Real Data: An Epilogue and a Beginning

I recently concluded my series on what data in the film industry currently looks like. I mentioned the reasons why it has been difficult to get much information out of the current system, and introduced a few companies that are trying to do something about it. I also mentioned that I work for VHX, one of the companies that provides digital distribution to filmmakers and a direct connection to their audiences.

Well, today that connection becomes a little more relevant, as VHX has announced the release of a website that aggregates all of the VOD data they have from two years of sales. It's real-time and is as transparent as it gets for this industry. I proudly present: VHX stats.

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We have been building this since I began working with the company, so I'm proud and excited to share it with the world. Click over there to take a look and just imagine the possibilities if the rest of the industry were brave enough to take this step.

Have We Been Hoodwinked? Bamboozled? Led Astray?

On the hotly contested and politically charged terrain of contemporary media culture most filmmakers live or die based on an industry model that is largely dependent upon the number of screens on which a film plays. This traditional line of thinking posits that the more screens on which a movie is shown the more money that movie makes.

However, given the state of audience fatigue induced by the current Hollywood megabudget, superhero, sequel, prequel, unoriginal remake, CGI, film cycle we're mired in--- this line of thinking has become misleading.  Movies with huge budgets that play on thousands of screens are failing to turn a profit (see my previous article: "Is Hollywood Out of Touch?" for more details.)

As a critical part of my research agenda, I’ve examined the most recent data from the United States Census Bureau and the theatrical market statistics from the Motion Picture Association of America, and what I’ve found is shocking.  People of color comprise 36 percent of the total U.S. population.

Yet, this same segment (people of color) make up 57 percent of the total movie-going audience.  That’s a lot of box office power!  But despite this stark overrepresentation of people of color in movie audiences only 2 percent of the movies produced in Hollywood have a diverse cast!  Have we been had?  Are we being took?  Have we been hoodwinked? Bamboozled? Led astray? Run amok?

You be the judge. Take a look at the infographic I've created below based on the data from a new study conducted at UCLA's  Ralph J. Bunche Center for African American Studies.

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Men lie. Women lie. But numbers don’t.

The stories, images, and experiences of people of color remain largely absent in commercial film and television.  The way America's population is trending (with people of color rising dramatically in number) this current lack of cinema and media representation is nonsensical and, frankly, fiscally unsound.  So instead of complaining about these gross inequities (and listening to others complain) I’ve decided to do something.  My current research with the CRI reveals that multicultural audiences have an enormous appetite for films that honestly depict the multiple facets of their communities using imagery that expresses the fullness of their humanity.

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With this in mind, working with the CRI I’ve designed Project Catalyst— an innovative transmedia company that fuses creative community building practices with cinema, art, and technology— to challenge the lack of visibility given to people of color in the current media landscape. 

My work with Project Catalyst is aimed at re-imagining the empowering possibilities of cinema by designing a new socially engaged, artistically rich, transmedia experience that directly addresses multicultural audiences and filmmakers.

As new technology continues to evolve and change the cinematic terrain, my goal is to embrace this change and push the boundaries of the possible.  My work with Project Catalyst emerges as a disruptive innovation that marries digital and mobile technologies with cinema, visual art, creative activism, and participatory engagement.  My aim is to achieve an alternative distribution model that navigates multiple media platforms to showcase amazing films— by and about people of color.  In fact, I contend a platform like Project Catalyst is long overdue.  And I am not content waiting around for some out-of-touch studio executive to finally recognize that people of color actually go to the movies!  The time has come to truly celebrate diversity in cinema and media— the audience is there, the appetite is there, the buying power is there, and the time— is NOW.

 I real(eyes) great ideas can changethe world, but it requires great people to make it happen. So I need your help. Go to our newly designed website www.projectcatalyst.com and fill out the information to “Become A Catalyst,” and get involved to show your support.  I look forward to taking this amazing journey with you!

Like our Facebook Page and follow us on Twitter  for more details on how you can help spark this exciting change!!!

