Lean Analytics · Use Data to Build a Better Startup Faster by Croll, Alistair -- Read -- Imperial Library of Trantor

Index

Lean Analytics: Use Data to Build a Better Startup Faster Praise for Lean Analytics Dedication Foreword Preface

Who This Book Is For How This Book Works The Building Blocks

Customer Development Lean Startup

We’d Like to Hear from You Safari® Books Online Thanks and Acknowledgments

I. Stop Lying to Yourself

1. We’re All Liars

The Lean Startup Movement Poking a Hole in Your Reality Distortion Field Airbnb Photography—Growth Within Growth

2. How to Keep Score

What Makes a Good Metric? Qualitative Versus Quantitative Metrics Vanity Versus Real Metrics Eight Vanity Metrics to Watch Out For Exploratory Versus Reporting Metrics Circle of Moms Explores Its Way to Success Leading Versus Lagging Metrics Correlated Versus Causal Metrics Moving Targets HighScore House Defines an “Active User” Segments, Cohorts, A/B Testing, and Multivariate Analysis

Segmentation Cohort Analysis A/B and Multivariate Testing

The Lean Analytics Cycle Evaluating the Metrics You Track

3. Deciding What to Do with Your Life

The Lean Canvas What Should You Work On? Create a Lean Canvas

4. Data-Driven Versus Data-Informed

How to Think Like a Data Scientist Lean Startup and Big Vision

II. Finding the Right Metric for Right Now

5. Analytics Frameworks

Dave McClure’s Pirate Metrics Eric Ries’s Engines of Growth

Sticky Engine Virality Engine Paid Engine

Ash Maurya’s Lean Canvas Sean Ellis’s Startup Growth Pyramid The Long Funnel The Lean Analytics Stages and Gates

6. The Discipline of One Metric That Matters

Moz Tracks Fewer KPIs to Increase Focus Four Reasons to Use the One Metric That Matters Solare Focuses on a Few Key Metrics Drawing Lines in the Sand The Squeeze Toy Define Your OMTM

7. What Business Are You In?

About Those People The Business Model Flipbook

Lots to Choose From

Six Business Models Pick Your Business Model

8. Model One: E-commerce

What Mode of E-commerce Are You? A Practical Example

Conversion Rate Purchases Per Year Shopping Cart Size Abandonment Cost of Customer Acquisition Revenue Per Customer

WineExpress Increases Revenue by 41% Per Visitor

Keywords and Search Terms Recommendation Acceptance Rate Virality Mailing List Click-Through Rates

Offline and Online Combinations

Shipping Time Stock Availability

Visualizing the E-commerce Business Wrinkles: Traditional E-commerce Versus Subscription E-commerce Key Takeaways

9. Model Two: Software as a Service (SaaS)

Backupify’s Customer Lifecycle Learning Measuring Engagement Churn

Churn Complications

Visualizing the SaaS Business ClearFit Abandons Monthly Subscriptions for 10x Growth Wrinkles: Freemium, Tiers, and Other Pricing Models Key Takeaways

10. Model Three: Free Mobile App

Installation Volume Average Revenue Per User Percentage of Users Who Pay Churn Visualizing the Mobile App Business Wrinkles: In-App Monetization Versus Advertising Key Takeaways

11. Model Four: Media Site

Audience and Churn Inventory Performance and the Sessions-to-Clicks Ratio Ad Rates Content/Advertising Trade-off Visualizing the Media Business Wrinkles: Hidden Affiliates, Background Noise, Ad Blockers, and Paywalls Key Takeaways

12. Model Five: User-Generated Content

Visitor Engagement Content Creation and Interaction Engagement Funnel Changes Value of Created Content Content Sharing and Virality Notification Effectiveness Visualizing a UCG Business Wrinkles: Passive Content Creation Key Takeaways

13. Model Six: Two-Sided Marketplaces

What DuProprio Watches Rate at Which You’re Adding Buyers and Sellers Rate of Inventory Growth Buyer Searches Conversion Rates and Segmentation Buyer and Seller Ratings

