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Predicting Movie Attendance

Predicting Movie Attendance.

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Predicting Movie Attendance

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  1. Predicting Movie Attendance I tried to single out a few variables that I found in my research to be important to predicting movie attendance. I dedicated at least a slide to each referencing an article that either supports my case or that may be of use for more detailed research. I also included a few models that people have come up with to predict movie attendance. I hope information is useful.

  2. Possible variables in forecasting movie attendance: • Release date • Presence of top dramatic talent • The Motion Picture Association of America (MPAA) rating of a film • Genre • Country of Origin • Distributing Company • Production Budget • Promotion Efforts • Word of mouth advertising • Internet Presence • Critics Reviews • Hollywood Stock Exchange

  3. Release Date • Holiday weekends and during summer, more people have spare time to go to the movies • Another important thing to consider is simultaneous releases or releases of potential block busters in a short time period • A strong opening weekend is generally a strong determinant of total gross, because it is usually the peak of attendance (Chen, 3) • The opening weekend of a movie’s release typically accounts for 25% of the total domestic box office gross- but ignores number of screens for the first weekend of general release may influence the number- international or national release (Simonoff and Sparrow, 1)

  4. Presence of top dramatic talent (Star Power) • Important to look not only at actors, but also directors • Look at cast list of a film to see if actor(s) and director have been financially successful in the past using Top 25 Actors and Actresses from acclaimed entertainment channels or magazines as good source of data • A Harvard study shows that “the involvement of stars impacts movies’ expected theatrical movies, but not that it increases the valuation of film companies that release those movies” (Elberse, 1)

  5. Presence of top dramatic talent (Star Power) • Additional Literature • Albert, Steven. (1998) Movie Stars and the Distribution of Financially Successful Films in the Motion Picture Industry. Journal of Cultural Economics, 22, 249-270. • Wallace, W. T., A. Seigerman and Morris B. Holbrook (1993). The Role of Actors and Actresses in the Success of Films: How Much is a Movie Star Worth? Journal of Cultural Economics, 17 (1), 1-27. • Prag, J, and J. Casavant (1994). An Empirical Study of the Determinants of Revenues and Marketing Expenditure in the Motion Picture Industry. Journal of Cultural Economics, 18, 217-235. • Sochary, S. (1994). Predicting the Performance of Motion Pictures. Journal of Media Economics, 7 (4), 1-20. • Ravid, S. A. (1999). Information, Blockbusters, and Stars: A Study of the Film Industry. Journal of Business, 72 (4), 463-492.

  6. MPAA rating of a filmwww.mpaa.com • G (general audiences) • PG (parental guidance suggested) • PG-13 (possibly unsuitable for children less than 13 years of age) • R (children not admitted unless accompanied by an adult) • NC-17 (no one under 17 admitted) • U (unrated)

  7. MPAA rating of a film • Helps determinate target audience of a film- • G, PGs are usually targeted to children; children usually need to be “taken” to the movies by adults, making them a somewhat limited market; lately there has been a surge of children movies also largely enjoyed by adults (e.g., Shrek, Ice Age, and Madagascar)- if this trend continues, it may largely influence future forecasting • PG-13 movies try to target early teens and older. Market wise, this rating the has the largest market potential • Rated R, NC-17, and U are ratings whose market gets progressively smaller due to the audience restrictions at the box office

  8. Genre • 16 different genres (IMDB) • Action Adventure Animation Biography • Comedy Crime Documentary Drama • Family Fantasy Film-Noir Game-Show • History Horror Music Musical • Mystery News Reality-TV Romance • Sci-Fi Short Sport Talk-Show • Thriller War Western

  9. Genre • Genre also helps determine the movie’s target audience • For example, some movies, such as horror movies, are often made with the teen audience in mind (Simonoff and Sparrow, 5) • Drama movies that portray thematic topics are usually rated PG-13 an over. In this case, a movie that is under the Drama genre, but rated R may be expected to not sell as well as a similar movie of the same genre that is rated PG-13 because the audience is more limited.

  10. Country of Origin • US (American movie) • English-speaking (but not U.S.) • Non-English-speaking • This article may be of help for further research on the topic: • Neelameghan, R. And P. Chintagunta (1999). A Bayesian Model to Forecast New Product Performance in Domestic and International Markets. Marketing Science, 18 (2), 115-136.

  11. Distributing Company • Reponsibilities of distributing companies (Tyson): • The studio makes a licensing agreement with a distribution company. • The distribution company determines how many copies (prints) of the film to make. • The distribution company shows the movie (screening) to prospective buyers representing the theaters. • The buyers negotiate with the distribution company on which movies they wish to lease and the terms of the lease agreement. • Another next big step occurs once the distribution company has rights to the film. Most distributors not only provide the movie to theaters, but obtain ancillary rights to distribute the movie on VHS, DVD, cable and network TV. Other rights can include soundtrack CDs, posters, games, toys and other merchandising. • A track record of a number of successful movies that made it up to the top 20 grossing films may be a clear indication of successful marketing and this trend is likely to continue for future releases by the same Distributing Company.

