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Geoframing is a highly accurate audience building strategy using location analytics to pinpoint the mobile devices observed within a user-defined polygon during a particular window of time. This is totally different from geofencing, which is an ineffective digital advertising tactic that attempts to serve ads in real-time to devices in a specific geographic area. Geoframing accurately builds a larger, targeted audience of mobile device IDs or household addresses that an advertiser can reach via multiple channels, where and when they are active. Drawing on data from over 500 million devices, the OnSpot platform delivers a best-in-class tool to build audiences using Geoframes.

When building Geoframes, the context of the location is very important to consider in order to ensure you are capturing the largest, most targeted audience. Take a look at the list below for best practices when creating Geoframes, and ultimately, Geoframe audiences.

Consider things like:

  1. User Behavior & Device Usage – Is the location a place where people are likely to spend time and use their mobile device? Or, is it more of a transient location that people move through quickly or are engaged in an activity where they don’t use their phone? Ensure your Geoframe includes areas where users are likely to be on their device, such as parking lots.

  2. Population Density – Is the location in a populated or rural area? Are there busy roads or public transportation hubs nearby?

  3. Business Density / Surrounding Businesses – Is the location a standalone structure or within a larger building like a strip mall or office park?

  4. Movements to and from the location – Does the location have dedicated parking? Or would someone have to park elsewhere and walk in order to reach the location?

Thinking through these items will help you capture the right devices and will enhance accuracy for audience creation, analytics, and attribution reporting.


Here is a rooftop-only Geoframe for a restaurant within a larger commercial building with a device count of 1,051 for the 6-month time frame. Although this count indicates that patrons to this restaurant are using their devices while inside, you are likely to miss some customers. There will be people using their device to navigate to the location in the parking lot, and then putting their device away once inside the restaurant.

Example of a small geoframe at a restaurant within a strip mall.

Now, let’s take a look at the device count when we include surrounding parking. Redrawing the polygon to include the full footprint of the restaurant and the likely customer parking bumped up the device count to 6,614 over the same 6-month time period. Once turned into an audience, this Geoframe will provide more accurate insight & demographic reporting of the customers of this restaurant. It can also be used for attribution reporting and help the advertiser understand footfall traffic to this location based on who was targeted with a campaign.

Example of a small geoframe at a restaurant within a strip mall that includes surrounding parking.

Overall, following best practices for creating Geoframes will go a long way to ensure your audiences are capturing the appropriate devices and produce accurate reporting. Reach out to OnSpot support for any questions you may have around this process.

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