Challenges to Consider for Retargeted Campaign

After visiting a website or app, users will behave in different ways. The ideal situation is where a user comes to your site and immediately purchases your products or services. Unfortunately, this is seldom the case. While there are those who will convert on their own, most of them will need a nudge in the right direction. This is where retargeting marketing comes into play. This is a strategy that involves reminding visitors of your products and services in an effort to convince them to convert. As you utilize this technique, here are some of the challenges that you are likely to face.

Creating Test and Control Groups

To better understand the performance of your remarketing efforts, marketers should carry out incremental testing. This will reveal the advantage that is being gained from these activities. This way, they can determine whether there are any benefits of running the re-engagement campaign as opposed to not having it at all.

For instance, an app can consider an A/B test to determine the optimal time after installation, which they should try to engage the new users in a bid to convert them into paying users. While carrying out the test, it is essential that the marketers introduce a control group. This will not be exposed to the experimental procedure. Instead, it provides a performance benchmark for evaluating how users would have behaved naturally had they not been re-engaged. 

When creating test and control groups, a problem may arise when more than one test is being run concurrently. It is necessary to ensure that external factors do not compromise your test group.

For instance, a particular company may identify a specific audience to perform their test on. They will then be subject to a retargeted campaign on a chosen platform. They may be faced with a challenge when their selected audience overlaps with the target audience for other retargeted campaigns. 

The company will have two options in this case. The first one would be to leave out all users who are part of other audiences involved in other retargeted campaigns. Therefore, the test and control groups will not be involved in any other retargeted campaign taking place at the moment. The other option would be to include the test audiences that are overlapping.

Optimal Volume and Duration

The number of users varies from one business to another. Hence, a challenge arises when it comes to choosing a size that will produce optimal results after testing and will be statistically valuable. Also, when selecting the experiment’s optimal duration, marketers need to factor in the high costs involved with a lengthy test period.

One thing to keep in mind is that the entire audience will not qualify for retargeting. Hence, in refining the target test group, it may end up being too small. This may lead to an even smaller control group which will lead to insignificant results. 

In the case where user volume is limited, the test may have to run for longer to effectively capture user engagement and behavior. A lengthy test duration may also be necessary to allow the study of users and the time that they take to convert fully. Hence, there is a need to determine how long incremental testing needs to be conducted to achieve meaningful results.

Outliers

Outliers are an inevitable factor when it comes to data. You, therefore, must find ways of detecting them. You will also need to understand the best ways of dealing with them depending on your KPIs. This is because these outlying cases can offer misleading figures that will, in turn, cause miscalculations in your test results. 

As you figure out what to do with the outliers in your data, it is important to note that volume will also play a significant role. If you are dealing with a large audience pool, then then the outliers will not affect your test as much. For instance, if you have only one unusual purchase, the average revenue per user will be more affected for 50 purchases than for 4000 purchases.

You may feel naturally inclined to exclude the top and bottom outliers of your data. This, however, may not always be the best step to take. It is also necessary that you use the proper method to even out your data. This should be done with reference to your KPIs. 

Choosing the correct method to handle the outliers in your data will significantly impact the calculation of your test results. There is no standard method, and a decision should be made depending on the business model at hand.

Seasonality

It is also crucial that you pick an appropriate time to begin your tests. As you study your KPIs, pay keen interest to the behavioral trend of your users. You should put into consideration seasonal factors that may affect this trend.

An example is a situation where you decide to run your test in the middle of a holiday season or during a promotion season such as Black Friday. It’s no doubt that a larger lift will be shown by your results as compared to that of the control group. This gives a false indication of the performance of the campaign during a typical season. To prevent this unnecessary shift in data, you want to keep in mind these major events and trends at the time when you intend to run your test.

Review the Data from Your Campaign

Getting the results from your test is one step. For your efforts to be meaningful, you still need to analyze them immediately. To do so, you need to establish the right processes for reviewing the data obtained from the test. This can be a long, tedious and expensive process. Therefore, it would be best if you considered using tools that will make this process easier and more effective.

Conclusion

Users who convert naturally are a dream. This is, however, not always the case. Retargeting efforts may be necessary. As you come up with these strategies, it is important that you take note of the above problems that you are likely to encounter when doing so.