Identifying Audience Channel

The dramatic fragmentation of viewing channels has frustrated marketers by increasing the difficulty of reaching the desired audience with the desired message. Amongst a variety of use cases for marketers, simMachines’ Dynamic Predictive Segmentation provides a highly accurate way for marketers to identify the proper channel to reach their intended audience, broken down to as granular a level as needed. For this demonstration we’ve trained a classifier to identify the media venue used by likely purchasers of a product, and then produced clusters around those classifications. Customers are classified as having Cable TV, Satellite TV, or Streaming Only. The result is highly accurate predictive clusters that not only identifies the medium through which these customers could be contacted, but further breaks down the audience into subsegments based on the shared characteristics of those individuals, allowing the creative delivered to be highly tailored towards the individuals being targeted, maximizing the effectiveness of marketing efforts. Let’s take a dive into the clusters.

Data Overview

Let’s take a look at the largest streaming cluster:

We see that this cluster consists of households with younger households (in their early 20) who are single, have a low net worth, no bank card, and do not shop over the phone or by mail.

Let’s compare this to households who have a Cable TV subscription:

This group consists of veteran grandparents with moderate net wealth, who use a DVR, invest in stock, are interested in technology and the outdoors, and are heavy TV watchers.

Finally, let’s look at a cluster of Satellite TV subscribers:

This is a moderately sized cluster consisting of older, wealthy households, who invest, shop online, collect sports memorabilia, and who may have younger individuals living in the house as well.

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