Data algorithms. They’ve leapt into notoriety over the past decade with curious stories about unexpected data correlations. Through data mining Wal-Mart discovered a bizarre correlation between diaper and beer sales. Inside Sales uncovered that sale cycles eerily coordinated with lunar cycles. As the volume of data and data providers have proliferated the marketplace, our industry has become fascinated by the promise of data’s application, though we’ve still struggled to connect a fragmented landscape into an actionable marketing tool.
There’s an undeniable lure to first-party data because it’s a cache of your established, valuable customers who already buy your products and services. It’s extremely relevant and powerful for marketing to current customers—those whom you already know something about—through loyalty, retargeting and lapsed lead campaigns.
But over the past few years, Facebook’s lookalike targeting has helped the industry set its sights on first-party data as a means to perform prospecting, branding and other forms of acquisition marketing—targeting unknown consumers who you know nothing, or very little about. Others, including Google, Pinterest and Twitter, have also followed suit, working to expand the potential of first-party data.
First-Party Data Politics
Because of its exclusive ownership, first-party data is often perceived as superior in quality, reliable and accurate, which is why its often wholeheartedly trusted by brands. However, its weakness is that it’s only comprised of what Donald Rumsfeld might call “known knowns”: insights (limited) you have about the people you know already.
But if you want to find the “unknowns”, then you must enter the realm of third-party data, which is admittedly a realm that can be a difficult to navigate.
Third-party data can be aggregated from online and offline outside sources, which provide more insight into the unknowns. For example, some companies pay publishers to access information about readers via online behavioral data like cookies. By examining cookie data, you get a sense of a user’s web activity and, by proxy, interests. Such data has its limits though. “Using cookies to drive online advertising is like using a chainsaw to do brain surgery, it will not keep you healthy, but will do the job” said Scott Howe, CEO of Acxiom said.
There’s a big difference between what one’s online behaviors suggest and what offline realities divulge. And the good news is, offline data bridges that gap. Financial health, census data, auto ownership, political party registration, purchase history and combinations of these offline data sets put online behavior in proper context, offering a more complete version of the consumer’s real likelihood of purchasing.
Even with a comprehensive understanding of the stark differences between different varieties of data, first- and third-party data still should not be thought of in isolation.
When first- and third-party data are used collaboratively, marketers can unlock insights about existing customers, reach valuable unknown prospects, develop compelling creative and reach those consumers efficiently across every channel and device.
Finding New Ideal CustomersTo expand the value of first-party data for your brand, and advantageously act on third-party data’s compilation of comprehensive data sets, start by creating a predictive model of your ideal consumer—the one that is most likely to consider, and to convert. The good news is that you probably have a list of your ideal consumers, based on their past purchase behavior. Through deep analysis of the profile characteristics of these customers, this list becomes the seed for creating the model.
This analysis also reveals new insights about your customers that can be used to develop your established understanding of who your existing customer is—what’s she interested in, what she does for a living, her financial health and more—to help elevate your personas and create impactful messaging.
But third-party data, empowered by a model, goes beyond existing customers; it establishes an audience of valuable consumers to target. Third-party data unleashes the model’s ability to discover audiences of consumers who you haven’t been able to reach before. When thought of this way, third-party data is about so much more than just “buying audiences”. It’s about understanding the audience you are really looking for in the first place.
A Fragmented Landscape
This sounds simple, and it can be. What’s complicated is the fragmented landscape of data that’s out there today. We’ve seen a proliferation of data and data technology providers. It’s all great for the marketing industry, but only to the extent that it leads to great results for the marketer.
To achieve real success, marketers and vendors alike need to think differently about data. First-party data is great for understanding the characteristics of a customer base. But third-party data is critical to fill in the missing pieces of first-party data, helping brands prospect for new customers at scale. The two data sources are naturally complimentary when integrated through technology that centralizes the critical steps of activation: data mining, algorithmic data analysis and the application of data correlations in an actionable way: building and activating highly accurate, scalable audiences across every channel and device.