Case study on dynamic pricing: Broadway

The movie exhibition industry is about 9x larger than the Broadway business (per total gross in 2013), but Broadway instituted dynamic pricing years ago and does face similar strategic challenges: a blockbuster-hits driven business that seeks to maximize profits under challenging audience constraints. About half of the tickets for most Broadway shows are sold the day of. In the movie business, studios spend millions towards a one-weekend gross or it’s a flop. But unlike movie tickets, Broadway ticket pricing continues to get more fluid. They sell three types of tickets – premium tickets, group sales, and discount tickets. Discount tickets are sold to those who don’t pay in full but will buy. These discount tickets won’t be assigned the best seats, nor will they fill a house with these buyers. By the night of the show, about half have been sold at various prices and no one knows what the other person paid. Sometimes, a producer would rather see the seat empty than sell too low of a ticket. You cannot discount too much if there are individuals who’d be willing to pay in full. The pricing power varies depending on the show’s popularity. For example, shows often up the price after a Tony Award win.

Movie ticket attendance has trended downwards at a fairly steady pace over the last 10 years, while Broadway ticket attendance has shown a more uneven trajectory. Despite a steady uptick in average ticket prices, the number of seats sold grew in 7 out of the last 10 years. A sign, perhaps, of the success of dynamic ticket pricing?

Annual Broadway BO

The pricing strategies vary from “The Lion King”, which has dynamic pricing down to an exact science, to “The Cripple of Inishmaan,” which is offering deeply lower tickets to lure young theatergoers to the art. In addition, new start-ups like Today’s Tix are pushing user-friendly ticketing experiences to attract those that won’t go to the box office for tickets or don’t find the coupon they want online.

It’s Lion King’s algorithm that is of particular interest to the scope of this project. The show draws from data for 11.5 million audience members so far, and has outearned other shows despite capping its prices. Their strategic decisions are all focused on sustainability. According to the New York Times, producers believe this keeps the show “relatively affordable for for large groups and families; lessens the chance of buyer’s remorse leading to bad word of mouth; and offers room to raise prices over the long term.”

Our analysis of Broadway, MLB, and airline ticket pricing underscores the importance of data. The next step of this project will be to gather as much data as possible about movie ticket attendance and demographics. Ideally, we can then chart potential pricing schemes for peak dates vs. off-peak dates. Just like the Lion King, the more data that is collected after instituting a dynamic pricing scheme, the better theater owners and distributors should be able to adjust and develop a more fluid algorithm to generate the price-attendance combo to maximize profits.

A look at existing film performance research

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Learning, Data, and Love

  One of the primary theses of my research is that people are not like films, people are like other people. As such, recommendation engines that try to base what you would like to watch on what you have already watched are inherently flawed. Even if this were the right starting point, the algorithms currently doing this work are likely to value the wrong things when comparing films. It is very possible to love Iron Man and hate Iron Man 2, but not according to these current systems.

So what should we be comparing? My belief is that people's behavior tells us what other people they are like, not what films they will like. I'm much more likely to watch a movie recommended by friends who share my tastes than by an advertisement, critic, or stranger. But if we are to accept this as the starting point, can we define people well enough to make the right match?

Well, that is certainly what I'm exploring in the film world, but some very smart man seems to have figured it out already in a not-so-different space: Love.

chris mckinlay

UCLA mathematician Chris McKinlay is profiled as doing just that in the Wired article How a Math Genius Hacked OkCupid to Find True Love. In short, he used data he collected by mining OkCupid to separate all female users into seven distinct cohorts. He could then look at the properties of these groups (age, religion, etc) and determine which fit the profile of someone he would want to date.

I certainly recommend reading the whole article (as the story of a mind who tries to find love by sleeping on a mattress in the cubicle of his office creates a compelling dichotomy,) but for the purposes of film marketing suffice it to say that this level of increase in marketing effectiveness is a virtual goldmine. McKinlay went from 100 high level matches out of 80,000 women (.1% effectiveness) to 10,000 high level matches (an insane 12.5% effectiveness rate!)

And it wasn't that he was lying to anyone. He just determined the right questions to answer that were the most relevant, and how important each of those questions were to the given cohort. Isn't this what marketing should be? Get the right message in front of the right people and your conversion rate soars.

At the risk of spoiling the article, I found this quote from McKinlay's now-fiancee to be the most illuminating.

