In my last post I introduced a reseach project I am developing. Here I give a little more evidence and context for why investigating VOD estimates in conjunction with digital engagement metrics is a valuable research topic, one which bears consideration from a market devices perspective.
The importance of International Revenues (to American Cinema)
Since international revenues overtook domestic in the mid 2000s[i], full exploitation of all international rights is extremely important to US filmmaking. Non-domestic box office accounted for two thirds of the global total box office in mid 2014[ii], and for total filmed entertainment revenue, estimates set North American revenues at just 40% of the total by 2017[iii].
The importance of Digital Home Entertainment
Digital Home Entertainment continues to increase in economic importance, and is expected to exceed physical by 2016[iv]. The general impact of VOD is well known, as Sr. V.P. of eOne Richard Rapkowski summarises: “VOD has come in very strong, the SVOD business with Netflix and other minor competitors in that space has come on very strong and has really changed the landscape for independent films.”[v] However, the detail of the challenge for film financing evaluations has been little researched and has only recently received comment in the industry press. The following quotes from Mr Rapkowski set up some of the basics of the issue:
“For the independent space it is quite different (to the studios) because you are relying on revenue streams from all these different platforms to be able to justify what you’re spending to acquire a film, and when there’s changes and uncertainty it becomes a lot more difficult to justify certain acquisitions when you don’t see the downstream revenue as robust as it used to be to be able to cover that, so there is a lot of uncertainty in the market.”
“We do, do a very sophisticated business analysis, where we do try to predict and it all starts with box office… and from there we have models that we run it through to try and predict what we think that relates to in terms of VOD revenue”
“You know Netflix has turned everything on its head… people are waiting more and more for content to hit those services and are perhaps spending less on VOD which we were hoping was going to replace Video. “
The main issues begin to crystalize when pre-sales and Europe in particular are examined more closely. The recent expansion of Netflix into European territories has prompted some apocalyptic commentary, for example in Forbes: “ Netflix will rip the heart out of pre-sale film financing.” [vi]Whilst Netflix is unlikely to become immediately monopolistic, as per Schuyler Moore’s provocation. However, the arguments that pre-sales will need to be done to a single window Home Entertainment player, that distributors may be cut out, and vast amounts of traditional value will be lost is a very real, very serious consideration. The ramifications of a few SVOD services becoming extremely dominant in multiple territories and Home Entertainment collapsing into one internet window are significant. The launch of Netflix in France, arguably a most hostile territory in terms of industrial environment[vii] has seen 100 thousand subscriptions in the first two weeks.[viii] One implication of increased SVOD carriage may be the exit of TV buyers from the feature film marketplace. Piracy and legal on-demand viewing culture has led to a current decrease in TV acquisition deals, traditionally part of distributors’ lifeblood for putting forward MG and supporting their P&A [ix]. Legal and regulatory forces at play supplement the business and technological trends pushing towards a dramatic reorganisation of the film-financing environment. The EU is proposing a single common digital market for content[x] and this is supported by other VOD players e.g. VODdler[xi] with producers looking for protective quotas for European content.
There is a great variety across different nations with respect to environments for windowing and VOD. In some territories’ theatrical leverage prevents VOD debuts[xii] including the US[xiii], but the move towards theatrical and fewer simpler at home windows is inevitable with pilots at large (Imax and Netflix)[xiv] and smaller scales (Curzon[xv] and Artificial Eye[xvi]). Other nations’ VOD models include develop innovative festival availability to address the glut of content and capitalise on period of most attention, be it for market sales (Venice)[xvii] or straight to consumer (Rotterdam)[xviii]. Sales agents and distributors generally want to exploit new avenues “without crippling the global pre-financing system”[xix] and so innovation is generally limited, undisclosed and not spreadable. But despite inertia these very complex areas are changing and are recognised as requiring research[xx] and attention. For instance, Joint-Venture initiatives between producers and distributors in which value can be ascertained earlier and developed through audience engagement activity usually beyond the financial scope of producers.[xxi]
These issues point to the conclusion that understanding the new evaluative processes connected to VOD rights will be extremely important to film financing. The investor finder network Slated offers a great example of how traditional film characteristics are being deployed in a digitally mediated environment. Calculative metrics such as credits, box office, script labs and awards, genre budget, and peer evaluated company attachments, together form a market construction device. In using packaging and credit scores investors implicate such formulae in their own evaluation processes and economic transactions result. Producers also benefit by understanding a more robust and standardised element of how their project is evaluated by potential partners.
