Data Driven A B Testing

Data Driven A/B testing – part 3

Is A/B testing part of your strategic plan? It should be. In part 1, we walked through what A/B testing is and the kinds of things you can test. In part 2, we put together a test plan.

Read part 1 here:

Read part 2 here:

Lastly, let’s figure out where to start testing.

Digital Customer Journey

If you’re not sure where to start, a solid analysis that will give you direction is a Digital Customer Journey to figure out what your channels are doing and start testing messaging. For example: 


We see that our company newsletter, In The Headlights, is toward the end of the journey – meaning it assists in people making a decision and converting. This is a good place to start with testing CTA and different offers. Conversely, you can see that Google Display ads are toward the top of the funnel and help with awareness. You could test different ads that promote free content such as blog posts or whitepapers. You can also test your free subscription assets, such as your newsletter, podcast, or YouTube channel to see if your ads can move someone further into the funnel.


Most Valuable Pages

If you want to get more granular, you can look at the Most Valuable Pages, which are pages on your website that people convert (based on your Google Analytics goals). You can see, for instance, that in Q3 2019, some of our Instant Insights pages were not converting as high as our original research. This tells us that the lower converting pages are where we want to start running tests. 


Google Analytics

If you want to keep it super simple, take a look in your Google Analytics (or Omniture) account. Which pages are getting the most traffic, which are getting the least. Using this information gives you a baseline to work against to see if your tests are having any impact of driving more traffic. When we look at the Trust Insights pageviews, we can see that our newer blog content is getting the most traffic. If we want to refresh and bring up other content, like “5 ways your AI projects fall apart” we could start our tests there. We know what traffic looks like now and then we can compare post-test to see if we were able to improve the page. 


You have the basics and the tools – now get testing! Pick one thing and test it for two weeks to see what happens. You might find that what you test has no significant impact and that’s ok! Keep going so that you know for sure all of your decisions are data-driven. 


Want help putting your test plan together? Let us know!


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