“People are much more complicated than their profiles,” she says. “So the way we met was kind of superficial, but everything that happened after is not superficial at all. It’s been cultivated through a lot of work.”

The way we introduce people to movies for a marketing perspective is always going to be somewhat superficial. The key is to make sure that after that introduction has been made, there appears to be the right motivations behind it. This gives the audience a reason to trust you and your message, and creates a virtuous cycle.

While my research may not take us all the way to the promised land (and it certainly won't get anyone a date,) I think it begins to push the ways in which we evaluate and understand audiences and their preferences. Most importantly, experiments like this should show distributors, marketers, and even studios the benefits of exposing their data. After all, when do you think was the last time any of them hired someone with a PhD in mathematics?

Real Film Data (Part 3: Online)

To this point, we’ve looked at why it’s hard to get data about film audiences from both theatrical and VOD companies, be they exhibitors or distributors. The misalignment of incentives is the primary motivator for the lack of collection of and the hesitance to distribute real numbers and reporting.

Fortunately, there is a new form of film distribution that is all about the data. Companies like VHX*, Gumroad, and Vimeo are enabling filmmakers to control the pricing, release strategy, and perhaps most importantly, the data that results from sales. This is a huge change in ethos from the business models we have been talking about

*Disclaimer: I have been working with VHX since the beginning of the year, specifically as a Data Analyst. The screenshots below are from their service largely because of the ease of access, but other services provide the same types of reports. 

What Data Looks Like

The images here are from the view a filmmaker would see in their dashboard. This is the top level report that shows the number of sales per day over the course of a week. It also shows important aggregate data such as “All-Time Revenue” and “Total Sold,” although these number are also things would would get from a distributor who offers your film on a VOD platform.

So what’s the big difference?

Screen Shot 2014-04-13 at 3.44.03 PM

With a traditional distributor, these numbers come in quarterly (if not longer,) by which time it’s too late to make any changes to your marketing, publicity, or release strategy. But with real time data, you can see your sales as they happen, meaning you can take insights away about how effective everything it, and even where advertising is working and where it isn’t.

You may be thinking, “If my film isn’t doing well, what can I really do?” Because of the amount of control you have, there’s actually quite a bit you can do.

What Pricing Looks Like

The first thing is the most obvious, you can lower your price. But rather than just dropping the price for everyone, you can run things like flash sales. By offering a coupon that discounts the price of the content, you incentivize people to buy the film before the price goes back up. It turns out that this is a strong motivator for audiences to purchase.

You can also tie bonus content to the movie and charge a premium price. Some films, such as the documentary Stripped, have massive amounts of additional footage that they add to a more expensive product, allowing super fans to get more content while still allowing everyone else to just see the movie. Other films, such as Camp Takota, leverage services like Shopify to sell merchandise along side digital downloads of the film.

There’s another important question companies like this hope to answer. Once people start buying your film, how do you spread awareness without spending boatloads of cash on marketing?

What Your Audience Looks Like

Once you get your film out there, whether it’s the “free” publicity from a film festival, active social media engagement, or just straightforward advertising, it’s important to know who is coming to your site and who is buying your film.

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The image here shows one way that the VHX platform tracks that, showing the source of traffic to your site, the conversion percentage for each source, and for all countries. This is a great way to get a top level view of where you audience is located, but there’s also a great way to know exactly who your audience is.

When someone buys the film, the filmmaker knows two important things: their location (at least their state/country) and their email address.

This is incredibly powerful for engaging with your viewers when it comes tim to grow your audience. You can send the people who purchased your film a discount code that they can share with friends, thus reaching people who your advertising may never get to. You can also carry this audience over to your next film, so you’re not starting over from square one with each film.

If you want to read more about great community engagement, read the Indie Game: The Movie case study. It might change your life.

What Isn’t There… Yet

I have painted a rosy picture of this world so far, but it is not quite there yet. The industry classifies this type of distribution as Electronic Sell Through (EST,) and it makes up a very small part of the industry’s gross revenue. This is partially because filmmakers and distributors are not looking at this as an important way to sell a film, but also because it is not a way that audiences are used to consuming their content.

It can also be more difficult to drive an audience to a specific film website as opposed to a market place. Think of it as the difference between the person who went to Blockbuster looking for a specific movie as opposed to the person just browsing for something interesting (you may have to be over 29 years old to understand that.)

