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A/B TESTING 
[A.K.A., BUCKET TESTS AND SPLIT TESTING ] 
WHAT IT IS, ISN’T, CAN DO FOR YOU 
+ HOW TO DESIGN YOUR TESTS
What isn’t A/B 
testing?
A/B testing is not 
• A communications strategy 
• An objective unto itself 
• Based on observational data or 
opinion 
• Something that should be 
examined in isolation of other 
information
What is A/B 
testing?
A/B testing is a tool to 
• examine user experience by testing 
2 variants to inform decision 
making 
• use quantitative analysis to shape 
design and copy 
• gather objective information on the 
impact of communication 
approaches
Examples 
• button placement 
• headline wording 
• color in graphics or text 
• link naming 
• photos vs. iconography 
• e-newsletter subject lines 
• banner ad placement
What Can A/B 
Testing Do for 
You?
A/B testing can 
• make communications efforts data-driven 
• help you craft a better user experience 
• aid you in achieving communications 
goals 
• inform your strategies and actions 
• provide quantitative data to inform or 
justify your decision making
How to Design 
Them
By putting on our 
lab coats.
[Insert image of 
fav scientists 
here.]
Scientific method 
1. Ask a question 
2. Do research or intuit a scenario 
3. Create a hypothesis (If/then statement) 
4. Design your experiment using control and 
variable groups 
5. Run experiment and collect data 
6. Analyze your data and draw conclusions 
7. Capture conclusions and share them forward 
8. Rerun experiment or adjust variable for new 
experiment
Tools to Use 
• Paid services like Optimizely.com 
• Free services with other paid services like 
e-newsletter campaign vendors for testing 
subject lines 
• Free services like Google Analytics 
(Content Experiments) 
• Data that you’re already collecting Google 
Analytics (page visits, time on page), 
Google Adwords, e-newsletter click-thru and 
open rates, donations, PDF downloads
What A/B Tests 
Aren’t
A way to break out into 
something completely new. It’s 
incrementalism, not game 
changing. 
A substitute for a vision. 
Useful without enough data.

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A/B Testing Presentation for Comm4Dev

  • 1. A/B TESTING [A.K.A., BUCKET TESTS AND SPLIT TESTING ] WHAT IT IS, ISN’T, CAN DO FOR YOU + HOW TO DESIGN YOUR TESTS
  • 2. What isn’t A/B testing?
  • 3. A/B testing is not • A communications strategy • An objective unto itself • Based on observational data or opinion • Something that should be examined in isolation of other information
  • 4. What is A/B testing?
  • 5. A/B testing is a tool to • examine user experience by testing 2 variants to inform decision making • use quantitative analysis to shape design and copy • gather objective information on the impact of communication approaches
  • 6. Examples • button placement • headline wording • color in graphics or text • link naming • photos vs. iconography • e-newsletter subject lines • banner ad placement
  • 7. What Can A/B Testing Do for You?
  • 8. A/B testing can • make communications efforts data-driven • help you craft a better user experience • aid you in achieving communications goals • inform your strategies and actions • provide quantitative data to inform or justify your decision making
  • 10. By putting on our lab coats.
  • 11. [Insert image of fav scientists here.]
  • 12. Scientific method 1. Ask a question 2. Do research or intuit a scenario 3. Create a hypothesis (If/then statement) 4. Design your experiment using control and variable groups 5. Run experiment and collect data 6. Analyze your data and draw conclusions 7. Capture conclusions and share them forward 8. Rerun experiment or adjust variable for new experiment
  • 13. Tools to Use • Paid services like Optimizely.com • Free services with other paid services like e-newsletter campaign vendors for testing subject lines • Free services like Google Analytics (Content Experiments) • Data that you’re already collecting Google Analytics (page visits, time on page), Google Adwords, e-newsletter click-thru and open rates, donations, PDF downloads
  • 14. What A/B Tests Aren’t
  • 15. A way to break out into something completely new. It’s incrementalism, not game changing. A substitute for a vision. Useful without enough data.