One of the most powerful (and beautiful) things about A/B testing is that it will work for businesses of any size or industry. A/B testing is basically a way to compare two versions of something to see which one performs better. It has evolved over the ages, especially in terms of the contexts in which it is applied — and today, being able to apply it in live, digital environments, makes A/B testing quite powerful and useful.

As a marketer in an ecommerce startup, you could use A/B testing in a lot of important ways. For your core marketing operations, you could test copy, actual advertisements or email marketing; of course, you could also test subject lines or even sending times to see which strategies help you achieve the highest open and conversion rates.

In the context of your website, you could use A/B testing to optimize your product pages, including product descriptions, images and layout designs. You could also use it to determine the best checkout flow and process. Finally, you can leverage it to determine which calls-to-actions (“CTAs”) — to buy, learn more or get a discount — yield the best results.

Though a powerful tool, A/B testing can often be incorrectly applied. Let’s look at four major things that an ecommerce marketer should watch out for.

Related: 4 Ways to Make the Most of A/B Testing Right Away

1. Do not ignore segmentation

If you focus solely on the impact that your experiment will have on the average of a business metric, you can end up with misleading results. This assumes that all your users behave similarly and overlooks the fact that you likely have various segments of users who behave differently. If your A/B test shows that a particular new feature launch will increase spending per user, it might obscure the fact this might only be true for a few heavy users of your product and not the majority.

You need to be aware of your distinctive customer segments. For instance, different kinds of users would have different average spends. You also need to be acutely aware if you have a global product; customers might have different levels of digital access (fast and reliable internet connections on the one hand and slow and unstable connections on the other) or access the internet differently (more people accessing via mobile devices compared to desktop computers). This will influence how accessible a change made to your website is for different users, and thus impact its success.

Segment-level personalization helps you deliver a personalized experience to specific segments. For example, you could show a specific promotion or offer to those who want to buy spices and a different one to those interested in frozen meats. Instead of finding the one version that works best for everyone, this approach will enable you to identify the version that will best serve each of your target audiences.

2. Run your tests for a long enough period

You will need to run the A/B test for long enough to get data that is statistically significant. But if you reach statistical significance in say, three to four days, it doesn’t mean you can afford to turn off your test. You would want the test to run for a long enough period to account for any seasonality or early outperformance. Ideally, you should run an A/B test for at least two weeks — this will help factor in any variances in behavior based on day of the week.

If your test group for a homepage CTA achieves better than the control group in the first two days, it is important to give this test more time as such outperformance might not be reflective of how it will perform over a longer period. This is because the audience that has accessed your homepage in those two days might not be representative of all of your customers and all of their usual behaviors.

Related: Experimentation and A/B Testing: A Must-Use E-commerce Growth Strategy

3. Be careful about testing too many elements

Sometimes startups test too many variables at the same time. If you do this, you won’t be able to isolate what element was the cause of your results in an A/B test. The practice of testing multiple elements at once is called multivariate testing; this will also require much more data to be statistically significant. For a startup, this can be quite challenging.

A/B tests are simpler, more practical and more efficient. If you wish to appropriately use A/B testing to test several aspects at the same time, that will require the creation of multiple variations for each aspect. This will make the whole process slower and require your ecommerce website to attract considerably more traffic to achieve statistically significant results. Be careful about what you are testing for, and make sure you run your tests correctly.

4. Do not ignore external factors

There might be factors outside of your control that impact your business measurably and thus your A/B test. Some of these factors could be seasonal variations or even competitor strategies that impact the behavior of your customers. For instance, if you are running a test during a busy holiday shopping season, it is likely that you will see conversion rates that are high, but such rates will not be sustainable across the year. Consequently, you will need to make sure that you are testing during normal business cycles and use control groups effectively to isolate the impact of the test changes from such external factors.

While A/B testing is a powerful tool, proper execution is key. By avoiding these common pitfalls, you can unlock the full spectrum of its benefits for ecommerce success.

Related: Why Your Approach to A/B Testing Is Costing You Sales