instead, rely
on a network of shared consumption.
From ideas like EatWith, a site that invites dinner hosts to open up their tables to
online guests, to ZipCar, a platform that lets users rent shared cars, the notion of
collaborative consumption, and of reducing waste on what had previously been unused
assets is taking over every industry and every city on Earth.
The sharing economy is not a trend or a fad. It is a new way of doing things that
is having significant impact on the old world. It is changing the rules.
The sharing economy changed the rules of the game by making people aware of
the fact that they had been spending lots of money for brand name servicesand it
personalized travel to the point where you knew your host, where living in somebody
else’s home was not only cheaper, but also richer in the sense of getting to know the
host city.
In doing so, it changed the culture and practices of people on the ground. People
got used to doing things their parents and grandparents would have never fathomed,
disrupting entire industries.
The sharing economy used the power of the Internet to make this all possible.
The almost nearzero cost of communication to coordinate people using what had been
unused spare capacity, and building value out of the empty room that was never used.
This is the fundamental tenet of the sharing economyfreeing up what had once
been wasted, unused resources. A spare room in the old economy used to be one of
the most illiquid assets you could hold: other than renting it out per month, there was
very little you could do to derive any value from it.
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Now you’re only a few button clicks away from creating constant economic value
out of what had been an unusable, and unsalable resource.
“What’s mine is yours.” Rachel Botsman
As sharing becomes the default of the digital economy, entrepreneurs that
embrace this new reality will thrive. They will be able to design better products, and
design within a rapidly evolving ecosystem that redefines how we interact with one
another, and how we collaborate to buildtogether.
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Design Thinking
There’s an oftrepeated mantra that “design thinking will save the world.”
How, you must wonder. What are pretty graphics going to do for the poor?
Design thinking isn’t just about making things look good. It’s about the whole
spectrum of user experience. It’s about making it as easy as possible for people to use
your solution, from the aesthetics to the flow.
The fabled UI/UX buzzword you may have seen floating around is an integral
part of design thinking. UI stands for the user interface, or how you allow the user to
interact with your technology. UX deals with user experience, or exactly what the user is
going through as they reach whatever they desire through the use of your technology.
When you go through the latest mobile application, you’ll find that everything has
been designed to make it as easy as possible for you to reach what you want.
Uber, the aforementioned taxihailing application, has only one button for you to
hail a cab. The founders’ explicitly thought of how cool it would be to have a button that
could hail you a car at anytime. This is one of the key rationales behind founding Uber.
Tinder, an online dating application, has a swipe like motion where if you swipe
right on potential dates, you have the potential of connecting with that person. If you
swipe left, you don’t.
You should know how many times Tinder for X gets pitched in the startup world.
I’ve heard of Tinder for fashion, Tinder for real estate, even Tinder for jobs.
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It’s because the swiping motion of Tinder has defined the easiest way for users
to find information, or to signal their intent. With the move from desktop to mobile,
design has helped users find each other as simply as possible.
The user interface of Tinder is very simple: only a couple of buttons define
actions, and then afterwards, it’s all about an intuitive swiping motion. When you first
use the application, numerous popups help guide you through the process so that your
user experience feels natural.
Is that unconnected to the larger problems of the developing world or the urban
poor?
Perhaps Tinder the application is, but the approach they embody can be used to
make it easier for people to achieve anything, including incredible actions for social
good.
Consider a social enterprise with a different goal, with the same design
philosophy.
Montrealbased startup I Can Go Without created an application that encourages
donations through all of the design elements that startups use to convince you to adapt
their new solution. By embedding sharp design, intuitive interfaces, and social networks
into the act of donating, ICGW makes donating fun, and viralultimately creating a
cycle where giving is embedded into daily life, and where more donations are made.
It has led to big results, with the application partnering with Simple Plan, and
Kardinal Marshall to deliver meals with the ONEXONE Foundation to Inuit children in
the north who are often subject to malnutrition because of a lack of an established food
infrastructure that can deliver fresh food at a fair price.
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The mobile application they have developed is driving a change in behavior.
Donations used to be a static affair, something where you would donate a large
amount of money once in a while. Perhaps you’d donate on a recurring basis to a
charity, but you’d only do it once in a while.