The value of international home entertainment rights and audience engagement data are increasingly important factors as filmmakers deal with the question of how to attract shrinking finance. For example the amounts quoted for Netflix rights buys in France are 15% of the norm[xxii]. Filmmakers must develop strategies for appealing to new types of buyers, and be able to assess when DIY on-demand or festival linked releases offer better chances of success than rights sales in particular territories. PR companies, producers, sales agents and management have long monitored social media and online opinion during festivals and markets as part of deal making techniques, it is now being standardised and legitimised.
Building in audience demand data to more traditional evaluative frameworks will facilitate a smarter boundary object to enable deals between partners. For investors evaluating a project to part-finance, an understanding of how digital rights are valued is essential and digital engagement will play a role in this. Whilst sales agents have traditionally been in a position of strength thanks to their historical data of comparable titles’ performance per window and per territory, evidence from Netflix indicates that sales agents will be missing some vital data and that old patterns linking performance across windows no longer hold as these barriers come down. The role of audience digital engagement is paramount in managing uncertainty.
Digital Audience Engagement Metrics: Challenging new calculative practices
“Algorithms drive our entire website— there isn’t an inch of uncalculated editorial space.”[xxiii] Ted Sarandos, Chief Content Officer of Netflix, 2014
Evidence from Netflix gives credence to arguments that understanding audience engagement data will be crucial to film financing, and that the future of independent filmmaking faces a more complex threat than is commonly understood. Comparing the quote above, to the explanation of current practice by global distribution force Entertainment One below, it is clear that there is a barrier to be breached in terms of understanding as windows further conflate and financing patterns change.
“It is art as much as it is business, and that is from the business side it is an art, because there are no clear-cut answers and ultimately no one knows how a film is going to perform… There’s an alchemy to it… it is not an easy thing to predict consumer taste… sometimes its timing and sometimes its that right magic with the right cast or right director… To say it’s a science would be untrue
The digital world also brought us Rotten Tomatoes, so it’s a lot easier to find out about films that people love and to find through social media to cut through in maybe a way that serves consumers better which is… to have almost instantaneous information about how good a film is if you trust others opinions both critical and your own social network” Richard Rapkowski, Sr. V.P. eOne, 2014
Statements from Netflix imply many challenging developments for independent film:
“We don’t really use the data to tell us what we should and shouldn’t have on the site. We use it to indicate how much I should or shouldn’t pay. In other words, if I can get an enormous amount of viewing, I’ll pay an enormous amount of money. We invest in a lot of content for really small audiences too, because it’s still valuable for subscribers who are really engaged fans of a particular program, and, therefore, it’s a valuable investment for us.”[xxiv] Two inferences may be drawn from this business perspective. First, independent films, which do not prompt the repeat or binge viewing that “TV” shows generate will have a tough time evidencing their value for engaging fans. Second, those films that do so will need producers and financiers to grasp more accurately ways in which consumer demand can be evaluated and demonstrated with digital metrics. They must also do so in a context of adaptive release patterns.
