The Science of Defining A Target Audience

The Science of Defining A Target Audience

Consumer behavior is becoming more and more complex. But thanks to technology, defining and targeting an audience isn’t rocket science. Many small business owners may not privy to the advances that have been made over the years. While many may believe that some things remain the same, new trends in technology not only influence how consumers shop but also, how they are targeted.

For years, marketers have been using different methods to segment audiences. While the tactics and data may have changed over the years, the results are still the same.  Thanks to the digital era, savvy marketers are able to leverage that data and are able to define and target audiences even further thanks hyper-targeting.

What is Hyper-targeting?

Hyper-targeting is a technique advertisers use to deliver personalized messages to a very narrow audience across different advertising channels such as mobile, desktop, disconnected television and out-of-home advertising. By building targeted audiences, we are able to put your mobile display ads in front of the right people, in the right place at the right time.

Audience Segmentation

Data scientists study a plethora of data, ranging from geographic, demographic and psychographic to discover consumer patterns to gain insights.

Capturing data from website analytics, social media networks and other data such as geographic, marketers can not just discover the power hyper-targeted audiences.

What is Behavioral Segmentation?

Behavioral segmentation is the results of grouping customers based on their demographics, behavior, such as purchasing habits.  By analyzing different customers’ various needs, wants, and buying patterns marketers then group them together by their commonalities.

For example, suppose you were a dog food brand wanted to advertise to pet owners.  Now marketers can use technology to specifically infer consumers who are dog lovers versus cat owners.

By studying consumer behavior, we have the ability to develop specific strategies on how to reach them such as geo-framing.  By targeting geographic locations such locations as pet stores and veterinary clinics to capture unique mobile device IDs.

The problem is, technically, those consumers could be cat owners and our ad spend could be wasted on the wrong audience.  By adding dog parks to your geo-framing search, we now can find common mobile ID devices of all three categories and infer those that are common are most likely dog owners. By capturing these IDs, one can easily eliminate duplicate mobile IDs and assume those that appear every day are workers and not consumers.

The Importance of Relevancy

Today’s consumers are highly annoyed with generic advertising and want to be served content (and advertisements) that are relevant to them.

In a study published by Instapage, 80% of all consumers report they are more likely to buy from a brand that offers personalized experiences. In order to engage with your prospective customers in a meaningful way, we as marketers need to make sure that our ad campaigns are relevant to our targeted audience.

Sending advertisements for cat food to dog owners or consumers who don’t own any pets for that matter, is just wasted ad spend. By defining hyper-targeted audiences and understanding their behavior and intent, we have the ability to run ad campaigns that are based on a specific audience, regardless of the channel.

Interested in learning more?

We understand the challenges small businesses are facing. If you would like to learn more about shifting your marketing strategies to grow your marketshare and bottom line, let’s have a conversation.  Stay informed to receive our Marketing Matters White Paper Series and Newsletter.

WUNDERWORX provides the power of real-time compliant programmatic advertising across all devices and media, leveraging sophisticated geo-spatial audience building technology from our easy-to-use platform.  Let us demonstrate how programmatic, paid search and SEO can reduce wasted ad spend and time to conversion.

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