Defining a market in experiential marketing research is typically a simple task, especially in the United States. Offering insights at the state level is usually the “Goldilocks” of insight. Markets aren’t so small that data collection is too low, and range isn’t so big that you are whitewashing responses. As you look at project insights, however, there are a few quirks that are important to address.
Starting at the state level
Are you okay with treating wildly different areas the same?
For some states this is not an issue. Maine, for example, is pretty homogeneous, but in larger states the disparity based on location can vary greatly.
States like Texas can be particularly problematic, where the dense population centers (Austin in particular) are unlike much of the rest of the state. If you do all of your research in Austin, can you really generalize the findings to the whole state?
This is a good place to use benchmarking data. You can compare your state-based data to your historical data to see if any of the trending is out of alignment, then look for plausible explanations.
Going deeper at the city level
On the smaller city scale, how detailed do you want to be?
We had a group that was activating in small towns just outside of Houston and Dallas. Do you really want to define a town that is only two miles from Houston as a completely different market?
If you were there only once, it wouldn’t really have much value as an independent data point. From a retail perspective, you can expect many of these people to be highly involved in the nearby metropolitan area, as it likely serves as a hub for the surrounding small towns.
We ended up using a 15-mile radius to include nearby towns within that perimeter in the major markets. This minimizes any overlap between major cities, and permits us strong regional breakouts to use for analysis.
What’s the best course of action?
Overall, market definitions may have to be revised frequently, but by incorporating these general guidelines beforehand, you can save yourself headaches later on.
States are a good starting guideline, though smaller or more localized programs may require a more nuanced approach. On a larger scale, regional census breakouts can help to compare groups of states easily.
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