ListenFirst, a Digital Audience Ratings company conceptualise the existing dichotomy and gap in knowledge in their summation of their own business proposition: There is a “shift from an era of scarcity of audience data to an era of overabundance. Because of earlier research in the media industries, we have some information regarding how executives and creators managed a paucity of data, including a reliance on gut instincts, industry lore, and complicated power plays among creators and gatekeepers that often deployed different conceptualizations of the audience. In an age of data overabundance, however, different individuals and organizations—different “power roles,” to use Joseph Turow’s generative concept—use data to try and gain acquiescence and advantage over other players. At the same time, an increasing amount of information is private and restricted.”[xxv]
Traditional element evaluation via historical performance and comparative titles analysis is an embedded feature of the content business that will continue: “…we (Netflix) pick the shows by intuitive, data- driven hunches. The good example is our production House of Cards. David Fincher is directing… Kevin Spacey and Robin Wright are starring in it. It’s based on a piece of intellectual property that we know very well. We can draw real data pools of people who love Kevin Spacey movies, David Fincher movies, the original House of Cards, political thrillers, and on and on. You wind up with a very predictable pool of viewers. If the show is executed well, we know how many people will watch it.”[xxvi] However, the mass of data created by VOD services is privileged information, and as TV and DVD consumption melds into internet Home Entertainment consumption, the value of this data will increase. It becomes incumbent on all market actors in the film value chain (funds [public and private], sales agents, distributors, producers) to be able to create and demonstrate audience engagement and likely demand, evaluate that data and present it in a format enabled to facilitate economic transaction.
Digital Engagement Metrics have become a proxy for demand data, new businesses are founded on their predictive capacities and they are reported in the same manner a Box Office data in the trade press[xxvii]. Academic research has proven the strength of relationships between such metrics and theatrical revenue when the data is drawn a few weeks prior to release. Early online response data substantially increases forecasting models also using traditional valuables (Dellarocas 2008). The volume, valence and dispersion of online movie reviews all have a significant relationship with Box Office. However, the fundamental dynamics of extreme uncertainty that govern revenue distributions in the film industry have not been shown to be reliably more manageable by the use of inherently global digital marketing tools. Investor, producer and distributor all aim for high online ratings[xxviii], blog references[xxix], Wikipedia edits[xxx], and Tweet rates[xxxi] as social word of mouth[xxxii] to exploit the positive feedback[xxxiii] and social learning multiplier of the internet.[xxxiv] This is because such variables are generally correlated to Box Office sales, however, the relevant market action takes place only after financing and rights sales decisions must be made and most costs are sunk. Understanding and capitalizing on the relative value of digital engagement information at earlier stages of the film life cycle is essential for film packaging and sales, for this reason social media data is tracked at festivals and markets. [xxxv]
Now that day and date has become commonplace, the statistically significant predictor of total revenues from Box Office returns may become lost as a tool. In response there is significant work to do to make sense of digital engagement data in relation to other established arbiters of film value, including determining how such information can be evaluated with respect to price. The results will include human interpretations for decision making as well as positivistic empirical fact. This process will differ depending on the market actor’s position and at different points in life of a film. It is only a small component part of the film financing question but one that requires attention now. The earlier a more regularized understanding of the new phenomena can be attained e.g. a plug-in to more established devices like sales estimates or recoupment waterfalls, then fewer opportunities will be missed. Whilst the expansion and importance of Netflix is just one influence on film financing, considering their dominance and data pool of viewing habits per talent, genre and territory, there is potentially a risk of greater extreme Pareto driven models of film activity, where only directors or stars that have followings can be re-financed. Thus there is a need to develop strategies to finance diverse content and preserve an appetite for risk. Research shows international box office determinants have tended toward blockbuster safety nets of action, children’s’ films, sequels and higher budgeted films[xxxvi], more challenging films will require a stronger evidence base for support and this can partially be sourced from Digital Engagement Metrics.
Digital Engagement as a Currency
There are new services and frameworks for aggregating data and linking it to rights exploitation that inherently involve processes of evaluation. DFCN (Digital Film Cloud Network)[xxxvii] provides an agglomeration of DRM, licensing arrangements and combined “social clout” scores.
Way To Blue[xxxviii] measures social media engagement via total mentions, and mentions with intent to view, which is claimed to have a statistically significant relationship with theatrical performance (2 weeks out). Proclivity to view is broken down by sentiment, themes, marketing assets and uses the social performance of comparable titles for benchmarking, controlling for the time of year and rating.
