• by Mike Peralta , Op-Ed Contributor, August 19, 2014

Every brand, agency and vendor involved in marketing is talking about data, but the uncomfortable truth is that a lot of people are bragging to save face. Like high school hallway gossip, everyone is talking, everyone thinks others are doing exciting things with big data, but the truth is that most people in the industry are still trying to figure it all out. Many lack even a basic understanding of this data, much less the terms used to describe it.

The thing about data is that it really comes down to how it’s used, not how much you have. To get a better understanding of the truth behind big data, let’s quickly define the three kinds generally discussed in online marketing.

First-party data: Data collected, created and owned directly by publishers, retailers and other companies, based on their site visitors and/or actual customers. This data can inform marketing activities and facilitate communication with these customers.

Second-party data: Used like first-party data, second-party data comes from a partnership with an external party, often a publisher. That external party is the direct source of the information and signs over the rights to the data to the advertiser using it. Advertisers can pay for this data, but it is often shared on a quid pro quo basis.

Third-party data: Data obtained under license from a third, external party, usually an organization that can assist with building segments and finding audiences online. Third-party data may come from behavioral data companies, shopper data companies, offline data warehouses, or financial data brokers, and is commonly used to prospect new consumers.

The next big misconception about advertising data is that amassing tons of it will make a brand smarter than the competition. The truth about data is that it’s only valuable if you can get information out of it. It’s called “big data,” but in reality lots of small insights are what help target campaigns with more precision.

Advertisers must make the most out of what they already have: the first- and second-party data. Fortune 100 brands often have online profiles created by their customers, or offline data from loyalty cards and frequent-buyer programs. That’s extremely helpful for reaching customers who have brand awareness and are very likely to purchase the same product again.

This kind of targeting can be strengthened with the addition of second-party data from a trusted publisher. Sites like Yahoo, MSN, and major newspapers know who visits their sites and what kinds of content they consume. Slicing these data sources in different ways provides a great deal of insight while remaining cost-effective for advertisers.

But first- and second-party data, while affordable and effective, carry limitations. For one, advertisers are only targeting consumers who already visit their site or buy their products, meaning these consumers are likely to buy the same brand again. Not even the biggest advertisers in the world have 100% coverage of every online consumer, and they certainly don’t have the same detailed profiles for each and every customer.

Here’s an example: a brand may know who buys their product based on an anonymous or pseudonymous online profile the consumer created. But the brand doesn’t know much about the consumer’s interests, behaviors, household size, or estimated income. Third parties can infer some of that information, in a privacy-safe way without any personally identifiable information. 

Third-party data expands the reach and is often used in combination with other sources to introduce campaigns to new customers: Lookalike modeling is based on first-party data, but identifies new prospects. Third-party data partnerships should always benefit the overall data pool, by adding scale and depth of understanding to the available first-party data.

Once armed with data, deciding which sources to use and how to leverage them comes down to each individual campaign and its desired outcome. A shampoo advertiser wants to reach people with hair, so it can waste impressions on the few consumers who don’t have any. But an auto advertiser is trying to reach consumers on a longer purchase cycle. That requires refined targeting, knowing not just that a consumer is interested, but when they are interested.

Study campaign results, look at the money allocated to data, and ensure there are clear benefits. Transparency into data cost is a major help here, as it allows brands to see if their investment is worth the return. Advertisers and their agencies will need to keep adjusting the data to find the right mix, but the more they study, the better they’ll perform.  With a little effort, advertisers can get much more out of data than they put into it. The focus shouldn’t be on acquiring data, but getting more from the data.