Audience Cartography 101: Anatomy of a Data Source

YP Audience Cartography, Audience Cartography, data, big data, data source, user profiles, audience segments, insights
Aug
10
2016

As you probably already know, we launched YP℠ Audience Cartography a couple of weeks ago to help national brands not only better understand what drives local consumers to make purchase decisions, but also to help them target, reach, engage, and convert their audiences with more granularity and precision than ever before. Our process and methodology use data-driven insights, from multiple high-quality data sources, to uncover unique consumer behaviors and pinpoint key action drivers as consumers move along their journey from search to consideration to purchase.

Now that you’ve had this quick refresher about what Audience Cartography is all about (albeit, at a very high level), the first question that likely pops into your head is this: how does YP do it? So starting today and rolling out over the next few weeks, we’re going to take a closer look at what makes Audience Cartography tick, why it’s such a unique offering, and how it can help national brands with a local footprint engage local consumers like never before.

So let’s start with what sits at the very core of our Audience Cartography platform: data.

As marketers, we understand the value of data-driven insights. We also know that there’s a lot of data – probably more than we can even wrap our head’s around – available to us on a daily basis. Though, here’s a slight hitch: not all data is created equally. But we do know that the strength of a marketer’s campaign is built upon the accuracy, relevance, and scale of data – precisely why we only sift through high-quality data sources to help amplify our understanding of consumer behaviors today. That’s what sets Audience Cartography apart.

We start this process by examining our very own proprietary search intent data. This is information that only YP has access to, as it’s tied directly to the interactions consumers have with the YP℠ app, the yp.com website, and our 500,000+ business listings.

That alone provides us with a wealth of insights to both better understand consumer behavior and help predict future behavior. After all, why look to outdated or inaccurate third-party sources – in an attempt to target potential customers – when we have an up-to-date, continually refreshed and unique database of active in-market consumers searching for a myriad of products and services? (Not to mention, we also have a wealth of historical knowledge built upon our very own user experiences!)

But our journey through data doesn’t end there. We look at mobile location data, age/income census data, behavioral data (in all forms), campaign interaction data, store visit data, and what seems to be an endless supply of high-quality data sources to help national brands start painting a much clearer picture of their local consumers.

By now you’re probably thinking to yourself: you’ve got all this great data to work with, but what are you doing with it? Fortunately, that’s an easy (and interesting) answer.

We layer it all on top of each other to understand how different bits of location, behavioral, and demographic data can come together to tell a more robust story about consumer behavior – much more, in fact, than by simply extracting insights from one data source at a time. And we do this for two very specific reasons: first, it helps us build specific user profiles (based on unique device ID’s) and then, second, taking that user profile information to group users into audience segments (based on similar behaviors, interests, search intent, and so on). This is precisely how we make data work much harder for national brands with a local footprint.

The Audience Cartography process doesn’t end there, but we’ll dig into what comes next soon. If you’re dying to learn more right this very minute, feel free to download the YP Audience Cartography eBook today – but then be sure to check back here for the next blog post in this series, “Audience Cartography 102: Converting Data to Knowledge.”

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