To examine genre preferences and whether they change over time, we selected three programs that aired in the spring and are now continuing in the fall: Desperate Housewives (ABC), Ghost Whisperer (CBS), and Heroes (NBC).  We then created two bubble charts for each program.  The chart on the left is based on April/May viewing habits, while the one on the right is based on September/October viewing habits.

The charts on the left look extremely similar to the charts on the right.  Most audiences had the same proclivity to the show in the spring as they do now in the fall.  Core audiences (upper-right quadrant) are mainly constant.

 Correlation in these charts is high, as we would expect.  Both Relative Segment Reach and Attentiveness tend to be similar by genre segment for spring episodes and fall episodes of the respective shows.  The table below illustrates these high correlations:

Finally, the two charts below plot Segment Reach and then Attentiveness for spring and fall, with each point representing a genre segment.  All six trendlines are at around a 45 degree angle, further indicating the high correlations.

 Further analysis could recreate this exercise for a larger quantity of programs.

Approaching loyalty through our personal television watching experience, we start with the programs to which we are loyal, the programs we eagerly await each week.  In light of our attitude toward those programs, we can’t help think that everybody that watches our programs is like us, that our programs’ audiences are as devoted as we are.

Extending to other programs, we think that all programs have a similarly loyal audience.  All these other programs that we’re not watching, they have their loyal audiences.  Other viewers are making dates to watch these programs and are eagerly awaiting their start times.

Dominant promotional strategy bolsters this perspective on television viewing.  Networks focus their marketing efforts on their loyal “core” audience – typically a demographic.  By concentrating their promotional arsenal in their own programming, networks endeavor to extend their core audience’s viewing to the next program.  If network’s loyal core audience is consistent and large, then the standard promotional strategy makes sense.

It turns out that we’re wrong.

Program loyalty is the exception, not the rule.  Only a minority of a program’s viewers is faithful and watches every installment.  Most of any program’s audience is just passing through.  They tune in to a program once or twice in the course of a season, and then go their merry way.  We touched on this subject in a previous post on primetime loyalty, and further analyses of individual programs have reinforced the pattern.

And if we hadn’t been looking at set top box-level viewing data, if we had analyzed per-program demographic composition in time series, we never would detected the sizeable churn in program episode viewing from week to week.  Looking at panel-based data, we would have seen the same or similarly demographically composed audience tuning in to each episode and failed to see that the larger part of a program’s ratings is attributable to transient viewers.

This makes more sense as we go beyond how we feel about our favorite programs and think through the implications of broader trends in television watching.  The fact is that we watch a lot of television.  The latest installment of Nielsen’s Three Screen Report has the average U.S. viewer watching a 151 hours of television in the home each month.  While we, personally, may watch less than the average, we recognize that we don’t dedicate all our viewing hours to programming to which we’re loyal.  We spend time surfing, sampling, and checking (and re-checking) programs we’ve heard about from friends and seen promoted.  In aggregate, our time on the hunt adds up and, from the perspective of ratings, accounts for a majority of attention to programming.

Our emotional approach to program loyalty now tempered by intellect and data, we can work though what this means for improving program promotion.  Immediately, we recognize that enticing one-time program viewers to commit another episode represents a significant ratings opportunity.  If we can find the one-time viewers that are receptive to watching again – whose attention is “for sale” – we can devise an effective promotion strategy.

At Simulmedia, we like to say “we have a segment for that”.

The fact that a program’s audience demonstrates observable differences in loyalty and in attentiveness (the volume of program minutes viewed) implies a program-specific segmentation.  We conceptualize the segmentation in the Loyalty-Attentiveness Matrix below.

a conceptual segmentation framework

This Loyalty-Attentiveness segmentation is unique for each program and independent of the Genre Segmentation we introduced last week.  Where we crafted the Genre Segmentation to explore notions of audience preference and their impact on what people watch, the Loyalty-Attentiveness Segmentation explores how people watch.

