New Feature: Automated Foot Traffic Segmentation Tool

Lyden Foust


April 28, 2022
Watch the full tutorial on Geosocial Academy

Foot traffic data has become a must for site analysis. While a clear metric like the number of site visits helps decision-making, we know that not every visit is equal. This data does an excellent job of answering the “where” and “how many” details of visits. But it leaves out the “who” aspect of visitors

Traditional Segmentation Methods

Understanding the people behind the visits unlocks the value of foot traffic data. The easiest way to understand otherwise anonymous visitors is to match visits to customer segments. Historically, it has been time-consuming and expensive to do this. Here are the options:

  1. Hire a consultancy to segment foot traffic visits in a weeks-long process.
  2. Have a GIS developer manually map visitors to segments.

Both paths include a five-figure cost and a free headache.

This is why we put so many resources into building a tool that automates the process of segmenting store foot traffic. I am excited to introduce the mobile data upload tool. Upload a foot traffic report from any provider and get your visits segmented immediately

How To Segment Visitors (In Seconds)

Profiling visitors to your site requires three steps:

  1. Download a visitor report CSV from your provider.
  2. Upload the report to the the PersonaLive platform using the mobile data tool.
  3. Receive a summary report profiling your visitors.

Download a Visitor Report CSV From Your Provider

The first step is downloading a raw visit report in CSV format from your foot traffic provider. The CSV should indicate the home block group of the visit. The tool uses that home block group to assign a segment to visitors.

An example of pulling a raw visitation file from Near.

Upload the Report to the The PersonaLive Platform

This is where the magic happens. Once you upload the report on the ‘File Upload’ page, our algorithm applies a weighted distribution of segments based on the home block group of the device. Learn more about this approach.

Uploading the raw file in the file upload tool.

Receive a Summary Report Profiling Your Visitors

An email is sent when the report is ready to download. Below is a sample visitor profile report for the Cincinnati Museum Center.

Customer profile report detailing the percentage of visitors from each segment.

Use Cases

Use cases include any time you’d want to know more about the visitors to a location, such as:


Understand the type of visitor to your city, event, or hotel and market to those types of visitors with relevant upcoming events. Recommend other attractions based on that segment’s interests while they are in town (wine tasting, sports, golf, etc). Learn more about tourism segmentation strategy.

Property Owners/Developers

Let the retail interests of visitors guide tenant selection. Profile potential tenants’ top locations to find a property that matches their customer profile.

Retail / Restaurant

Profile top stores and find markets with a high percentage of top segments. Enhance targeting for your current stores by running ads to your top customers near your store – personalized by segment.


The introduction of foot traffic data has been arguably the most significant innovation in market analysis over the past ten years because it provides a clear answer to two questions:

  1. How many visitors came to this site?
  2. What is the trade area?

We believe that as the use of this data becomes more ubiquitous, people will start to ask:

  1. Who are my customers?
  2. How do I activate that knowledge?

PersonaLive now answers the “Who” in minutes. And by activating those audiences via the Audience Builder, segmentation moves foot traffic data from insightful to actionable.

How PersonaLive Segmentation System Works

Personalive segmentation uses social media, mobile foot traffic, online activity, and individual-level demographics to organize every US household into one of 80 behavioral segments. These segments provide visibility to the online and offline preferences of the customers visiting any US property.

01 Append

Draw a polygon around a property to identify the behavioral segment of every visitor.

02 Analyze

Rank the top customer types visiting a location. Then match retailers based on online and offline activities of visitors.

03 Activate

Demonstrate visitor brand affinity to close deals. Activate marketing campaigns to drive target segments to your location.

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