Tie Attribute Loyalty to Variety Seeking

A study done more than fifteen years ago recommended that movie sequels be named, not numbered. Analyzing movie titles in IMDB, the UCLA and University of Pennsylvania researchers saw how sequels carrying names did better at the box office and drew interest for a longer time. We’d expect “Die Another Day” to earn more than “James Bond 21.” Numbered sequels were perceived by participants in their studies to be too similar to the original.
     After that research, “The Fast & Furious” franchise came along. Using variations of the same name in successive movie titles seems to have paid off just fine. “Fast & Furious 6,” “The Fate of the Furious,” “F9.” The right answer seems to be that if you want entertainment to attract audiences, blend the familiar elements which have earned loyalty in the past with novel elements which satisfy variety seeking. This is the formula attended to by researchers at The University of North Carolina at Charlotte and California State University-Long Beach in predicting how financially successful a movie will be.
     Because studio movie production costs are extraordinarily high, the researchers aimed for an analysis model which could be used before a script is greenlit—approved for financial backing—in the language of the industry. With this in mind, they based their methodology on a computerized analysis of the text in the movie script. One tool for this was the Linguistic Inquiry and Word Count dictionary, which covers grammatical and social psychological factors and has been widely employed for content analyses of text.
     Comparison was with the text of scripts for past movies. Also conducted was a textual analysis of consumer reviews of past movies. The researchers’ objective was to identify which content attributes should stay the same as in previous movies proven attractive to a similar audience and which attributes should be different.
     The resulting model’s predictive power was greater than that for comparable benchmark models from the literature. The impact of the study, though, has less to do with the specific attributes identified than with the approach to prediction. The statistical assumptions and methods used in the research were highly sophisticated. The conclusions were limited to predicting the success of movie scripts. Application to books, stage plays, and maybe even advertising campaigns might work. Beyond that, maybe not so well. But the general lesson applies broadly: For maximum attraction, realize that attribute loyalty is tempered by variety seeking.

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