This document summarizes a presentation on building lovable products using data. It defines lovability as earning genuine love and loyalty from customers. It discusses how products can be made lovable by exceeding expectations, solving real problems, and creating customer allies who want the product to succeed. The document outlines the product development lifecycle, emphasizing talking to users through interviews and research to build empathy. It discusses using pilot programs, internal testing, and A/B testing to gather feedback and continuously improve products. The presentation stresses using both qualitative and quantitative data but notes that anecdotes are often right when they disagree with measurements. It provides frameworks for prioritizing features and bugs as well as examples of product metrics.

1. How to Build Lovable Products Using Data by
LinkedIn Sr. PM
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7. Sparsh Agarwal
TONIGHT’S SPEAKERS

8. Building Lovable Products

9. Photo Lab

10. Photo Lab

11. LOVABILITY [luhv-uh-bil-i-tee]
The capacity to earn genuine, heartfelt
love and loyalty from customers.
Source: ‘Lovability’, by Brian de Haaff, CEO of Aha!

14. What makes a product lovable?
Delight: Exceeds customer expectations
Utility: Solves a real problem
Creates Allies: Customers want product to
succeed

15. DATA [dā-tə]
Facts and statistics collected
together for reference or analysis.
Quantitative and Qualitative
01001100 01101111
01110110 01100001
01100010 01101001
01101100 01101001
01110100 01111001

16. DATA [dā-tə]
“The thing I have noticed is when the
anecdotes and the data disagree, the
anecdotes are usually right. There's
something wrong with the way you are
measuring it.”

17. Product Development Lifecycle
Build Empathy: Talk to users
Intuition, Hypotheses
Formal Research
Inception Development
Product Metrics
Feedback
Continuous Improvement
Post Launch
Pilot Programs
Internal Dogfood
Online A/B Tests

18. Get to know your customers, learn
what they care about and learn to
care about them.
TALK TO PEOPLE!
INCEPTION

19. • Interviews / Focus Groups
• Surveys
• Usability Testing
• Concept Testing
Formal
Research
Methods

20. • Usability Hub
• UserTesting.com
• Invision Prototypes
Tools for
Research

21. Product Development Lifecycle
Build Empathy: Talk to users
Intuition, Hypotheses
Formal Research
Inception
Pilot Programs
Internal Dogfood
Online A/B Tests
Development
Product Metrics
Feedback
Continuous Improvement
Post Launch

22. • Segmentation
(Industry, Size, Revenue etc.)
• Involve customers early
• Early builds / beta launches
Customer Pilot

23. Source: Gusto Blog, by Tomer London, Co-Founder & Head of Product
Feature
Prioritization
Framework

24. • Unexpected moments of delight
• Think beyond happy paths (how
does feature look with less/no data?)
• Onboarding experience
Finesse Matters

25. • Isolated (one change at a time)
• Hypothesis driven
• If it sounds too good to be true,
it probably is
Online A/B
Tests

26. Product Development Lifecycle
Build Empathy: Talk to users
Intuition, Hypotheses
Formal Research
Inception
Pilot Programs
Internal Dogfood
Online A/B Tests
Development
Product Metrics
Feedback
Continuous Improvement
Post Launch

27. • Output, Asset and Value metrics
• UU’s, PV’s, DAU’s are vanity metrics
• Look for repeat usage: Sessions,
Sessions/UU, Retention
• Customer Support Tickets
Metrics

28. Correlation
≠
Causation
Fun Read: Spurious Correlations

29. Bug
Prioritization
Framework

30. • Consumer
• Enterprise
Examples

31. Thank
you

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