Out of all the demographic attributes we analyze and score, geographic attributes (e.g., State, Census region, and Census division) tend to be the most consistently accurate. These attributes consistently have average Truthscores™ of .85-.95. In contrast, the average Truthscore for other attributes can be much lower.
Every quarter we run our accuracy scoring, calculating Truthscores for over a dozen demographic attributes (e.g., age, gender, ethnicity, race, household income, presence of children, geography, educational attainment, etc.). The result is over 850 million distinct Truthscore-d consumer records.
It seems logical that higher populated states would be highest in accuracy and the less populated, less accurate, because more data, more accuracy. But, digging a little deeper, the accuracy is not strictly linear. Louisiana and Wisconsin both rank pretty low in terms of population, 7 and 5 respectively, (with California being the most populous at number 52) but are nicely in the middle of the pack Truthscore-wise, at 27 for Louisiana and 32 for Wisconsin. Conversely, Arizona, population 7.3m and a ranking of 37, has a Truthscore rank of 38, and Florida, with a population rank of 31, has a Truthscore rank of 49!
There are a few reasons why geographic attributes perform so well in accuracy scoring. For one, many data partners build the initial backbone for their full consumer file (to which other PII and demographic information is later associated) on the physical address, either at zip code level or residency. In addition, there are numerous, credible public sources of residence information about specific consumers. For example, information about home purchases and mortgage applications is in the public record. Therefore, data providers have many reputable, external sources of geographic information about individual consumers that they can use to either validate their own geographic data or inform their own models.
While geography data is generally good-- and for the above reasons, perhaps unsurprisingly -- data for all states isn’t created equal. There is significant variation in data accuracy (according to average Truthscores) from state to state and provider to provider, and Truthscores can be as low as .7 for some providers. That’s a lot of wasted spend on audiences outside of your desired locality.
So how do you avoid spending money on those inaccurate records? It’s simple! The easiest way to improve your targeting is to use Truthset Scored segments, available wherever you buy 3rd party segments, like LiveRamp Data Marketplace, Adobe’s AAM, Lotame, The Trade Desk, Xandr, AdSquare, Salesforce/Krux, etc.
Truthset Scored segments only include the records that meet a threshold for accuracy, meaning we’ve removed the IDs least likely to be the purported attribute of the segment, in this example, location. This leaves only the more validated IDs for advertisers to run their impressions against.
If you have any questions about how you can improve the ROI of your marketing with independently validated audience segments, contact us.