This document discusses an experimentation process for growing a business that involves 4 steps: 1) Using data to identify problems to solve, 2) Forming hypotheses about solutions, 3) Testing hypotheses through experiments, and 4) Acting on the results by deciding what to implement or test next. It emphasizes starting with quantitative user data to point to high-traffic, low-conversion areas to improve. Qualitative user research can inform hypotheses. Proper documentation and checklists help avoid unintentionally decreasing conversions when testing. The goal is to continuously learn and improve through experimentation.

1. Growing Your Business Through
Experimentation
Hiten Shah
hnshah@gmail.com

2. Product, Design, Engineering, Marketing, Growth, Sales
What do you do?
 

4. How do you make
all the things
better?!
Figuring this out is your job.

5. A/b testing

6. Only 1 out of 5 tests win.
4 out of 5 tests cost
you money.

7. So, why experiment if so many tests fail?

8. Go Where Customers Are!
Long, slow, SaaS ramp of death from 2006…

9. Go Where Customers Are!
Now…

10. Go Where Customers Are!
Growth can be sped up!

11. Increase Hello Bar’s installation rate

12. Improve the KISSmetrics features page

13. Increase signups from Crazy Egg’s homepage

14. Grow Crazy Egg’s revenue

15. Results from 3 months of focused growth effort

16. Results: KISSmetrics signups over time

17. Simple 4-step experimentation process
Data
Figure out what to improve
Hypothesis
Make an educated guess
Experiment
Test your guess
Act
Decide what’s next

18. Data
Figure out what to improve

19. Data doesn’t make decisions for you.

20. Data informs your decision making.

21. Data helps you identify the most
painful problems people have.
(not the ones that bother you the most)

22. Find problems worth solving by
starting with quantitative data.

23. When in doubt, look at your top pages. Usually the homepage.

24. A simple framework for choosing what to improve

25. Find pages with high traffic and high bounce rate
HTTP://GOOGLE.COM/ANALYTICS

26. Find pages with high traffic and low conversion rate
HTTP://UNBOUNCE.COM

27. Find sources with high traffic and low conversion rate
HTTP://HUBSPOT.COM

28. Find opportunities based on user paths
HTTP://KISS.LY/KMPATH

29. Increase Conversions
By A/B Testing
Do a Happy Dance
But Watch it Closely
Get More Traffic
So You Can Start A/B Testing
Get More Traffic
So You Can Do a Happy Dance
High Traffic
Low Traffic
High ConversionsLow Conversions
How To Figure Out What To Improve

30. Where do you have the most
visitors, users, customers,
emails, or notifications?
More volume helps you test faster.

31. ๏ Website Traffic / App Installs
๏ Welcome Emails
๏ Web / Mobile Onboarding
๏ Email Digests
๏ Triggered Notifications
๏ Cart / Funnel Abandonment
๏ Dormant / Churned users
Common areas with large volume and high impact potential

32. What percentage of your
customers or users have
adopted each feature?
Intercom on Product Management
When you’ve already got usage, analyze it.

33. Find out why by getting
qualitative data.

34. A few qualitative tools
HTTP://USERTESTING.COM HTTP://SURVEYMONKEY.COM

35. A few more qualitative tools
HTTP://QUALAROO.COM HTTP://OLARK.COM

36. Use exit surveys to learn why people bounce
HTTP://QUALAROO.COM

37. Use post-conversion surveys to understand why
HTTP://QUALAROO.COM

38. Discover if your web pages are effective at their goal
HTTP://QUALAROO.COM

39. What frustrates people?
EMAIL

40. Find people who don’t do things and email them
EMAIL + SURVEYMONKEY

41. User Research gives you a headstart

42. Hypothesis
Make an educated guess

43. Ideas
Designs
Solutions
Assumptions
(A guess about the best way to solve a problem)}

44. Everything can start with a
testable hypothesis.

45. Before you create anything, make an educated guess.

46. Use simple equations to assess potential impact of each idea
DAN MCKINLEY HTTP://KISS.LY/DANETSY
visits x conversion rate x order value x li4 = ?
users x order value x resurrec7on rate = ?
ESTIMATED
ESTIMATED
MODELED
MODELED

47. Assess the potential impact,
difficulty and priority of
each test idea you have.
Prioritize your tests

48. Experiment
Test your guess

49. Test your hypothesis by starting
an experiment.

50. Not button colors…

51. Don’t copy “best practices” blindly

52. Test specific button copy

53. Sensitivity tests help you
learn what your visitors care
about and what they don’t.
Run sensitivity tests on your web pages

54. Remove graphical elements and see what happens

55. Does social proof and logos matter for your visitors?

56. Remove social proof and learn what happens

57. Act
Decide what’s next

58. You’ve probably seen an A/B testing report before

59. 1. Your starting hypothesis.
2. Dates for when you ran the test.
3. Screenshots of control and all variations used during the test.
4. Expected change in conversion.
5. Probability of change.
6. Screenshot of the raw data used in your analysis.
7. A screenshot to the A/B Test Report in KISSmetrics.
8. The decision you've made from the test.
9. What you learned from the test.
Document every A/B test and create a playbook

60. What learnings do we want to
carry over from the past?
Helps you avoid unknowingly
decreasing your conversions.

61. ✓ Keep the footer links
✓ Autofocus on the first form field
✓ Do not include social proof
✓ Link to the features page
✓ Use “Log in” copy on the button
Create experiment checklists based on learnings

62. If you’re not testing,
you’re not learning.
☀

63. Always have tests running,
no matter how small.
⌾

64. If you don't have a process,
you won't continuously improve.
∞

65. Work on things that matter.
Make those things better.
Be happier ☺

66. Thank Y0u =)
Got questions? Need help?
Contact me any time!
Hiten Shah
hnshah@gmail.com