1. Digital experiments, also known as A/B tests, involve making small changes to digital content and randomly assigning users to different versions to measure the impact of changes.
2. They provide an unambiguous way to measure the impact of changes through randomized controlled experiments, helping teams find problems, save time and money, and improve performance.
3. The presentation provides examples of how to structure different types of digital experiments and tools for implementing experiments on websites, apps, email and more.
4. User research is important to guide the questions being tested to ensure experiments are strategic and focused on key areas of impact.
13. Know what works (settle arguments and
market the hell of our your success)
Randomized Experiments:
The Gold Standard
Statistical Models w. Controls:
Harder Work, For a Silver Medal
15. Hundreds of experiments…
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38. 1) Does the darned thing work?
Name: an “Impact Test”
Version A: Do Nothing
Version B: Your Communication
39. 2) Can we get anything to work better?
Name: a “Kitchen Sink Test”
Version A: Current Underperforming Version
Version B: Your Best Shot, with everything
40. 3) What fundamentally
resonates with our
users more, X or Y?
Name:
an “Archetype Test”
Version A: Everything is X
Version B: Everything is Y
41. 4) What exactly
drives a result?
Name:
“Isolated Intervention”
(Aka “Microscope Test”)
Version A: A baseline
communication
Version B: The exact
same communication,
with a single small
change
42. 5) Are my tools working?
Name:
“Sanity Test”
(Aka “A/A Test”)
Version A: Something
Version B: The exact
same something