Digital ad buyers know the ins and outs of audience-based buying better than anyone. Many have been masters of programmatic ad buying for more than a decade.

Let’s face it -- buying data can be a risky proposition. Here are several reasons to never blindly trust anyone offering the best data set on the web.

1. It costs you money to see whether it might work. Many buyers say the only way they can really evaluate the efficacy of a particular data set is to use it in an actual ad campaign. At the risk of stating the obvious, it’s less than ideal to do research on your client’s dime.
2. You may have already bought this data. This is more common than you think. An agency will work with one data broker, hire another, and realize mid-campaign that they are sourcing data from the same sets of in-market hair-product shoppers. That’s not only wasteful, it’s annoying to consumers.
3. Evaluating data yourself is cumbersome. It’s true that an individual agency or marketer can opt to conduct a firsthand analysis of data from a third party --  if they are willing to schedule multiple calls between their data scientists and that company’s product teams, able to steal some of their privacy and legal team’s precious time to weigh in on compliance processes, and more. This is hardly efficient in a business that is often all about speed.
4. You can’t compare data sets effectively. When it comes to the murky data-broker world, too often marketers can’t do basic things like compare reach, database size and even costs with other data companies. This puts third-party data at odds with how the majority of media is gauged and valued.
5. The data itself isn’t all there. For example, ad buyers can’t always get a grasp on how much of the data they may potentially purchase for a client is directly connected versus projected or estimated. Do you actually have data on 4 million moms with minivans. Or is it really a thousand moms, and you’ve extrapolated the rest? Again, lookalikes have a place in this industry as long as that’s what you thought you were buying for your client.
6. There is no mechanism to hold the data provider accountable. At the end of the day, without a standard set of criteria that all providers are evaluated against, there is no way for you to know whether there is something that you have missed in your evaluation. There is also no way to guarantee that they have shared all of the details with you and that those details accurately reflect what they are doing.
7. You could land yourself in hot water with consumers -- or perhaps worse -- the regulatory bodies. Can you be sure that the data provider you’re working with has received all the necessary consumer consent when obtaining the data they are selling? Or that they even know the answer to that question. In the current climate, including CCPA and growing consumer pushback on tech companies collecting their information -- any type of data consent mistake can be not just painful but damaging to a brand’s bottom line.
8. You are playing games with your most valued asset -- consumer trust. This is really the most dangerous data game a brand can play -- taking liberties or unnecessary risks with data to target potential customers -- and instead ticking off their biggest loyalists. Trust takes a long time to build. It can be lost quickly, and trying to rebuild it may not be realistic.

We all laughed at "Elf" when the lead character got sucked in by a diner promising the "world’s best cup of coffee," but when it comes to data, the results won’t be funny if we believe "best data" claims without a verification process.