The Attention Inc. Model | Audience | Content | Market Strategy

AUDIENCE

Sometimes good shows fail to connect with their target demographic. Knowing your audience is key to both the creative process and the marketing and distribution of your product.

"People are different all over the world, yet people are the same the world over. Attention Inc. attempts to bridge that anomaly." (Zak Shaikh, Managing Director, Attention Inc.)

Our studies show that originality and familiarity are two key components to successful drama. However, these two factors can pull in opposite directions. What is the appropriate balance? It depends on your audience. For instance, older viewers tend to appreciate familiarity while younger viewers respond more to originality. But an over-reliance on originality causes the brain difficulty in connecting to the material.


Risk-management can avoid thisThe kinds of audience analyses we do range from simple reports on Nielsen (or the relevant country) data to complex applications of algorithms and psychology techniques. We can provide insights into the aspects of a particular show that provoke reactions from different demographics. The analysis of a hit sitcom about a group of New England forty-something real estate agents may highlight an unsatisfied demand for shows set in New England among 18-49 year olds. Alternatively, it may be the fact that the characters are uneducated forty-year-olds which attracts that demographic. Either way this type of information is useful in figuring out both schedules and new shows to develop. In this type of analysis, we use our Preference™ System, which analyzes audience data and discovers elements to programming where there is extreme demand.

Our Attention® algorithm highlights those points in a particular episode that attracted a high attention level from the audience, and those that caused viewers to switch channels. The interpretation of these results points to moments in the story that were successful, and moments that failed.

This type of analysis can help decisions regarding:

• The network’s schedule
• Understanding the reliability of Focus Groups
• Developing or Editing pilot shows
• Marketing the Shows
• Advancing recommendation systems (e.g. a TV version of Amazon.com’s recommendation service)
• Maximizing the demand of different demographics