• by Charlene Weisler , Op-Ed Contributor, February 13, 2019

The race for the best attribution model is on as technology improves and cross-platform connections advance. An entrant in the ad-to-in-store attribution solution is Placed, which uses an opt-in app to track where people go and rewards them with gift cards, sweepstakes entries and charitable donations in exchange for sharing location and device data. 

David Shim, founder and CEO, Placed shared how his company measures attribution.

Charlene Weisler: What is your definition of attribution? Multi-touch attribution? And the most effective attribution models available today?

David Shim: In the case of Placed, attribution is measuring the impact of ad exposures on store visitation. With partnerships across 400+ publisher, networks, and platforms, Placed is able to directly measure an ad impression on digital, TV, and OOH to a real-world store visit.  

By delivering a single currency across multiple channels of advertising, Placed enables advertisers to measure and optimize to the most effective media, regardless of platform.

Weisler: Will we ever get to true attribution? What do we need that we may not have now?

Shim: True attribution requires the ability to measure each ad touchpoint prior to conversion.  In order to measure each ad impression, it requires partnerships be established in advance of any campaign. 

Once these partnerships are in place, the ability to measure each ad impression across multiple partners enables a true view ad exposures mapped back to the ultimate conversion, which in Placed’s case is store visitation. 

In the last two quarters, we have announced partnerships with such companies as Adobe, Inscape, Pandora, Roku, Roku and others. This ability to drive adoption across TV, digital, audio, and OTT is the basis for enabling true attribution.

Weisler: How does Placed map attribution? Tell me more about your process.

Shim: Placed processes over 3 billion raw location signals on a daily basis to generate over 100 million visits on a daily basis. This visitation is then mapped back to ad exposures across our 400+ partners across digital, TV, and OOH to determine store visits and incremental store visits utilizing a programmatic conversion window. This conversion window takes into account the number of days after ad exposure, as well as distributing credit across all ad impressions.

Weisler: Does it map all types of stores, products and services across genres? If not, what is missing?

Shim: Placed takes a meta-based approach to mapping store locations. Rather than limiting ourselves to a single place database, we license store location data across a variety of providers enabling a much larger and more accurate view of businesses and locations than a single place database.

Weisler: What media is part of Placed model? How do you follow cross-platform? Print? Radio?

Shim: Placed measures digital, TV, and OOH. In terms of sub-categories, we break digital out into a number of categories including audio, connected TV, desktop, mobile, programmatic, search, video, etc. In terms of TV and OOH, we supports linear, addressable, and programmatic.

Weisler: What metrics do you use?

Shim: With location-based attribution, store visitation is the base metric that counts the number of store visits tied to ad exposure. Building upon store visits are two different lift metrics that determine if the store visit was incremental.  

Standard Lift measures the difference in store conversion rates for exposed versus a similar looking unexposed population. This metric is utilized heavily when a customer isn’t a regular visitor (ex. Auto, Furniture, Theatrical). 

Behavioral Lift incorporates past visitation into the calculation for incremental visit. If a consumer goes to a coffee shop three times a week, do they go four times the following week due to the ad exposure, generating Behavioral Lift.