Research Terms in Experiential Marketing Analytics

Written by PortMA

Research Terms in Experiential Marketing Analytics

Updated May 2021 – Estimated reading time: 3 minutes

Experiential marketing research is a powerful tool. But, it’s oftentimes misunderstood. Unless you’re a researcher (or a research junkie), your eyes may likely glaze over when terms like sample size, the margin of error, or confidence interval are mentioned.

As a consumer, it’s vital to understand the following research terms in experiential marketing. Even a fundamental awareness helps protect you from accepting a sub-par research product as gospel. The “Garbage In, Garbage Out” idiom applies directly to research.

Quantitative v. Qualitative Research in Experiential Marketing

There are two primary approaches to research: Quantitative and Qualitative. Qualitative research helps with the process of discovery. It typically utilizes focus groups and in-depth interviews. While an important and legitimate approach, qualitative research is not the focus of this article.

Quantitative research refers primarily to things that can be measured objectively and analyzed using mathematical and statistical techniques. Survey research is a good example. Thus, composing a proper survey is a science unto itself. Let’s begin with these three experiential marketing research terms: Sample Size, Segmentation, and Margin of Error.

Sample Size – Number of Respondents in the Experiential Marketing Research

The sample size is an important aspect of any survey research. The more completed surveys available in experiential marketing practice, the more confident we can be with drawing accurate conclusions and applying them to a broader population. For any given program, we aim to get between 350-400 completed surveys per market. This affords greater flexibility with segmenting the responses and analyze them accordingly.

Segmentation – Dividing Experiential Marketing Respondents into Key Groups

Segmentation is where we can provide the most value in experiential marketing analysis. For example, it’s not enough to say that 75% of consumers surveyed are willing to purchase Product X. That may appear to be a good number. But what if we took a closer look and segmented the data by gender?

One might find that the majority of those willing to purchase Product X are women. That is great news if Product X is targets women. But what if Product X targets men?  The research would seem to indicate that the experiential marketing campaign is reaching the wrong target audience.

Before jumping to that conclusion, we would work with our agency client to confirm if and how the Field Staff are engaging the target consumer. Then, we would determine if we need to make changes to engage the target consumer better. This single differentiation can provide powerful and actionable insight.

Margin of Error – Accuracy of Experiential Marketing Results

The power of this term in experiential marketing is that if we have a small number of responses, this insight is also small as the sample size decreases, the margin of error increases. The margin of error is a statistical term that provides a sense of how much error is likely to occur in sampling. Thus, fewer responses generate a greater likelihood that results will be more prone to error (a.k.a. statistical flutter).

The margin of error displays a +/-xx% (you see this with political polls). For example, if your exit survey results indicate that 75% of consumers are going to purchase Product X,  and if there is a margin of error of plus or minus two percentage points, you can reliably assume that between 73% and 77% of your consumer base has a strong intent to purchase Product X. We discuss this further in our discussion of statistical significance.

The key takeaway is that the greater the sample size, the more reliably the results and the ability to apply them to a broader consumer base. In addition, the more data, the more we can dig into it to find actionable insights that help drive the success of an experiential marketing campaign.

Additional Resources


  • Experiential Measurement Blueprint
  • Event Impression Calculator
  • Experiential ROI Benchmarking Reports
  • Event Measurement Video Tutorials
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