That said, these problems are not unsolvable, and in fact are well on their way in the right direction. Shortly after championing the new models of distribution in his speech at the Edinburgh International Television Festival, Kevin Spacey self financed and self released his documentary Now: In the Wings on a World Stage, while Joss Whedon released his film In Your Eyes on Vimeo On Demand for rental.

As more people within The Business start to understand the benefits of this type of release, I imagine the problems presented above will fade.

Data: An Epilogue

What is next for us. Now that we know the truth about what data is out there, we can begin to explore what we can do with it. The next step for me as part of the CRI program is to start the quest toward defining a way of talking about this data that makes sense to films and filmmakers. The first step toward that will be next week.

Case study series on dynamic pricing: MLB

Ticket brokers like StubHub and scalpers brought dynamic pricing into sports ages ago, but not until recently did officially-sanctioned dynamic pricing emerge. The MLB has been the most aggressive over the last several years and 26 of the 30 teams now use dynamic pricing. Last time, the airline industry was placed under the microscope. This week, let’s assess the MLB and what ticket pricing principles in that realm can be transferred to the theatrical business. Unlike the movie industry, there is a lively and active secondary ticket selling market, most prominently on StubHub. But teams became concerned this resale market devalued tickets and responded with dynamically priced tickets and other programs for ticket resales. The SF Giants paved the way four years ago. Variables used included: weather, winning streaks, starting pitchers. The algorithm came from ticket-pricing firm Qcue, who built it with data on popularity of opposing teams and prices from online secondary ticket markets.

The pilot was a resounding success - it pulled in an extra $500K over the season. With a World Series win and solid performance since then, the Giants continue to capture more market value than under a static pricing system. Ticket revenues are up by 7-8% per year. Though season ticket sales skyrocketed, the team still caps a quarter of the ballpark to dynamic pricing. The prices varied by $1-2 at the beginning, but can now go as high as $5-15 more for high-demand games.

Between studying the MLB and the airline industry, the project continues to narrow down into the exact type of test we’ll conduct:

Here are the major takeaways from the case study of the MLB:

• The relationship between sports games and movies draws more similarities than airlines. However, movies – unlike sports – are not one-time events. Watching a movie is still less “must-see” because you can see it in many other formats later.
• The goals of this project are similar to what the Giants and MLB wanted: more revenue from high-demand movies (games) and ensure that seats at less popular movies (games) that would otherwise go vacant are sold.
• Contact Qcue for a conversation. Que also sets prices for 30+ NHL, NBA, MLS, and MLB teams.
• Start finalizing the short list of variables we want to consider.
• Where can we get data to develop a simple-as-possible algorithm?
• Set a ceiling and a floor for ticket prices to preserve revenues and to ensure people do not think you’re greedy. Consumers will not buy into perceived greed.
• The type of test the project continues to narrow. The current intended focus: reward those who buy tickets early. Prices increase as ticket inventory decreases or as the date of the movie approaches.

Forest for the trees: Risk categorization criteria

Over the last month I’ve been wandering through a forest of data - exploring and compiling various pieces of information related to 1350 films that received a US theatrical release in 2012 and 2013. This data will be used to train the initial rubrics that will guide my separation of films into four risk levels.  While I’m still in the process of finding and organizing this data, I wanted to reach out to readers to ask for your thoughts on my approach. As a reminder, I’m initially dividing the index into 4 sub-indices, each with a distinct level of risk. See my last post for more detail. My job, therefore, is to properly select criteria that correlate to risk (in terms of films’ financial returns). The 3 criteria I believe will be most important follow:

Marketing budget

I believe this is one of the most important factors contributing to a film’s success or lack thereof. You can tell a unique story through an amazing, well-crafted film, but if you don’t properly get the word out about it, it won’t be seen by many people. Unfortunately, I’m discovering that accurate information about films’ marketing budgets is quite difficult to find.

I’m planning to compile information from filmmakers, distributors, ad agencies and journalists to triangulate/approximate marketing budgets for specific titles. However, this may not be fruitful in a lot of cases. And it’s hardly a scalable approach. So, dear reader, where else might I look for information about marketing budgets? Extra points for accurate, scalable sources.

