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LSA15: Location Targeting, Location Data, Location Analytics

Location, location, location. The sophistication of location-targeting and online to offline attribution are really moving the needle when it comes to reaching local consumers and understanding their reaction to locally targeted ads and messages. During the first panel discussion at LSA15, experts in the location space provided some insight into the latest practices and technology behind targeting and attribution.

Location Targeting

Loren Hillberg of Thinknear talked about the evolution of location targeting. From mapping locations and reaching those consumers in those locations, to targeting specific demographics in those areas, the space has evolved drastically.

Today, targeting “audiences” is the latest trend in location. These audiences are built based on a series of data layers such as:

  • Contextual: Reaching consumers based on where they have been recently or where they are now.
  • Behavioral: Using location data over time to get a stronger understanding of what a consumer does.
  • Demographic: Targeting based on age, gender, marital status, etc.
  • 3rd Party Data: A variety of organizations sell consumer data that can be layered overtop these other forms of data.

Manifestations of Location Data in Media

Todd Juneau of Mindstream Interactive went into the ways location data is actually showing up in media. He discussed a variety of tactics he is seeing include:

  • Programmatic Media: Using location data to buy and sell location based ad inventory.
  • Household Extension IP Targeting: Targeting 1st party audiences across all household devices via household extensions and leveraging IP targeting to reach prospects across screens.
  • Mobile Location Targeting: SDKs are tracking tools embedded in apps that allow for targeting true lat/long location data instead of geo-targeting which is not always accurate.
  • Pre-Roll Video Targeting: YouTube has introduced geo-targeting, cross device views, analytics, and allow advertisers to only pay when watched

Online to Offline Attribution

David Shim of Placed went into the weeds as it relates to tracking online to offline consumer activity and how that currently is being handled in the marketplace today. Based on an opt-in tracking model, Placed is capturing some really interesting insights into the online to offline journey and showcased these insights in a variety of case studies:

  • Case Study 1: A high-end retailer wanted to attract more 13-24 females. By tracking consumers who had opted into Placed’s tracking tool, they found that this demographic of consumers were coming to store, but going to less expensive stores to buy. This insight could inform a geo-fencing campaign to track these consumers.
  • Case Study 2: People who went to Kohl’s on Black Friday also went to Walmart, Target, Best Buy. Knowing this, Kohl’s would be able to similarly create better, more informed geo-fencing campaigns.
  • Case Study 3: Of people to go on auto lot, 51% of people with smartphone look at prices, payments and offers. Highlights importance of targeting these places, meaning 51% are open to visiting another lot

Q&A

What is really happening in the world of location targeting?
More clients are moving into highly sophisticated campaigns, especially in regards to attribution and offline analytics. On the agency side, looking to location experts like Placed and Thinknear allows organizations to become better educated on what is going on.

Do these sophisticated targeting and attribution models work on an individual store basis?
While these kind of practices don’t work well for SMBs given such their limited budgets, from a benchmarking standpoint, these sophisticated practices and analytics allow you to show what kind of targeting tactics are driving store visits. Once people start asking questions about these location analytics and attribution technologies, people are quick to see the value.

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