A tremendous amount of money is spent on data for media buying decisions, specifically third-party audience data. Third-party data can come from many different sources, and multiple methodologies can be used in its collection, structuring, and marketing. This often makes it difficult for advertisers to understand exactly what they’re buying, leaving advertisers at a disadvantage and at risk of purchasing data that’s unsuitable for their purpose. To address this problem, advertisers need to evaluate the quality of a dataset before purchasing it. This paper recommends five criteria to focus on when evaluating data:
- Data Accuracy: Does the data actually mean what I think it does, e.g., are visitors to an auto website actually more likely to buy cars?
- Data Precision: Are the data collection and modeling procedures sufficiently precise to avoid a large number of false positives, e.g., does the vendor use a lookalike model that assigns people to the audience who shouldn’t actually be included?
- Data Recency: How regularly is the data refreshed? When was it last refreshed?
- Data Coverage: Does the dataset cover enough of my intended campaign audience to provide necessary scale for my client’s campaign?
- Data Deployability: Can I use the data with my chosen tech partners?
A checklist is also provided for advertisers to use when considering a new data partner.
This is an initiative from the Trust Consortium, which was launched by the ANA in 2019 in partnership with Reed Smith, the ANA’s outside legal counsel. The Consortium’s mission is to restore trust in the marketing ecosystem through transparency, integrity, and growth.
“Data Sources for Media: A Buyer’s Guide.” ANA, 2020.