Location Data Is Not Created Equal

Using mobile location data to identify trends in foot traffic to a business has made leaps and bounds over the past few years. As mobile app usage has exploded so the amount of location data available. However, not all location data is created equal. As I’m sure you have noticed even apps as stable as Google Maps can occasionally misreport location.

All things considered, we are not yet at a place where this data can be used to create the desired 1 to 1 attribution model that we strive to complete. Even companies the size of Google who have access to vast amounts of data still require the use of poll and questionnaire data to verify location data and do not find the scale needed to create the 1 to 1 match.

Location data is collected and verified in many ways today. The primary means to date generally fall into 2 categories. App and Web collected data and Questionnaire or Poll data. Web and App data is collected when the user opts into sharing their location data from an app or site. Questionnaires or polls are surveys sent to users to collect or verify their data.

What data we use and how it is verified is often determined by the scale of your locations and volume of foot traffic at those locations and the size of the marketing campaign supporting it. The response rate on questionnaires or polls tends to be a fraction of the total reached user base and is often applied to large-scale marketing campaigns tracking millions of users.

This data, if used in the right way can be incredibly insightful and can inform the optimization of marketing campaigns to maximize return on investment. However, to be usable the amount of collected data must achieve the proper scale in user count and be collected over several months to truly find trends that are statistically significant enough to make optimization decisions or judge success.

Ultimately, it’s all about creating enough data, so things like campaign duration and targeting matter, too. As a rule of thumb, longer campaigns are better when it comes to generating a substantial amount of data to provide analysis

Source: Martechtoday.com

This type of attribution is very similar to political exit polling in that it isn’t 100% accurate at all times but, at the proper sample size can often predict the correct trends and forecasting.

Want to learn more about how you can use in-store attribution and location data? Contact Us to learn more.