How Location Analytics Can Help Increase Mobile CPMs

Adweek’s recent article, Mo’ Traffic but No Mobile Money, took a look at the mobile CPM challenge plaguing publishers. Even with mobile traffic skyrocketing and smartphone adoption continuing its steady climb, mobile ads still struggle with low engagement, less sophisticated advertising technology and limited screen space, keeping mobile ad prices well below those of their desktop counterparts.


Perhaps the biggest hurdle for publishers though is the lack of metrics currently available to make the case for greater mobile CPMs. As the Adweek article states, “For publishers to justify more mobile investment, the industry needs better metrics, most argued.”


While on-device metrics are important in moving mobile CPMs higher, many publishers often overlook the value of location context that is inherent and unique to the mobile platform. Try to remember the last time you saw someone pull out their laptop while shopping, now try to remember the last time you DIDN’T see someone browsing on their phone in the same store – get the point?


Answering the where in the mobile audience equation has the potential to unlock a wealth of consumer insights to help build the case for greater mobile ad rates. The ability to know and quantify the stores, restaurants, businesses and categories that mobile users are nearby when engaging with publisher content creates a whole new layer of context (and value) for advertisers looking to bridge the gap between the offline and online experience.


In a recent case study, we highlighted how one news publisher was able to increase mobile CPM rates using Placed Analytics location data. Here’s a brief recap of the strategies they used to achieve better mobile ad rates:


Increase Mobile CPMs with Placed Analytics

  • Identify new categories to prospect:
    The publisher saw that 36% of usage occurred nearby restaurants. However, restaurants made up less than 10% of total ad sales. Using this data point, the sales team was able to identify restaurants as a top prospecting category and use location data to back up their pitches.
  • Optimize ad delivery by day and time:
    The publisher discovered that their users were most often nearby department stores on weekday evenings and weekend afternoons, so they decided to optimize the delivery of retail ads to reach visitors during the times and days when they were most likely shopping.
  • Selling to new advertisers:
    The sales team was able to use location data to secure a new supermarket advertiser. Being able to show that 10% of mobile usage occurred nearby that supermarket’s stores, as well as how much activity occurred near competitors’ stores, and which markets had the most competitive behavior helped justify higher rates for access to its more qualified audience.

As 2013 gets underway, improving mobile monetization is set to be a key theme for publishers and advertisers this year as both seek ways to leverage the small screen for big advertising gains.



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