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Factual, Ibotta Identify Unique Behavior Based On Location, Purchase Data

Factual and Ibotta discovered a method to combine location and purchase data that creates audience segments advertisers can use to determine behavioral patterns not identified in the past. The segments are intended to run across programmatic channels, but can be used for a variety of media such as mobile, search, television, video, and display. 

Several unidentified advertisers have begun to make use of location and purchase data through the partnership agreement. Factual is a location data company, whereas Ibotta tracks purchases that allow consumers with a shopping app to earn cash back on in-store and mobile purchases from retailers like Kroger, Target and Walmart.

Those unique behavioral patterns can detect shopping patterns related to the types of restaurants the consumer visits. For example, if the consumer consistently goes to the grocery store to buy avocados, tortillas, and salsa, there is a high probability they would be interested in dining at Chipotle, Qdoba, or Taco Bell explains Mike Dadlani, vice president of media and partnerships at Ibotta.

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The data also analyzes grocery store purchases and determines which consumers have a higher propensity to dine at a Mexican restaurant.

The audience segments for programmatic targeting can be used across a variety of demand-side platforms (DSPs) and data management providers (DMPs) such as Google and LiveRamp.

“When you pair the data, it allows marketers to get a lot more creative,” Dadlani said.

Historically, consumer product goods companies, retailers and restaurants needed to choose between two types of data -- either location or purchase.

The “unique” partnership aims to help advertisers further personalize the experience for consumer based on what they buy, where they buy it, and when they make the purchase, explains Glen Straub, vice president at Factual.

Marketers also have the ability to measure the value of their campaigns, attributing the consumer’s online purchase to in-store behavior. For example, a luxury brand sold at Neiman Marcus can reach the consumer interested in a Chanel blouse, while excluding those who are shopping for the thousands of other items available in a large retail store. The brand also can identify the specific locations driving the in-store purchase as a result of digital campaigns.

Cross-channel shoppers seem to generate higher lifetime value in terms of sales, according to the companies. By understanding the connection between mobile advertising and in-store purchase brands can strengthen their cross-channel strategies.

1 comment about "Factual, Ibotta Identify Unique Behavior Based On Location, Purchase Data".
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  1. John Grono from GAP Research, October 23, 2018 at 6:53 p.m.

    Based on location, purchase data and behavioural data, my new classification system has identified 7.65 billion segments!

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