ListenFirst[xxxix] provide Digital Audience Ratings (DAR) which are raw aggregate daily engagements of owned, earned and organic behaviour on Facebook, G+, Instagram, Tumblr, Twitter, Wikipedia and YouTube. The system charts pre-release of films: “DAR can provide a side-by-side comparison of how impactful online a trailer for a movie coming out in 2016 is, alongside a movie being released next week.”[xl] The company specifically aim to provide a standardised framework for evaluation: “We’re providing the measurement standard to quantify audience engagement in a way that complements traditional tracking and ratings that don’t take these critical indicators into account.”[xli] How such figures are currently taken into account by different market actors at different points of a film’s life, and how they should be in future, is the topic of my research.
Endnotes / Links
[xiv] http://variety.com/2014/digital/news/crouching-tiger-hidden-dragon-sequel-netflix-weinstein-co-1201316645/ ; http://blogs.indiewire.com/boxofficeinsider/okay-what-happens-now-as-big-3-exhibitors-nix-crouching-tiger-netflix-imax-plan-20140930?utm_campaign=okay-what-happens-now-as-big-3-exhibitors-nix-crouching-tiger-netflix-imax-plan-20140930&utm_medium=social&utm_source=Facebook&utm_content=okay-what-happens-now-as-big-3-exhibitors-nix-crouching-tiger-netflix-imax-plan-20140930
[xxiii] Interview with Ted Sarandos, Chief Content Officer of Netflix in Curtin, M., Holt, J., & Sanson, K. (Eds.). (2014). Distribution Revolution: Conversations about the Digital Future of Film and Television. Univ of California Press.
[xxiv] Interview with Ted Sarandos, Chief Content Officer of Netflix in Curtin, M., Holt, J., & Sanson, K. (Eds.). (2014). Distribution Revolution: Conversations about the Digital Future of Film and Television. Univ of California Press.
[xxv] Media Programming in an Era of Big Data – Timothy Havens
[xxvi] Interview with Ted Sarandos, Chief Content Officer of Netflix in Curtin, M., Holt, J., & Sanson, K. (Eds.). (2014). Distribution Revolution: Conversations about the Digital Future of Film and Television. Univ of California Press.
[xxviii] Dellarocas, C., Zhang, X. M., & Awad, N. F. (2007). Exploring the value of online product reviews in forecasting sales: The case of motion pictures. Journal of Interactive marketing, 21(4), 23-45.
[xxix] Sadikov, E., Parameswaran, A. G., & Venetis, P. (2009, March). Blogs as Predictors of Movie Success. Proceedings of the Third International ICWSM Conference.
[xxx] Mestyán, M,.Yasseri, T., and Kertész. J. (2012) Early prediction of movie box office success based on Wikipedia activity big data. PLoS ONE 8(8).
[xxxi] Hennig-Thurau, T., Wiertz, C., and Feldhaus, F. (2012) Exploring the “Twitter Effect:” An Investigation of the Impact of
Microblogging Word of Mouth on Consumers’ Early Adoption of New Products. Cass Knowledge Paper. Film, Media, and Entertainment Research Centre.
[xxxii] Ishii, A., Arakaki, H., Matsuda, N., Umemura, S., Urushidani, T., Yamagata, N., & Yoshida, N. (2012). The ‘hit’
phenomenon: a mathematical model of human dynamics interactions as a stochastic process. New journal of physics,14(6), 063018.
[xxxiii] Duan, W., Gu, B., & Whinston, A. B. (2008). The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry. Journal of Retailing, 84(2), 233-242.
[xxxiv] Moretti, E. (2011). Social learning and peer effects in consumption: Evidence from movie sales. The Review of Economic Studies, 78(1), 356-393.
[xxxvi] Terry, N., Cooley, J. W., & Zachary, M. (2010). The determinants of foreign box office revenue for English language movies. Journal of International Business and Cultural Studies, 2(1), 12.
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