Percent of Flagged Listings

Visualizing a Two-Sided Marketplace Wrinkles: Chicken and Egg, Fraud, Keeping the Transaction, and Auctions Key Takeaways

14. What Stage Are You At?

Pick the Stage That You’re At

15. Stage One: Empathy

Metrics for the Empathy Stage This Is the Best Idea I’ve Ever Had! (or, How to Discover Problems Worth Solving) Finding a Problem to Fix (or, How to Validate a Problem) Signs You’ve Found a Problem Worth Tackling Running Lean and How to Conduct a Good Interview How to Avoid Leading the Witness Convergent and Divergent Problem Interviews How Do I Know If the Problem Is Really Painful Enough?

Calculating the Scores

Cloud9 IDE Interviews Existing Customers How Are People Solving the Problem Now? Are There Enough People Who Care About This Problem? (or, Understanding the Market) What Will It Take to Make Them Aware of the Problem? A “Day in the Life” of Your Customer Finding People to Talk To Getting Answers at Scale LikeBright “Mechanical Turks” Its Way into TechStars Creating an Answers-at-Scale Campaign Build It Before You Build It (or, How to Validate the Solution) Localmind Hacks Twitter Before You Launch the MVP Deciding What Goes into the MVP Measuring the MVP

Don’t Ignore Qualitative Analytics Be Prepared to Kill Features

Static Pixels Eliminates a Step in Its Order Process A Summary of the Empathy Stage Should You Move to the Next Stage?

16. Stage Two: Stickiness

MVP Stickiness Iterating the MVP qidiq Changes How It Adds Users Premature Virality The Goal Is Retention Seven Questions to Ask Yourself Before Building a Feature How Rally Builds New Features with a Lean Approach How to Handle User Feedback The Minimum Viable Vision The Problem-Solution Canvas VNN Uses the Problem-Solution Canvas to Solve Business Problems A Summary of the Stickiness Stage Exercise #1: Should You Move to the Next Stage? Exercise #2: Have You Identified Your Biggest Problems?

17. Stage Three: Virality

The Three Ways Things Spread

Inherent Virality Artificial Virality Word-of-Mouth Virality

Metrics for the Viral Phase Beyond the Viral Coefficient Timehop Experiments with Content Sharing to Achieve Virality Instrumenting the Viral Pattern Growth Hacking

Attacking the Leading Indicator What Makes a Good Leading Indicator? Correlation Predicts Tomorrow Causality Hacks the Future

A Summary of the Virality Stage Should You Move On to the Revenue Stage?

18. Stage Four: Revenue

Metrics for the Revenue Stage The Penny Machine

Penny Machines and Magic Numbers

Finding Your Revenue Groove

Where Does the Money Come From?

Customer Lifetime Value > Customer Acquisition Cost Parse.ly and the Pivot to Revenue Market/Product Fit

Review Your Old Assumptions Begin a Process of Elimination Deep Dive Find Similarities

The Breakeven Lines in the Sand

Breakeven on Variable Costs Time to Customer Breakeven EBITDA Breakeven Hibernation Breakeven

Revenue Stage Summary

19. Stage Five: Scale

The Hole in the Middle Metrics for the Scale Stage Is My Business Model Right? Buffer Goes from Stickiness to Scale (Through Revenue) The Three-Threes Model Finding Discipline as You Scale A Summary of the Scale Stage

20. Model + Stage Drives the Metric You Track

III. Lines in the Sand

21. Am I Good Enough?

WP Engine Discovers the 2% Cancellation Rate Average Isn’t Good Enough What Is Good Enough? Growth Rate

