How Accurate is your Geo-Fencing?

One of the most popular products that we offer is Mobile Conquesting, and it’s also one of the more advanced and sophisticated products we offer, because of all the shiny bells and whistles that it offers. With Mobile Conquesting, we can target people by online behaviors (people who have shown specific behaviors online or are in a certain demographic) and also by offline behaviors (targeting people by where they have been tracked with their phone recently, such as a location, business, or specific brand name stores).

That’s the first layer of Mobile Conquesting. With the second layer, we can add in all sorts of “geo” terms, like geo-fencing, geo-retargeting, and geo-retargeting lookalike, where we put a tight radius around an address to capture device IDs and serve ads to those mobile devices. While this is a really neat product, some people might question the validity of how a tight radius is determined. Is the advertiser going to have wasted impressions because the radius is cutting into the neighboring business? Or they are counting people in the parking lot of the strip center that the business is located in? Is the radius actually around that business owner’s location?

IF YOU ARE DOING GEO-FENCING FOR YOUR BUSINESS YOU SHOULD ASK YOUR DIGITAL PROVIDER WHAT TECHNOLOGY METHOD THEY ARE USING!

I’m going to break down different methods mobile technology vendors use for geo-fencing businesses:

Radial Fence by Address – The most basic method of location-based geo-fencing is by placing a radius around a place’s address. Since addresses were built to provide directions to the location, many times the physical location is across the parking lot or on the street.  Research estimates that there can be up to 84% waste in targeting this way.

Radial Fence by Geo-Code – This method places a radius around the center of a business or location. Since most locations are not circular, there will inherently be waste. How much waste depends on the size of the radius.  Research estimates that there can be up to 75% waste in targeting this way.

Parcel Mapping -Also known as property mapping and tax mapping are maps typically built to identify property boundaries and is a popular data source for industries such as real-estate. Parcels can often contain many businesses in the same plot.  Research estimates that there can be up to 51% waste in targeting this way.

Polygon Mapping (This is the technology that we use with Mobile Conquesting) – Polygons are formed by tracing the store or place boundary based on satellite images and latitude/longitude and capture the precise boundaries of a location.  Percent waste = 0%

Now that we have taken a peek behind the curtain to see how geo-fencing is put into action, let’s talk about on-site visit tracking. Another one of the bells and whistles that business owners love about Mobile Conquesting is that they can see their return on investment because we can show how many people saw their ad, and then physically came to their location, but how do we track the actual business, and not surrounding areas?

In-Store mapping is the most granular polygon layer, serving to precisely map the outlines of the business or point or interest.

On Lot mapping is a polygon layer that separates a business from it’s parking lot.  In instances of a standalone business, this could be the entire parking lot.  For strip malls or adjacent storefronts, this will typically just be the area directly in front of the business.

Here is an example of an auto dealership polygon: 

How visits are verified:

Once the location signal is matched to a place, the final step is determining whether a visit has actually occurred.  The following data is evaluated to determine whether a visit is deemed to be verified:

  • Store hours – How frequently does the user visit and for how long? What are the store hours and when did the visit take place? Only visits that occur during open store hours are counted.
  • Employee status – Understanding employee status allows (when people work and how often) allows the system to exclude employees.
  • Dwell time – How long did the user spend in the store? Dwell time is used to filter for inaccurate visits.
  • Speed – How fast was the user moving when he/she was tracked as a visit? If they’re moving faster than then the system’s average speed threshold, the visit is not counted.
  • Horizontal accuracy – What is the percent accuracy of the lat/long the system received? If the horizontal accuracy that falls within the polygon that is being tracked is not higher than the system’s average percent threshold, the visit is not counted.

This verification process means that the system has a 94% accuracy rate!