Don’t assume that all data is created equal in terms of quality and accuracy. Here are some ways to evaluate data quality:
Many buyers lump together data from various providers in order to increase scale. While the campaign setup becomes easy and efficient, learning about performance by segment becomes difficult. This means you can see overall performance, but you might not learn how each segment or data provider performs.
Modeled data is not bad data – as long as the provider models an outcome instead of an attribute. Most marketers drive a specific outcome: purchase, registration, a political donation, and so forth. A good model will use the desired outcome as a seed and will help you find other users who match the seed users’ characteristics across multiple dimensions. Even branding campaigns should reach users who are similar to your best customers.
Sophisticated modelers combine hundreds of profile signals to create complex custom multi-faceted models, which can successfully predict users’ propensity to convert. It’s simply more sophisticated than a person running an Excel model. Modeled data may get a bad rap, but machine learning can be very effective at determining ideal targets.
*Disclaimer: The above are suggested best practices to be used with discretion. Online behavioral advertising should follow all applicable Digital Advertising Alliance self-regulatory principles, including all opt-out requirements.
As a best practice, ask your data providers whether their data collection practices are compliant with all applicable data privacy laws and regulations.
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