Political preference predicts movie choice

Video content: https://www.youtube.com/watch?v=fggaqF6lLCo

What predicts whether a movie will become a box-office success or a flop? Movie theater operators desperately want to know, as they have to fill up the seats to make a profit. But in order to fill seats at cinemas, they have to show movies that people actually want to see. Assistant Professor Jason Roos of Rotterdam School of Management, Erasmus University (RSM) found out we can forecast a movie’s success by looking at the political preferences of our local audience.

Many people have tried to figure out how to predict which movies become box-office hits. On an international level, some people say ratings and reviews are solid indicators of a movie’s success. Other people base it on how many edits the movie gets on Wikipedia.

However, movie theatres don’t serve entire countries, they serve villages and neighbourhoods. From one village to another, movie preferences may very much vary. What the local population wants to see is what matters to local theatre operators. But how do you figure out what kind of movies appeal to your local audience?

Dr Jason Roos analysed box-office data from more than five years from 25 counties in the USA. He found that political preferences are a much better indicator of how a movie would perform in a local market, than traditional marketing variables such as age, income and level of education. Republican voters tend to prefer movies with female Caucasian actresses in the lead role, whereas democrats like movies with African American males in the lead role.

When we talk about movies in the press, we often use words such as action, thriller, comedy or drama to describe them. But according to Roos, these genres don’t tell us nearly enough about movies and don’t tell us about what really matters to consumers. Whereas the Internet Movie Database (IMDb) is going to list a movie as either a comedy or not a comedy, Roos has found that it is more important to consumers to consider whether a movie is for adults or for the whole family, or if it is emotionally intense or easy to watch.

Roos says that we can improve revenue forecasts in the movie industry if we do two things: think about movies in the same way as moviegoers, and use political data to better understand differences across local markets.

For this study, political preferences were utilised to understand what types of movies people want to see, but this data could be used to study consumer behaviour in all markets. It can be used to understand what type of cars people want to drive or what kind of clothes they want to wear. The possibilities are endless.

Rotterdam School of Management, Erasmus University (RSM) is one of Europe’s leading business schools, and ranked among the top three for research. RSM provides ground-breaking research and education furthering excellence in all aspects of management and is based in the international port city of Rotterdam – a vital nexus of business, logistics and trade. RSM’s primary focus is on developing business leaders with international careers who carry their innovative mindset into a sustainable future thanks to a first-class range of bachelor, master, MBA, PhD and executive programmes. RSM also has offices in Chengdu, China, and Taipei, Taiwan. www.rsm.nl

For more information on RSM or on this release, please contact Ramses Singeling, Media Officer for RSM, on +31 10 408 2028, or by e-mail at singeling@rsm.nl.

Read the entire RSM Discovery magazine article about Roos' research below:

Politics and perceptions in the demand for movies

By Jason Roos

Knowing which party a consumer votes for can potentially predict what kind of car they will drive, the brand of clothes they wear, and the name of the cologne on their bathroom shelf. It certainly predicts the kind of movie they will pay to see.

I read an article in "The Economist" ten years ago that said pornography sales in the United States “bore an eerie resemblance” to an electoral map*. That is to say, it is theoretically possible to predict which party a person would vote for by tracking their consumption of purchased pornography.

I discussed this idea with my co-author, Ron Shachar of IDC Herzliya, and we wondered if the reverse would also hold true. So many variables about people are used to predict election results, from basic demographics right down to how an individual uses Twitter.

So, what if we were to switch the regression equation around and see if election results could predict these variables? Namely, can you look at consumers’ voting decisions and use them to predict their purchasing decisions? As it turns out, you "can", at least with a certain kind of product. Our paper, "When Kerry met Sally: Politics and perceptions in the demand for movies", examines this correlation, revealing some interesting results for marketers.

We chose to look at movie sales rather than pornography or even blue jeans for two reasons. First is the practical importance of predicting whether a movie will be popular. The movie industry is very well-studied in the marketing literature because it's an industry where every product is unique. Predicting a movie's success is something like predicting the success of a completely new type of yoghurt, in which the flavour has never been used before, the consistency has never been used before, the packaging has never been used before, and so forth. Nobody really knows for sure whether the movie will be good until they go to see it. As making movies is neither cheap nor easy, a great deal of time and effort is spent trying to predict how well audiences will receive them.

