Datamatterz Blog

How to A/B Test: 7 Tips for Success

The A/B Test Dream: You tweak a button, headline, or entire feature, then kick back, watch conversions soar, and bask in the success of your data-driven decision-making. 👏🏆
While that dream is achievable, the reality of success through A/B testing can be messier. Having worked with different startups, we noticed that many still fail at this, getting increasingly burnt by bad A/B tests and ending up with unclear results. 😓
But don’t run away from A/B tests just yet. This is still one of the most useful ways to optimize your product and reach your goals. You just need to do it right.

Here are 7 A/B test tips you can implement today:

(Use these tips to make your experimentation in products more purpose-driven and accurate)
1. Target the right tweaks.
Not every tiny UI/UX decision deserves an A/B test. If the change won't significantly impact key metrics or business goals, spare yourself the hassle. Think strategically – focus on elements with the potential to truly move the needle and not just make the noise.
2. Run your tests for long enough.
A/B tests take time to run. Rushing to conclusions based on limited data is like celebrating a touchdown before the play's over. It's tempting, but remember: statistically significant results need sufficient traffic. Explain this to your higher-up (or yourself) beforehand, stick to the plan and be patient.
3. Choose the right metrics to improve and set realistic goals.
Choosing not appropriate metrics to measure in A/B tests can lead to misleading results. For example, instead of ‘conversion’ many choose 'number of active users' as a target metric. This is generally not advised because the latter is a vanity metric that doesn't let us conclude whether one variant is better than the other. Another metric to be avoided is ‘retention’. Retention is affected by many different factors in the product and is difficult to directly attribute to a specific product change.
4. Segment your traffic.
Not all traffic is created equal. You need to segment your traffic to get accurate results from your tests because differences in traffic can accidentally distort your A/B test results. For example, you might want to test different versions of your website for different demographics, platforms or user segments.
5. Guard your goals.
Guardrails are secondary metrics that you track to ensure that your A/B tests won't have a negative impact on the other parts of your product. For example, you should track session duration or conversion in another affected flow to ensure your don't break anything by improving one thing. Don't forget to think about other important parts or flows of the product that may be affected by the A/B test variants, and set the guarding metrics.
6. Mix quantitative with qualitative data.
During my work with one European Fintech startup, I launched an A/B test with the goal to increase the adoption and usage of money transfers via phone numbers—then this happened.
There was 3 groups in the test: one without any changes in the flow and two other groups with a money rewards for transfer.
Obviously, we saw more users trying out phone number transfers but the returning usage rate was worse for the campaigns with monetary rewards. More users tried the service but just for the sake of getting the reward and never got back to use them again. Because this result was unexpected we turned to user research. Using qualitative data, we found the reason of low adoption for the test group: users didn't understand how these transfers worked and had a lot of security concerns which stopped them from active using of it.
Quantitative data tells you what, but not always why. Combine it with qualitative insights for a complete picture.
*This story deserves its own post. Stay tuned for a deeper dive into the power of combining quantitative and qualitative data.
7. Iterate and learn.
A/B testing is not a one-shot deal. It's a continuous learning process. Analyze your results, identify learnings, and refine your hypotheses for the next round. Remember, even negative results of test tell you something valuable – use them to adjust your course and get closer to your goals.
So there you have it! Seven tips to turn your A/B testing from a time-wasting exercise into a powerful tool for data-driven improvements. Remember, patience, focus, and a healthy dose of curiosity are your secret weapons. Now go forth, test with confidence, and watch your product evolve into something truly remarkable.