We find viewers tuning in to different numbers of a program season’s episodes.  In the matrix, the segments tuning in to more episodes find themselves in the right quadrants.  Collectively, these are the “Rooted” audience having demonstrated loyalty to the program.  The segments tuning in to fewer episode are placed in the left two quadrants.  These are “Rovers”, demonstrating less loyalty.

We also find viewers watching different volumes of program minutes.  In the matrix, the segments watching more minutes find themselves in the top two quadrants; segments watching less, in the lower two.

The Rovers with high attentiveness should be the focus of program promotion (the red box in the Matrix).  Though relatively less loyal, these are the viewers who have sampled the program with relative vigor.  Their higher degree of attentiveness to the program is a signal of their preferences.  Exposed to more program promotions, they may be more likely to return to the program for more episodes, helping the program’s ratings as they do so.

Darwin postulated that competition for limited food resources led to the single finch population on the island to diverge into 13 different species. Each species adapted to specialize on a different food source – resulting in the evolution of different beak shapes that we see today.

At Simulmedia, we think that TV networks face similar pressures as they compete for a share of increasingly scarce audience attention.  These pressures force networks to focus on attracting specific audiences.

We tested our hypothesis by adapting the Audience Attentiveness framework we introduced in an earlier post.  To recap, the Y-axis represents Attentiveness, measured as the average network minutes viewed during primetime per viewer, the X-axis represents the Relative Segment Reach which is the percentage of audience segment viewing primetime on that network, and the area of the bubbles represents the number of total network primetime viewers within each segment.

We predicted that broadcast networks should have programming that caters to a wide variety of audiences – intuitively, the only way they could maintain their large reach.  As a result broadcast networks should have audiences distributed across all four quadrants of the Simulmedia Attentiveness chart.

Cable networks, like the finches, should show signs of specialization.  We should see a small cluster of audiences with high attentiveness and high reach in the upper-right quadrant with the rest of the audiences clustering towards the center.  Data was extracted for February 2009 by applying Simulmedia Audience Segments© on the TNS InfosysTV system.

As predicted, the cable networks we sampled displayed various degrees of specialization (see charts below). Their charts showed a cluster of audiences separate from the others in the top-right quadrant.  ESPN, as expected, with its exclusive focus on sports tends to be an extreme case of specialization as seen by the Basketball Fans.

Spike, although not as extreme as ESPN, tends to have relatively higher segment reach and attentiveness into the Remote Detective audiences; whereas for Discovery the core audiences are TV Naturalists and Reality Watchers.

Among the broadcast networks, while audiences interacted with NBC as predicted – relatively equal distribution across the four quadrants – CBS and ABC had remarkably different patterns. CBS and to a lesser extent ABC’s audiences aligned themselves almost perfectly in a straight line.

We think this indicates that CBS and ABC have adopted an audience acquisition strategy focused on niche audiences.  Their attentiveness charts look somewhere between a traditional broadcast network and a cable network.  This slight tilt towards specialization seems to have worked as both have beat NBC (when one excludes the Super Bowl) in the ratings game.

In conclusion, we think that TV Networks are adopting a range of audience acquisition strategies.  Cable networks continue to specialize on small niche audiences. Some such as ESPN are hyper-specialized focusing exclusively on sports audiences, whereas Discovery and Spike Cable networks show a lesser degree of specialization.  Surprisingly, broadcast networks are also showing signs of specialization as illustrated by CBS and ABC; however others such as NBC continue to execute on the traditional model.

As for the finches, they continue to evolve 150 years after their discovery by Darwin. National Geographic reports that “Since the arrival of the Large Ground Finch in 1982 on the island of Daphne the Medium Ground Finch, a long-time Daphne resident has evolved to have a smaller beak-apparently as a result of direct competition with the larger bird for food.”

Thoughts welcome….

*Thanks to Jeff Storan and Stewart Hauser for their help with the data visualizations.