The second reason is more psychological. We think movies have the potential to appeal to consumers’ self-images and aspirations. Unlike more functional products (think plastic spoons), movies call for emotional and intellectual engagement; they encourage a viewer to identify with – or in opposition to – the main selling points of the product (the characters within the story). This type of emotional engagement can be – and often is – engineered in the marketing of other products that appeal to a consumer’s sense of “who you want to be.” In this way, the idea of using electoral data to predict consumption can be extended to many more product categories.

Genre vs Perceived Attributes

While genres are routinely used to classify movies, this method can overlook important similarities between seemingly disparate films. What we call “perceived attributes” are the consumer’s own perceptions of a movie. These attributes are much more subtle than standard genres, particularly when factors like the ethnicity or gender of the lead actors are concerned. Many moviegoers will happily acknowledge that they like romantic comedies, but few will realise or acknowledge that they consistently choose young white female lead actors over African-American male leads. Even fewer will realise that these choices correlate closely with their political preferences.

Compared to the list of genres that typically describe movies, perceived attributes should be more meaningful to marketers, because they are measured directly based on the movies consumers choose to watch. Genres, on the other hand, are defined in a top-down fashion by reviewers. The usefulness of perceived attributes (when compared with the genre system) in grouping movies and predicting their fit with consumers is so pronounced that we were able to show a US$93 million improvement in yearly revenue forecasting in the United States film industry "before" we even factored in the political data.

Perceived attributes group films in ways that would be impossible under the standard genre system. And it wasn’t until we laid out the groupings in visual form that the striking nature of these similarities became apparent. For example, although the films "Crouching Tiger, Hidden Dragon" and "Ocean’s Eleven" would be classified into very different genres (action/drama/romance vs. crime/thriller), consumers perceived them to be quite similar.

Over the course of our study of movie sales, six significant latent attributes became apparent, as did their correlation with consumers’ voting preferences.

For instance, in markets where votes favour the Democratic Party in congressional races, voters prefer movies with African-American male leads. At first glance, one might expect this to be due to the popularity of the Democratic Party among African-American voters, but the numbers stayed true even after we adjusted for a large number of demographic variables. Congressional Democrat voters like to see movies with African-American male leads and congressional Republican voters prefer movies starring young white women. It’s that simple.

Because the identified attributes come out of the collected data (rather than pre-defining categories and trying to make the product fit into one of these categories), it is conceivable that this approach can be adapted to other products that also appeal to consumers’ self-images. The attributes will obviously be different for each product category, but the principle should remain the same.

Real world applications

Our paper uncovered two separate findings. The first relates to the relationship between electoral results and movie sales. The second is the use of perceived attributes in predicting the success of a movie. Each of these is useful in their own right and when combined create a highly accurate model of consumer behaviour.

Unlike census data, electoral results are “refreshed” every couple of years. Not only do these data give an updated map of political views that can be used to predict the sale of a certain kind of product, they have the added benefit of giving a more accurate reflection of the changing demographics within a geographical region. These data are an untapped marketing resource.

The method we used to predict movie sales is applicable not only to two-party systems like the one used in the United States. In fact, it is fair to expect that the information gathered within a multi-party system would be even more detailed, and therefore more useful. Let’s say we live in a world that has only two soft drinks - Coke and Pepsi. If all I know about you is which of these drinks you prefer I might accurately predict if you like potato chips. But in a world with Coke, Pepsi, and 7-Up, I might do even better, perhaps even predicting which brand of potato chips you like.

Perceived attributes go beyond typical product classifications. In this paper, we believe we have tapped into something fundamental about what people see in movies. Extrapolated to other settings, this approach might reveal fascinating associations across seemingly unrelated product categories. By looking back at sales of past products and lines and applying a model of perceived attributes to explain their failure or success, we could conceivably provide a foundation of knowledge that increases future sales and directly influences product development.

  • This article draws its inspiration from the paper "When Kerry met Sally: Politics and perceptions in the demand for movies", written by Jason M.T. Roos and Ron Shachar and forthcoming in the journal Management Science. http://ssrn.com/abstract=2395746
  • Jason Roos is Assistant Professor, Department of Marketing Management, Rotterdam School of Management, Erasmus University. Email: jroos@rsm.nl
  • This article was published in RSM Discovery Magazine 18. More information about and back copies of RSM Discovery Magazine can be found here.
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