The whole notion of making microdonations were confined to donating a bit of
change if you had some, to somebody who was around if they were. Maybe there was a
bake sale for charity: if you were in the area you might give.
In a mobile world where data can pass back and forth, this way of donation has
quickly grown to be antiquated.
I Can Go Without is helping you to trace a personal story of giving. It’s a new
application for managing charity that has embraced the core tenets of design thinking.
By skipping out on a daily vice, such as an evening beer, and having that money
flow naturally to the charity of your choice, I Can Go Without helps you build a personal
dashboard where you can see how much money you have raised for the charity of your
choice by going without something for a few days.
Donating is as simple as inputting a credit card, and pushing a few buttons. You
can not only trace your own progress, but you can also draw inspiration from the paths
of otherscurated stories that can be found by a nifty discover function that sheds light
into how others are donating on the platform.
I Can Go Without is an intuitive platform that creates a new way of giving.
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It is the new design thinking of startups improving upon traditional systems. By
making it easier and funner to donate, platforms like I Can Go Without make creating
and sharing social impact intuitive.
A clean and simple user interface, and a pleasant user experience can help solve
a lot of big problems.
Design thinking can make great things happen, if it is directed the right way. By
making it easier for all of us to achieve our goals, it can help encourage and coordinate
social impact.
Design thinking can save the world.
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Cryptocurrency
Migrants like Ahmed Ali are trying to wire money from America back to their
relatives in Somalia, a process known as making remittance payments. Ahmed says
that the money will make the difference between his family eating or starving.
Remittance payments are a lifeline. In 2014, the World Bank calculated that $436
billion will be sent from family members in developed countries to developing nations.
Between 1960, and 2003, total foreign aid to Africa was around $600 billion, yet
remittances sent from the African diaspora were double that. Many of the financial
institutions that move money back and forth charge exorbitant fees to keep that lifeline
opensometimes ten percent or more.
Marc Andreessen notes that switching these systems to bitcoin could save
billions of dollars in value for the world’s poorest by reducing transfer fees to nearzero.
Bitcoin could also be tracked more easily than cash, resolving some laundering fears.
Xoom, a digital remittances platform, has demonstrated the potential of moving
away from convention by capping transfer fees as low as $2.99. They convinced
senders to make one part of the remittances journey digital: instead of going from cash
to cash, Xoom takes money directly from bank accounts, and credit cards.
Yet among all of the countries on the transfer list, there are none from Africa. The
issue has always been that you can have a great sending infrastructure: but what about
the people receiving the money, people who might not have access to modern financial
institutions?
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Vodafone’s MPESA has stepped into the breach in Kenya, allowing for people to
send and receive money via their mobile phones, and for people to pick up money at
small MPESA affiliated retail branches.
Kipochi is a bitcoin mobile wallet that has built onto this system, and allowed for
the transfer of bitcoin through MPESA. As MPESA looks to expand into India, and
other nations this could represent the cutting edge of the future, the awaited solution for
Ahmed and his family.
Yet questions remain. Bitcoin, and MPESA could not be more different in how
they are organized. MPESA is locked up proprietarily by Vodafone. Bitcoin is explicitly
open, and encourages others to build on top of it.
Part of MPESA’s success has been due to the overwhelming clout of Vodafone.
Could that ever be matched by an open network of technologists?
Does Vodafone have enough clout to bring the MPESA model to every corner of
the globe?
Larger questions are weaved into the narrative of incumbent and newcomer.
Bitcoin is not without failure, but the financial system has woven through it time and
again.
Can the technology of tomorrow solve broken systems today? It’s a fundamental
question that bleeds at the edge of technology and society, and pits the slowmoving
legislative process against quickpaced hackers on the edge of the possible.
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There’s hope to be taken from the past. The long history of the Internet was filled
with geeks tinkering with things, breaking them, then seeing great new technologies
they never fathomed coming out of it. The era of massive startup failures like Pets.com
would give rise to the massive lean successes of today.
Open technologies like Linux, Apache, and Hadoop have changed the world for
the better.
If the elusive anonymous Satoshi, the creator of Bitcoin, would speak, he might
voice those hopes. Perhaps the financial system we live in is the not the system we
need, it is the one we deserve...and perhaps we could build something better if we set
out to do so, together.
