Beacons As A Data Source – Beacon Stats & A Case Study

As beacon installation in retailers reaches the tens of millions, our database of classified beacons becomes one of the most unique and powerful mobile audience targeting tools on the planet.  Let’s begin with the beacon stats.

Juniper Research estimates that by 2020 retailers will invest $2.5B in Internet of Things technology for their locations. The majority of that will be spent on beacons and RFID tags.  

Just for fun, let’s estimate that half of that $2.5B goes towards beacons, or $1.25B.  The average price on a beacon today is about $30, give or take a few dollars depending upon type and quality. That represents over 42M beacons, essentially blanketing the globe.

Chuck Martin at MediaPost reports on this research, and another stunner, in this Sept 2015 article. The second doozy is that the 2015 Store Operations Survey states that 46% of retailers plan to implement, or have already implemented beacons this year.

Tying this back to Reveal Mobile, we build mobile audience segments based upon when, how often, and where devices bump into beacons. We’ve got a handful of patents filed, with more on the way, for the algorithms we use to detect, place, and classify Bluetooth beacon signals anywhere in the world.

Today, the 100,000+ beacons that we’ve classified prove incredibly valuable to both app publishers and advertisers, and we’re only scratching the surface. Beacon detection occurs while the app is running and also while in the background on a phone. This drastically increases the size of location-based audiences in contrast to exclusively lat/long derived audiences, which require the app to be opened and running.  

Here’s a real-world example.


The NC State Jenkins MBA program (proud alum) wanted to reach target audiences in mobile apps for their full-time, executive, and online programs. Working with Reveal Mobile, two rare things happened, resulting in a great outcome.

  1. We targeted against demographics in native mobile apps: income, education, age ranges. This is surprisingly difficult and rare data to come by in apps. Cookie tracking doesn’t work in native apps.  Part of our secret sauce is surfacing demographics from multiple data sources.
  2. We targeted against devices that had bumped into beacons we classified as being at airports.  This “travel” audience proved to be a relevant audience for online programs. This may have been the first beacon-powered retargeting audience campaign in the country.  Pretty cool.

The result: Campaign performance more than doubled, achieving a click-through rate of 1.00%.

Grab the full case study here, which explains how Reveal Mobile, WRAL, and the Jenkins MBA Program worked together to build this innovative campaign.

Bring on the beacon explosion. 








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