Accuracy is a critical factor in a content testing and optimization program that is too often overlooked. Getting the most accurate results from your testing means you will have better information and a clearer, more confident picture of customer preferences and behavior on which to base business decisions. Safeguards must be in place to ensure the validity of the data sources, the analytics, and the analytics reports that are used to convey the data captured within results. Knowing these safeguards are in place gives you the confidence to make business and user experience decisions in real time based on the trends you are seeing in campaigns.
Ensuring accuracy in the testing of marketing content involves building an effective test design based on your goals and metrics, feeding the right data and rules into the tool or engine for desired impact, and having a depth and breadth of recorded results to filter by in order to determine effective takeaways based on a sufficient analysis of the results.
Too often, testing and optimization solutions take shortcuts such as making quick, broad assumptions based on a simplified view of the test results, skewing the data to achieve the desired results, or merely taking an “average view” of a diverse visitor base. It is important to understand that your visitor and customer base is diverse. Distinct, accurate customer preferences need to be identified in order to provide the best customer experience, rather than making broad assumptions based on a limited view of the data.
Beyond simply understanding what types of information will provide you with the best answers, the software you use to design and test your digital marketing content must have built-in safeguards to protect and secure the accuracy of results.
The most basic thing that can affect your ability to create accurate testing results is the depth and richness of the data available to you. The perspective that rich data provides can greatly assist in the formulation of the most effective rules or hypotheses to test. Many tools simply use the data designated to be captured by the tool itself in particular locations, or even within single sessions, as the basis for high-level testing and targeting assumptions. However, this limited data set doesn’t provide a comprehensive view of customer behavior and the factors that influence it. This can result in the loss of significant data points, such as other customer interests, whether a return visitor responds differently to the same set of material, or simply whether the user is an existing customer.
Historical data can be particularly insightful. Incorporating historical analytics data into your testing can more clearly identify significant preferences and parameters for a particular audience, or even a specific individual, over time. Also, identifying trends within your tests as they occur over time can provide unique insights into factors that affect how people react to your content. These factors can include cyclical events, such as seasonality, or simply how the marketplace changes over time. Capturing your data’s time factor allows you to see correlations within the data that you might have otherwise missed.
Other types of data that can help improve accuracy are third-party data sets and captured analytics from areas where the tests aren’t being implemented into your testing tool. Third-party data includes information from data providers who compile data from myriad sources, such as search engines or other websites, that helps to inform you where your visitors are coming from and what types of interests they may have outside of your company. You can use this data to identify richer subsegments of your customer set based on these preferences that couldn’t be known by just capturing data within your test environment.
Not having these data sets available, or the ability to filter your results by these variables, makes your program blind to their potential impact or influence on conversion, and severely limits the accuracy of the limited analyses you can conduct.
In my next article, I’ll look at some of the safeguards that can be put in place to ensure the accuracy of your testing, and what techniques are available to you to improve that accuracy.