An entrepreneur could pick out a simple solution for how people could withdraw
bitcoin into local currency without the need for corporate muscle. Others could found the
secure bitcoin exchange of the future, and relieve laundering fears. Solutions could
spring forward from anywhere.
Cryptocurrency is fundamentally different from the conventional financial system
because it allows us to ask these questions.
The conventional financial system is one of intermediaries, where people who
are experts in financial information help move the flow of value back and forth. Banks
are cogs in the middle of the system: they take the information from both parties of a
deal, and match them with the right fit. A pension fund looking to invest in lowrisk loans
will be matched with a pool of individuals with good credit scores.
The system that each bank uses to process the information they have is jealously
guarded by each bank. It is some of the most closed technology on the planet.
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Bitcoin was built so that the transaction of value would be based on open
technology, and peertopeer interaction. People are able to peer behind the hood with
bitcoin, and contribute different technological fixes to different issues.
The chief innovation of bitcoin has been that it allows two individuals to transact
value amongst each other without having a bank in between to establish trust.
Using advances in cryptography, and a chain of publicly available records, bitcoin
employs mathematical formulae that require a large amount of computing resources to
solveonce solved, the proof is available to all that a particular computing unit solved
the bitcoin problem, and can thus be assigned one bitcoin.
When people transfer bitcoin amongst each other, they are transferring value that
comes at a cost: the electricity and computing resources needed to “mine” virtual
bitcoins.
They are able to transact freely even if they don’t know the other person behind
the bitcoin: they know the user on the end is part of a public registry that builds on itself
with each bitcoin mined, the long chain of valid Bitcoin transactions guards against
fraud, and allows one to track where bitcoin comes from.
Trust is the currency of the Internet. Cryptocurrencies are the technology that
enable it to be created seamlessly.
Bitcoin has given birth to different communities that embrace the cryptocurrency
concept, even if they don’t directly embrace bitcoin itself. Entire waves of Internet
memes have become tradable commodities overnight, including the famous Dogecoin.
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Here, one of the defining fights of cryptocurrency remains. Many say that bitcoin
and their ilk cannot be construed as currencies. The IRS considers bitcoin to be
property rather than foreign currency, subjecting bitcoin to capital gains taxes. This is
largely due to the volatility of bitcoinoftentimes 3 times as much as a typical currency.
These cryptocurrencies are best seen then, perhaps, in the lens of communities.
An organic gathering of people who believe enough in something to see it become a
store of value for others.
One of the most interesting use cases I saw was an idea known as potcoin. I
wrote about it on TechCrunch, right when interest was peaking around cryptocurrencies.
Potcoin was organized around the legal marijuana industry in America.
It was used by a community of marijuana merchants and people fighting to
maintain a financial system for marijuana shops who were selling legally, yet being
denied access to the conventional banking system due to old stigmas.
Without banking, marijuana dispensaries were being subject to violent crime, as
thieves knew shop owners had to stash high amounts of cash. A movement to legalize
marijuana to reduce violence was ironically causing more.
It was the creators and community behind potcoin that stepped into the breach,
helping stores convert their cash into digital assets.
It was very much a representation of how the open web, and peertopeer
communities could solve old problems with new approaches.
In a world where software is connecting communities of thinkers, solutions will
spring from anywhere.
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Conclusion
Software is eating the world.
The data we are able to collect and manipulate is multiplying exponentially.
Open communities are collaborating to build out magical ideas together.
The world is changing before our eyes.
The terms and ideas we went through together are but a reflection of this
significant change, small tokens of the change that is coming every day, raw
transformative power confined in a few short words.
When I first set out to write this book, I wanted to share with you what I saw
happening around me. I truly believe this change will define the early parts of the 21st
century. I’ve framed this as a guide for entrepreneurs, and people seeking to build new
ventures, but really, I think the terms discussed are something everybody in the world
will have to be familiar with to have a full voice at the table.
To be a part of this new digital age, everybody will have to join this discussion.
So feel free to share the knowledge you’ve gained here, and let people know
about these terms. This is meant to be just an introductionI’d hope that you’d explore
as much as you can outside of this book.
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If you want to learn with me again, check out code(love). I’ll be posting resources
to learn code and entrepreneurship, and defining the future piecebypiece.
To end off: true learning never stops. I hope you never lose the curiosity that
brought you here in the first place.
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