How audience profiling

How audience profiling, based on real-time online customer interactions, reveals the faces in the crowd

Today’s scattergun approach to targeting, based on wide demographic assumptions, overlooks an important fact for marketers: Target audiences are made up of real people.

Getting to know customers and prospects on a personal level is the only way marketers can truly understand what will be relevant to them, what they want and need and what will motivate them to buy.

While brands have access to a wealth of first-party data that can help them understand who their customers are and what interests they have, many are overwhelmed by the sheer volume of information available and don’t know where to start or have access to the correct technology and capabilities.

But help is at hand. With the arrival of cognitive technologies and machine learning, it’s now possible to create advanced audience profiles based on the “propensity to interact” (click or buy) with the brand message. This allows marketers to make the most of valuable online first-party data and finally reveal the faces in the crowd.

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So how does advanced audience profiling work, and what benefits does it bring to marketers?

Audience profiles are built up using the amalgamation of multiple data streams, including demographic data, psychographic data and behavioral analysis based on previous interactions, such as online media consumption and online browsing interests. It uses advanced technologies such as semantic analysis and natural language processing — a type of cognitive technology that analyzes the content a user consumes to determine real interests, the sentiment, emotional context and grammatical nuances contained within it — to get to know the consumer at a more granular level.

The benefits of audience profiling for marketers are vast, and it can enable them to achieve the following:

By combining a variety of data streams, in-depth audience profiling can provide a far greater level of insight than demographics alone.



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