Copyright © 2014 by Juice Inc. Turning data into dollars Juice Analytics September 2014
Nov 29, 2014
Copyright © 2014 by Juice Inc.
Turning data into dollars Juice Analytics September 2014
Copyright © 2014 by Juice Inc.
Today’s objectives
Explain the opportunity to monetize your data
Identify your opportunities to create data products
Understand the elements involved with bringing data products to market
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5 Steps to Data Monetization
1. Data as a product
2. Data meets audience
3. Designing a data product
5. Launching a data product
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Schedule
Introduction and examples Notes Discuss in small group
Share with allTopic 1
15 min 5 min 5 min 5 minTopic 2
Topic 3
Topic 4
Topic 5
20 min (Update on Apple announcements)Break
20 min (optional)Examples
10mIntro
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TOPIC 1
DATA as a PRODUCT
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DATA is the new OIL
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Raw materials Finished product
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Competing on Analytics (Analytics 1.0)
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Analytics 3.0: Turning data inside out
Every organization—not just online firms—can create data and analytics-based products and services that change the game
Not just supplying data, but insights and guides to decision-making
Use “data exhaust” to help customers use your products and services more effectively
Source: International Institute for Analytics
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Data products vs. traditional analytics
Research report
Internal External
Static summary
Interactive
Target audience...
Delivered as...
Reporting
Dashboards
Data productsInteractive, web-based solutions sold independently or delivered as part of another solution.
Web basedFeature-rich
Solve specific problems
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The Data Monetization Opportunity
(1) The big-data revolution in US health care: Accelerating value and innovation, April 2013, McKinsey & Company
In healthcare alone, there is an estimated $300B to $450B in annual cost savings that can be
achieved through data applications (1)
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Types of data products
New data product
Enhance an existing data product
Revenue generating
Value add to a product/service
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LinkedIn: User engagement
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US News: New revenue stream
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Exercise 1: Data as a product
Brainstorming data product concepts for you or your organization. For each one, describe the problem it solves.
Data product concept What problem does it solve?
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TOPIC 2DATA meets AUDIENCE
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Data meets audience
Data product Target audience
http://businessmodelalchemist.com/blog/2012/08/achieve-product-market-fit-with-our-brand-new-value-proposition-designer.html
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What data could help them in their role?
How can your data best serve this audience?
Who is your target audience?1
2
3
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Different data for different folks
Chief Marketing OfficerMarketing Analysts
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What’s this calculated metric?
Enhancing your data
3rd party data sources
Predictive modeling
Calculated metrics
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Benchmarks, comparison, and context
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A data readiness checklist
Do you have rights to the data?
Can the data be accessed in an automated fashion?
Is there personal data that should be obscured?
Can the data be presented at a level of summarization/granularity that the audience will find most useful?
Does the data need to be cleaned or transformed to make it useful?
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Example: Predikto
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Exercise 2: Data meets audience
Fill out the table for each of your favorite 2-3 data product concepts
Data product concept Who is it for? How can the
data help?Is the data
ready?How to add value
to the data?
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TOPIC 3
DESIGNING your data product
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What goes into the design of a product?
Self-serve, not self-solve
purposeful design leading to action fit users workflow
guidance and storytelling
form follows function
right-sized
socialize-able
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Designing for action
“I’ll get right on that”“good to know”“neat”
Interesting < Useful < Actionable
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Guidance and storytelling
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Volume
How will they use it?
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Form follows function
timeliness
aesthetic
mobility
connectivity
data detail
data density
interactivity
collaboration
functionform paper Excel online app e-mail large
screen
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Socialization: reaching your audience’s audience
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Example: US Chamber of Commerce
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Exercise 3: Designing your data product
For your one or two of your favorite product concepts, answer the following questions:
Concept 1 Concept 2
In what form would the data product be delivered?
How does the product fit into in the user’s workflow?
What specific actions can it drive?
How can you help users share the data/insights?
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TOPIC 4
Go to market challenges
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Selling
Agreeing
Delivering
Supporting
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Volume
Selling
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Selling
How will it be sold/distributed?
What’s needed to help sell it?
How will you explain it?
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Volume
Agreeing
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Agreeing
Existing customer agreement or new one?
How will billing occur?
Who needs to be involved?
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Volume
Delivering
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Delivering
How will user receive it?
Who is delivering?
How do we make delivery successful?
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Volume
Supporting
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Supporting
!
Who will answer questions, comments, etc.?
How will the product be maintained?
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Example: Hall & Partners
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Exercise 4: Go to market challenges
For your data product concept, list your biggest or most likely obstacle or challenge. For each risk, consider potential approaches to mitigate these risks.
Challenge Mitigation strategy
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TOPIC 5
Launching a data product
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Volume
Pick One
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“Data isn’t like kids you don’t have to pretend to love them equally.”
Amanda Cox, NY Times
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Volume
Think Lean
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Lean Canvas
Volume
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Volume
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=Have conversations
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Example: The Essential Economy
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Exercise 5: Launching a data product
Provide a brief description of the data product that is most promising and describe the key features that represent the minimum viable product.
Data product description
Minimum viable product features
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5 Steps to Data Monetization
1. Data as a product
2. Data meets audience
3. Designing a data product
4. Go to market challenges
5. Launching a data product
Copyright © 2014 by Juice Inc.
About Juice Analytics
Our B2B clients (from start-ups to Fortune 500) have launched profitable products with our design and technical guidance
Design and launch data products
Fruition: Data Product Platform
Data visualization components designed for non-technical end-users
Features for sharing and collaborating on data insights and analysis
A decade of guiding businesses through the process of designing, creating and launching new data products
Recognized thought leaders
Available early November
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Data Product ExamplesDataSift - licenses data from Twitter to aggregate, process and deliver social data to enterprises about their brands. ADP - provides a monthly snapshot of U.S. nonfarm private sector employment based on actual transactional payroll data Payscale.com - links individuals and businesses to the largest salary profile database in the world. Glassdoor.com - Influence job seekers at the moment they are making the decision whether or not to work for you Indeed.com - Reports for economic forecasting or stock trading models. Compete.com - compare publishers to buy the most efficient traffic Alexa.com - compare publishers to buy the most efficient traffic Quancast.com - compare publishers to buy the most efficient traffic Zillow.com - Home values (real and estimated) for all houses in US ProjectHoneyPot.org - Black lists of IP addresses or email addresses used in fraud, Botnet activity or forum spam. FICO - Selling scores, such as click scores or any other scores. FICO was one of the first companies to do so. Skift - provide you with the latest intelligence on travel trends. SuperData Research - Data-driven market intelligence on online, mobile and digital games Factual - Data on over 600,000 consumer packaged goods in a UPC centric database with ingredients and nutrition information
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Additional reading1. Data Jujitsu by DJ Patil.
2. The evolution of data products by Mike Loukides.
3. John Foreman blog - MailChimp data scientist
4. Juice Analytics.com Product Manager’s Checklist