Qual vs Quant: Using Better Data to Build Better Products
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The document discusses the importance of combining qualitative and quantitative data to enhance product design and user experience. It emphasizes a systematic approach through identifying problems in user funnels, understanding user behavior, proposing solutions, and iterating based on findings. Additionally, it highlights the value of A/B testing and learning from both types of data to continuously improve product offerings.
Qual vs Quant: Using Better Data to Build Better Products
- 1. Qual vs Quant Using Better Data to Build Better Products Laura Klein laura@usersknow.com @lauraklein
- 2. Who’s Tired Of Hearing About Data?* *be honest
- 3. A/B Testing
- 9. Sorry. I’m Going To Talk About Data Some More.
- 11. Well…Sometimes
- 12. What Data Can’t Do Replace Design Replace Listening to Users Tell Us What We Should Be Building
- 13. What Data Can Do Inform Design Inform Research Tell Us What We Should Be Investigating
- 14. How About An Example?
- 15. A Funnel
- 16. A Checkout Funnel Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell
- 17. A Leaky Checkout Funnel 100% Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell -20% -10% -50% -33% -25% == ???
- 18. What That Means to You 100 Buyers Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell -20 Buyers -8 Buyers -36 Buyers -12 Buyers -6 Buyers == 18 Buyers
- 19. 100 To 18???? How Do We Fix This?
- 20. Identifying a Friction Point 100 Buyers Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell -20 Buyers -8 Buyers -36 Buyers -12 Buyers -6 Buyers == 18 Buyers
- 21. Stop It
- 22. Quantitative Data Qualitative Data Understanding the Friction Point
- 24. How Can You Use Them Together?
- 25. Step 1: Identify the Biggest Problem
- 26. Step 1: Identify the Biggest Problem Use Funnel Metrics
- 27. The Biggest Problem 100 Buyers Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell -20 Buyers -8 Buyers -36 Buyers -12 Buyers -6 Buyers == 18 Buyers
- 28. Step 1: Identify the Biggest Problem Use Funnel Metrics Quant
- 29. Step 1: Identify the Biggest Problem Use Funnel Metrics Step 2: Understand Why
- 30. Step 1: Identify the Biggest Problem Use Funnel Metrics Step 2: Understand Why Observational Usability
- 31. Step 1: Identify the Biggest Problem Use Funnel Metrics Step 2: Understand Why Observational Usability Qual
- 32. Problem Possibilities Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell -36 People • Didn’t have payment info handy • Confused by specific question • Looked for promo code
- 33. Step 1: Identify the Biggest Problem Use Funnel Metrics Step 2: Understand Why Observational Usability Step 3: Propose Solutions
- 34. Step 1: Identify the Biggest Problem Use Funnel Metrics Step 2: Understand Why Observational Usability Step 3: Propose Solutions Create Solution Hypotheses
- 35. Solution Hypothesis ! Problem People looked for a promo code.
- 36. Solution Hypothesis ! Possible Solution Remove promo code entirely.
- 37. Solution Hypothesis ! What Do We Think Would Happen? An increase in conversion.
- 38. Solution Hypothesis ! What Might Go Wrong? A decrease in acquisition or revenue.
- 39. Step 4: Learn & Iterate* *The last step is always learn & iterate! Quant & Qual
- 40. Learn… ! How Would We Know We Were Right? A/B test of the checkout flow with and without the promo code.
- 41. What Really Happened? Create Account Select Plan Payment Info Address Confirm Thanks & Up Sell
- 42. Why Did It Happen? Qual!
- 43. …And Iterate ! Another Possible Solution Create custom landing pages rather than promo codes.
- 44. Step 1: Identify the Biggest Problem Use Funnel Metrics Step 2: Understand Why Observational Usability Step 3: Propose Solutions Create Solution Hypotheses Step 4: Learn & Iterate!
- 45. Or…
- 46. Step 1: Identify the Biggest Problem
- 47. Step 1: Identify the Biggest Problem Interview Current Users Qual
- 48. Step 1: Identify the Biggest Problem Interview Current Users Step 2: Understand What
- 49. Step 1: Identify the Biggest Problem Interview Current Users Step 2: Understand What Study Relevant Metrics Quant
- 50. But Why?
- 51. Step 1: Identify the Biggest Problem Interview Current Users Step 2: Understand What Study Relevant Metrics Step 3: Propose Solutions Create Solution Hypotheses
- 52. Step 1: Identify the Biggest Problem Look at Your Sales Pipeline Step 2: Understand Why Interview People Who Said No Step 3: Propose Solutions Create Solution Hypotheses
- 53. Step 4: Learn & Iterate* *The last step is always learn & iterate!
- 54. Once Again… Quantitative Data ! WHAT Qualitative Data ! WHY
- 55. Better Data == Better Products
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