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nalytics and Data Cultur Lessons from a fast growing tech SaaS startup Putting data at the heart of your business to make fast decision based on data
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Think tank - Data Culture for a Better Business

Sep 13, 2014

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Data & Analytics

Growth Hacker and Data Punk Daniel Cave talks about how how to put Data at the heart of your business.

What you should track, what you should share and who you should share it with to drive the best business decisions possible.
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Page 1: Think tank - Data Culture for a Better Business

Analytics and Data CultureLessons from a fast growing tech SaaS startup

Putting data at the heart of your business to make fast decision based on data

Page 2: Think tank - Data Culture for a Better Business

Quick ‘about me’

SEO / Technical Import.io • Technical Marketing/Growth Guy• In Product Analysis and Stats to drive insight• Contractor Intuit, Wordtracker, linkedex User.

Page 3: Think tank - Data Culture for a Better Business

What to TrackWhat to ShareHow to share

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DATA Culture

Page 5: Think tank - Data Culture for a Better Business

The 3 Biggest most painful Lesson(s)

First of All

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“If you are not collecting data now, its impossible to collect it later!”

So collect all data even if you are not using it right now. Try to plan ahead, and

imagine what you will need to analyse in the future.

Lesson #1

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With Any Dataset, Perspective and Context are paramount. Who has the

domain knowledge for each data point?

Lesson #2

Page 8: Think tank - Data Culture for a Better Business

“Not Putting Data culture into the heart of your business and not including

everyone makes for worse decisions”

Lesson #3

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My PhilosophyGather / Store / Display - Bits of Lean

• Learn to Collect Everything• Learn how to Share the Right things, Right

People• Make better choices based on data viewed

through your domain experts (your team).

Page 10: Think tank - Data Culture for a Better Business

What to TrackWhat to ShareHow to share

Page 11: Think tank - Data Culture for a Better Business

Real Success… and whats influencing it.

Better info to grow a businessUseful info to drive team

What to track?

Page 12: Think tank - Data Culture for a Better Business

Culture: What we TrackEverything, the whole journey for every user.

• Acquisition• Signups, Browser Download, Video Played,

Contacts, Forms Submitted, Content Type Consumed, Form Fields Clicked, Campaigns sending traffic.

• Activation• Successful and failed uses of every feature,

support requests, enterprise data requests.• Retention

• Returning Visits, Regularity of visits• Active and Core Users

• Which customers are REALLY engaged

Page 13: Think tank - Data Culture for a Better Business

How we TrackOur tracking infrastructure

+

Page 14: Think tank - Data Culture for a Better Business

What to TrackWhat to ShareHow to share

Page 15: Think tank - Data Culture for a Better Business

Culture: What to shareThings people can understand and effect

• Leading Metrics• Browser downloads / Newsletter Signups• Signups• Conversion rate / Purchase• Minutes read• Successful / Failed Feature used

• Lagging metrics• Active users• Returning customers• profit (after returns etc)• Growth Rate

Page 16: Think tank - Data Culture for a Better Business

Type of MetricsRe-visiting Leading vs Lagging

Better info to grow a businessUseful info to drive team

Page 17: Think tank - Data Culture for a Better Business

What to TrackWhat to ShareHow to share

Page 18: Think tank - Data Culture for a Better Business

Share the data with your whole team/business

Data Lunch

Page 19: Think tank - Data Culture for a Better Business

“But Data is for nerds and nobody cares…”

Page 20: Think tank - Data Culture for a Better Business

“Don’t fear that you will be alone…”

Page 21: Think tank - Data Culture for a Better Business

“You will be famous!”

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“Everyone wants to have the voice and opinion heard…

Everyone of your team has a unique view on what the data could mean…

Everyone can see what actions could influence it.”

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How we use/share the Data

Measure Real Success!

• Develop & Analyse Core User Profile Using Data• where a user came from (acquisition trail) • when they visited• what device they visited on• how/when/why did they signup• which features they used• what task they tried to complete• how many times it took them to complete the task • how many did not complete • how many times have they visited in the last

week/month* Cost per Goal Completion

UI / UX + Analytics

Why?Marketing+Web

Analytics

Why?

User Success + Analytics

Why?

Page 26: Think tank - Data Culture for a Better Business

How to use that DataSegmenting and analysing as a team.

• Marketing: Knowing your Core User CPA by channel gives you solid ground to advertise from.

• Product managers and Developers: Test new features for effect on retention, adoption and profit.

• Social/Engagement: Engaging People who are already bought into your business (aka core users) reaps big dividends.

• Support: Squash common issues as a priority and support your theory with data.

Page 27: Think tank - Data Culture for a Better Business

ExamplesSimple Cases

• Segment and Email Core Users Using SQL + Woopra, then invite them to your ambassador program.• You Can Get

• Free content from them• Free Social Media exposure• Free Links from there Network

• They Get• Freebies• Insider emails• Advanced webinar tickets

Page 28: Think tank - Data Culture for a Better Business

ExamplesSimple Cases• When you implement a New Feature

• Have visibility on its real world effects• Does it increase the percentage of Signed

up to ‘activated’ users (aka real growth).• Does it effect the CPA of core users and/or

retention rates.• Have you reduced or moved the “time to

Wow”

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ExamplesSimple Cases

• When you are buying visitors/media• Have visibility on real deep ROI

• Is it sending visitors that stick?• Exactly which visitors did it send and what

did they do different to others.• What is the CUCPA*• Improve your persona to product fit, which

traffic sources drove use of (or purchase of) which features.

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Co-Hort AnalysisSee customer behaviour in reaction to your changes

orMarket trends

38%

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The advanced stuff…for another day

• If you have the right data you can start creating a predictive analytics model to help plan spending and buying.

http://en.wikipedia.org/wiki/Regression_analysis

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Thanks

https://import.io/

Daniel Cave

@importio

@Dancave