The Bartender’s Guide To Blending Better Mobile Audiences

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dansilver“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Dan Silver, director of marketing at xAd.

Two parts first-party data, a splash of third-party segmentation, garnished with a slice of real-time consumer behavior. If only building mobile audiences were as easy as mixing your favorite cocktail.

There is a recipe, however, and it’s not as guarded as Coca-Cola’s secret formula. The recipe for an accurate mobile audience starts with location data. Understanding this essential ingredient, along with its components, will allow you to better evaluate its potency.

Step 1: Base Ingredients (Location Data)

Awareness of the forms of location data that are available is the first step to building more accurate mobile audiences. To understand how location is an indicator of audience, the place to start is with the consumer. We have a home (hopefully), we have a job (in most cases) and we have our leisure time (again, hopefully). So there is our mixture – home, work and everywhere else.  Now, what types of data are tied to these locations?

POI: In mobile location-based advertising, it all starts with points of interest (POI). The foundation of mobile location intelligence begins with a comprehensive and accurate understanding of where businesses and landmarks are located. With POI data, we can start to use the “where you are and where you’ve been” formulas to determine what type of audiences is most likely found in a certain location. Retail locations, fast-food restaurants, gyms, airports, amusement parks and sports complexes, for example, all yield incredible amounts of information about audiences. With any of these POIs, the more granular you can get, the more intricate an audience can be built.

Retail, for example, can be broken down into luxury retail or sports apparel retail. Auto could be broken down into gas stations, car parts or dealerships. Dealerships could be further divided into imports, used or luxury dealers.

Subsets of POI data can be formed as well, like event-based data, which is typically more short-term and seasonal. Whatever the case, layering time and seasonality on top of POI data is always another critical tool.

Dwells: Since consumers spend about one-third of their waking day at home, accurately defining or reaching them there is another key component to mobile location-based targeting. There are a number of different data elements needed to get to the heart of audience definition at the home. One is simply demographics: What types of residences are in what locations? Is it urban or suburban? Does it skew low-income or high-income? Does it index highly for Hispanic audiences or another race? Is it a college town or an elderly community?

Once you know these demographic factors, it’s possible to overlay data that includes vehicle ownership, product preferences, television-viewing habits or even political affiliation. There are countless other data points that can be factored in as well, that, when considered together, help build an increasingly rich depiction of audiences at home.

Consumers also spend about one-third of their day in an office, so being able to understand where these businesses are and who is likely to work there is another fundamental key. Think about what we could determine about the type of consumer that works in a factory vs. a tech startup, or the consumer that works in a medical facility vs. one that works at a day-care center.

Step 2: Add Bitters And Garnish (Real-Time Data)

Most of the data sources mentioned previously are static, meaning the data generally does not change. But we can liven up our targeting by layering real-time data on top of the static data. This can be in the form of mobile search data, something easily tied back to location. Or it could be in the form of mobile social media data, another tool easily connected to location. Other sources, like dynamic weather data, can also be layered onto location to further help advertisers gain an added advantage to targeting accuracy.

Step 3: Mix And Serve (Audience Targeting)

Now that we know where audiences are and what data sources are available, it’s time to balance the data mixture. You might, for example, find business travelers at airports on weekdays and at business suite hotels during weeknights. They may be located at white-collar office buildings, large business conferences or events and in affluent communities that index highly for business television channels, such as CNBC or Bloomberg TV. They may be searching for hotels, airline flights or rental cars.

At a high level, these data points can be mixed together to provide a rich target pool for your audience. The creative and messaging can now be added and ads served.

People are constantly in motion, so being able to capture and layer the right data sources together is paramount to reaching these consumers at influential moments. We know consumers are at home, work and on the go. Cheers to reaching them in the right moment and serving the most relevant message possible.

Follow Dan Silver (@danjsilver), xAd Inc. (@xAdInc) and AdExchanger (@adexchanger) on Twitter.

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