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Once you’ve made a decision, you want to monitor things so you can see how your decision is working out, which gets us to use case #2 for location data: Measuring the effect of a change.
The bigger the change, the more important and complex it can be to measure. Typically, people are looking for location data to help them measure change in one of two ways:
For example, a new e-bike vendor, or Uber launches in Small Town A. How does that change mobility patterns?
If the same thing happens in Small Town B what will that look like by comparison?
As a CRE investor, what can location data tell me about foot traffic in the area around the properties I own, and what can that tell me about what rent growth, or rent default, may look like down the road?
In each case, the intent is to use location data to help measure the effect of change over given points in time.
For example, municipalities are expected to be good at measuring the effects of change. Is that new clinic serving its intended purpose, or would a new downtown arena disrupt traffic on key commuting routes?
The intent of these questions is to measure change not just in an immediate area or timeframe, but with reference to the surrounding area and over an extended period of time. So, identifying collateral effects is really the art of measuring the ripples of that investment.
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