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Consumer data is invaluable to digital marketing. It allows brands across all industries to track customer behavior online, measure checkout amounts, identify loyalists and model top-performers to find lookalike consumers.

Within the realm of consumer data, the two most popular sources are first party data, which a brand collects directly, and third party data sold by tech providers. While both have their advantages, they also have their limitations -- ones that brands can overcome.

First Party Data

One of the biggest benefits of this type of data is that it is free and proprietary to the brand. Other sources of data, in comparison, are under the ownership of a data seller and sold to any other brands willing to pay -- often times to competitors.

While first party data is brand-owned, it includes current customers, only. For a digital marketing campaign, setting up audience targeting solely with first party data does not discover new audiences. Brands that limit their targeting to their own customer data -- even those that model off of their own customer data and purchase third party data with segments that match with their own -- are preventing themselves from discovering new personas that are different from their known customers and perform just as well.

Third Party Data

While this type of data runs at a cost to marketers, it does allow them to scale out their audience base to include prospects that a brand has yet to interact with.

Third party data providers develop and sell consumer segments based on behaviors, intent, personalities, demographics, lifestyles, and past purchases. They even provide brands with specific and/or time-sensitive segments that can align directly with campaigns (e.g., a World Soccer segment for marketers looking to advertise during the World Cup, or a Traveling with Kids segment that includes moms and dads browsing vacation options for their children’s winter break).

While third party data opens a door for many marketers looking to expand their targeting, it has its drawbacks. The many hundreds of categorizations that exist to help marketers find and access particular aspects of consumers can sometimes misplace consumers based on search habits. For example, an American regularly searching online to learn more about the horrific terror attack in Paris in early January might have accidentally been placed into a France travel destination segment.

Additionally, third party data is perishable. Someone placed in a dating segment now might be in a relationship next month, but continue to be targeted for online dating apps and services. Not only that, but third party data is often inferred. While some providers guarantee that data is demonstrated or self-declared by consumers, this is not always the case; some providers use lookalike modeling to beef up their segments.

Self-Declared Data

First and third party data can be complemented with scalable, campaign-specific, consumer-declared data. Like first party data, self-declared data can be free and proprietary to a brand, but it also has the scalability that third party data has. Adtech vendors who provide this type of data are able to set up a question that asks consumers directly about their preferences, behaviors and values. This question is run at large through a social network, and it collects data that can jumpstart a campaign.

This type of polling identifies a micro-segment that is instrumental for marketers who are launching a product or trying to find a new audience. Imagine, for instance, a pizza brand looking to target deep-dish pizza lovers with a new, innovative deep-dish option. By asking consumers directly, the brand can find its true prospects and anti-target those who prefer thin-crust pizza.

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When brands layer self-declared consumer data into both proprietary data and purchased audience segments, they improve the qualified reach of branding campaigns and the performance of direct response campaigns.

Self-declared data is on the rise, and adtech vendors are continually sharpening their capabilities and user interfaces to capture this information in a way that entertains consumers and keeps them coming back for more. This type of new data allows for more accurate targeting, customization of creative and increased ROI.  

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