  12. Production Budget • Its hard to access the production budget- even when companies disclose this information it’s hard to know if the it includes for example, in collecting data from companies, it’s hard to know if advertising and promotion are included in the production budget • Another complicating factor in measuring the production budget in predicting movie attendance may be the option with which most expensive stars in the movie are choosing to get paid- For example, in the movie Saving Private Ryan, the budget was of only $65 million, but the director and star waived their normal salary requirements for a participation in the film’s gross receipts (Simonof and Sparrow, 2)

  13. Promotion Efforts • Advertising, publicity, and promotion events help not only bring awareness to the audience, but also helps shape the audience’s opinion of the movie before they even watch it • If a preview, or advertisement does not look appealing, people most likely not spend time and money going to the theater • If the promotion efforts are successful, positive word-of-mouth advertising will likely occur- without any additional effort from the distributing company

  14. Word of Mouth Advertising • Existing new product diffusion models implicitly assume that an individual’s experience with a product is communicated positively through word-of-mouth (Mahajan and Muller, 1979) • Some actively spread favorable word-of-moth and can be thought of as adding free flow of information which augments the flow of information generated through advertising (Mahajan, Vijay, E. Muller, and R. Kerin, 1) • The challenge is measuring the extent that word-of-mouth influence in movie attendance

  15. Internet Presence • Availability not only of trailers and clips of the movie of the online movie databases like IMDB, AOL, YAHOO, and others. • AOL also has an online database of “Unscripted” Interviews, where the people can email questions to be answered impromptu by the cast; promotions such as these can really help the market awareness • BLOGS are a good indicator of how strong the internet presence of a movie is • A blog is not going to improve a bad movie, but it can certainly help generate more excitement, anticipation and attendance than an official website (Dugan).

  16. Critics Review Article: Film Critics: Influencers or Predictors • The Wall Street Journal concludes that one-third of moviegoers surveyed chose films because of a favorable review (Film Critics: Influencers or Predictors Journal of Marketing, April 1997)(70) • There are different theories of what the role of movie critics may be in relation to the box office, so I decided to list a few articles that may shed some light on the subject

  17. Critics Review • Buor, Myron (1990), “Reliability of Ratings of movies by Professional Movie Critics,” Psychological Reports, 67, 243-57. • Wyatt, Robert (1990), “Effects of Information and Evaluation in film Criticism,” Journalism Quarterly, 67 (Summer) 359-68. • Burzynski, Michael H. and Duwey J. Bayer (1977), “The Effect of Positive and Negative Prior Information on Motion Picture Appreciation,” Journal of Social Pyschology, 11, 215-18.

  18. Hollywood Stock Exchange • www.hsx.com • HSX is an online stock market simulation focused on the movie industry • As of January 2005, it had 500,000 registered users, a frequent trader group of about 80,000 accounts, and approximately 19,500 daily unique logins (Elberse, 11)

  19. Models Devising a Practical Model for Predicting Theatrical Movie Success: Focusing on The Experience Good Property http://www.leaonline.com/doi/pdf/10.1207/s1 5327736me1804_2?cookieSet=1 Sawhney, Mohanbir S. and Jehoshua Eliashberg (1996). A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Picture Industry. Journal of Cultural Economics, 23, 4, (November), 319-323

  20. Mentioned websites : • www.imdb.com (categorizes films and contains the most information on MPAA ratings, full cast lists, etc.) • www.the-numbers.com (revenue information, theater counts, etc.) • www.aol.com (has not only trailers, but also “Unscrippted” interviews with the cast of movies where they answer questions the audience has emailed to AOL) • www.movies.yahoo.com

  21. References Chen, Andrew. “Forecasting Gross Revenues at the Movie Box Office" Department of Economics, University of Washington June 2002. 20 July 2006 <http://www.econ.washington.edu/user/startz/OldCourses/482_SP2002_studentPapers/econ-482-finalpaper%20Chen.pdf >. Simonoff, Jeffery, and Ilana Sparrow. “Predicting movie grosses: Winners and losers, blockbusters and sleepers” . Jeffrey Simonoff’s home page. 2006 New York University. 6 August 2006 <http://pages.stern.nyu.edu/~jsimonof/movies/movies.pdf>.

  22. References Elberse, Anita. “Do Stars Drive Success in Creative Industries?" HBS Working Knowledge 2006 Harvard University. 6 August 2006 <http://www.hbswk.hbs.edu/item/5407.html>. Tyson, Jeff. How movie Distribution Works. How Stuff Works. 6 Aug 2006 <http://electronics.howstuffworks.com/movie-distribution2.htm>.

  23. References Mahajan, V. and E. Muller, “Innovation Diffusion and New Product Growth Models in Marketing” J Marketing, 43 (Fall 1979), 55-68. Mahajan, V. and E. Muller, R. Kerin “Introduction Strategy for new product with positive and negative word-of-mouth” Management Science (pre-1986). Dec 1984.

  24. Reference • Elberse, Anita and Jehoshua Eliashberg (2003). Demand and Supply Dynamics for Squentially Released Products in International Markets: The Case of Motion Pictures. Marketing Science 22 (3, Summer), 329-354. • Dugan, Kevin. Blogs Predict Dukes of Hazzard Movie Doom. Web ProNews. 2005. 8 Aug 2006 <http://www.webpronews.com/news/ebusinessnews/wpn-45-20050806BlogsPredictDukesofHazzardMovieDoom.html>.

  25. Reference • Film Critics: Influencers or Predictors Journal of Marketing, April 1997)

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