Is Growth at All Costs a Good Thing? Bottom Line

Number of Engaged Visitors

Bottom Line

Pricing Metrics Socialight Discovers the Underlying Metrics of Pricing

Bottom Line

Cost of Customer Acquisition

Bottom Line

Virality

Bottom Line

Mailing List Effectiveness

Bottom Line

Uptime and Reliability

Bottom Line

Site Engagement

Bottom Line

Web Performance

Bottom Line

Make Your Own Lines in the Sand

22. E-commerce: Lines in the Sand

Conversion Rate

Bottom Line

Shopping Cart Abandonment

Bottom Line

Search Effectiveness

Bottom Line

23. SaaS: Lines in the Sand

Paid Enrollment

Bottom Line

Freemium Versus Paid Upselling and Growing Revenue

Bottom Line

Churn OfficeDrop’s Key Metric: Paid Churn

Bottom Line

24. Free Mobile App: Lines in the Sand

Mobile Downloads

Bottom Line

Mobile Download Size

Bottom Line

Mobile Customer Acquisition Cost

Bottom Line

Sincerely Learns the Challenges of Mobile Customer Acquisition Application Launch Rate

Bottom Line

Percent Active Mobile Users/Players

Bottom Line

Percentage of Mobile Users Who Pay

Bottom Line

Average Revenue Per Daily Active User

Bottom Line

Monthly Average Revenue Per Mobile User

Bottom Line

Average Revenue Per Paying User

Bottom Line

Mobile App Ratings Click-Through

Bottom Line

Mobile Customer Lifetime Value

25. Media Site: Lines in the Sand

Click-Through Rates

Bottom Line

Sessions-to-Clicks Ratio

Bottom Line

Referrers

Bottom Line

Engaged Time

Bottom Line

What Onsite Engagement Can Tell You About Goals and Behaviors Sharing with Others

Bottom Line

JFL Gags Cracks Up YouTube

26. User-Generated Content: Lines in the Sand

Content Upload Success

Bottom Line

Time on Site Per Day

Bottom Line

Reddit Part 1—From Links to a Community Engagement Funnel Changes

Bottom Line

Reddit Part 2—There’s Gold in Those Users Spam and Bad Content

Bottom Line

27. Two-Sided Marketplaces: Lines in the Sand

Transaction Size

Bottom Line

What Etsy Watches Top 10 Lists

Bottom Line

28. What to Do When You Don’t Have a Baseline

IV. Putting Lean Analytics to Work

29. Selling into Enterprise Markets

Why Are Enterprise Customers Different?

Big Ticket, High Touch Formality

Legacy Products

Incumbents Slower Cycle Time Rationality (and Lack of Imagination)

The Enterprise Startup Lifecycle

Inspiration Empathy: Consulting and Segmentation

How Coradiant Found a Market

Stickiness: Standardization and Integration Virality: Word of Mouth, Referrals, and References Revenue: Direct Sales and Support Scale: Channel Sales, Efficiencies, and Ecosystems

So What Metrics Matter?

Ease of Customer Engagement and Feedback Pipeline for Initial Releases, Betas, and Proof-of-Concept Trials Stickiness and Usability Integration Costs User Engagement Disentanglement Support Costs User Groups and Feedback Pitch Success Barriers to Exit

The Bottom Line: Startups Are Startups

30. Lean from Within: Intrapreneurs

Span of Control and the Railroads Skunk Works for Intrapreneurs Changing—or Innovating to Resist Change? Stars, Dogs, Cows, and Question Marks Swiffer Gives Up on Chemistry Doritos Chooses a Flavor Working with an Executive Sponsor EMI Embraces Data to Understand Its Customers The Stages of Intrapreneur Lean Analytics

Beforehand: Get Buy-in Empathy: Find Problems, Don’t Test Demand Skip the Business Case, Do the Analytics Stickiness: Know Your Real Minimum Viral from the Start Revenue Within the Ecosystem Scale and the Handoff

31. Conclusion: Beyond Startups

How to Instill a Culture of Data in Your Company

Start Small, Pick One Thing, and Show Value Make Sure Goals Are Clearly Understood Get Executive Buy-in Make Things Simple to Digest Ensure Transparency Don’t Eliminate Your Gut Ask Good Questions

A. References and Further Reading B. About the Authors C. The Lean Series Index About the Authors Copyright

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