Production budget

A film’s budget impacts everything about it. If a story hasn’t been sufficiently supported through its budget, an amazing story and/or cast won’t shine through. Nor will a marketing budget be as effective, regardless of its size. This is not to say that all films have to have a large budget – many very low budget films have still performed very well, both critically and financially. While I believe it highly likely there will be strong correlation between film budget and ability to drive revenue, I also believe films with distinct profiles have distinct budget levels that will indicate propensity for success at the box office and beyond.

Sources like BoxOfficeMojo are fantastic aggregators of data like film budget. However, it’s not assured the recorded budgets are correct. Additionally, I’ve found sites like this don’t record budget for hundreds of low budget indies. Where might I find budgets for these smaller films? How might I confirm the accuracy of reports made by data aggregators like this?

Attachments

Films are not commodities. Films’ casts, directors and producers undoubtedly have enormous impact on the finished product. Therefore, I’m positing that attachments themselves have significant impact on the potential performance of a film independent of its production budget or marketing budget.

The creative players in a film are some of the easiest pieces of information to discover with certainty. However, unlike budgets, attachments are not numerical in nature. To approximate a numerical system, I’m taking on the highly imperfect task of devising a scoring system within which to place key attachments, based on the financial success of films in which they previously participated. I am trying to create a science in something that is obviously unscientific. Any opinions about factors I might want to consider along the way are highly encouraged.

I should note that I will be tracking other sorts of data as I organize my training data. Critera like distribution strategy (wide, platform, limited, day-and-date, ultra-VOD, etc.), source (studio, mini-major, established indie filmmaker, unknown, etc.) and origin (existing blockbuster book, original material, etc.) are likely related to level of financial risk. However, these may end up being largely duplicative of the above, more complex criteria. Also, I’m limiting the data pool at this early point in hopes of not muddling other correlations that may prove strong.

I’m lucky to have had interested mathematicians and data scientists reach out to help me discover and organize meaningful conclusions from my raw data. Engaging with folks who read these posts has been incredibly helpful. I want to talk with even more people – so, please, comment on this post or email me directly at colinwhitlow@gmail.com if you’d prefer. I’m open to all ideas and questions.

ANNOUNCING THE 2015 CRI FELLOWSHIP

The Cinema Research Institute is pleased to announce that applications are now open for the 2015 CRI Research & Development Fellowship! In 2015, the Cinema Research Institute will award up to 3 research & development fellowships to individuals or teams interested in the conception, development and execution of new models and tools of film finance, marketing, and distribution. CRI Fellows will use their creative, strategic, and research skills, both individually and collectively, to address the challenges and seize the opportunities of the ever-changing film industry.

All interested individuals and teams are welcome to apply for the CRI Fellowship. Applicants may 1) propose research to examine independent film finance, marketing, and distribution models on a national and/or global scale for film, television, and other media; 2) develop an innovative idea to address a specific problem; or 3) demonstrate a proof of concept. Applicants may also submit a proposal to further work on existing CRI research projects.

Regardless of the developmental stage of the idea, appropriate candidates are academically and creatively accomplished individuals from a wide variety of disciplines. Successful applicants will receive up to $25,000 for their yearlong Fellowship (January – December 2014), during which time they will be introduced to industry mentors, have the opportunity to test their hypotheses and propose solutions, engage with academic and industry advisors, and publish their findings through the Cinema Research Institute .

Each CRI Fellow will be required to attend monthly advisor meetings, contribute to the Cinema Research Institute Blog, submit quarterly reports, publish a white paper on his or her research to the Cinema Research Institute Journal, host an individual symposium on his or her research topic, and participate in an annual CRI conference. Applicants are encouraged to review existing projects on the CRI website.

There are three rounds of application review for the CRI Fellowship.

Round 1 – Applicants submit:

• A CV or resume.
• A proposal describing the research topic, methodology and any testing opportunities (1-2 pages.)

The deadline for submitting an initial proposal is the end of day on June 2, 2014. Proposals should be emailed to miranda.sherman@nyu.edu. Applicants will be notified of their status by July 7, 2014.

Round 2 – Semi-finalists provide:

• A personal statement of purpose (1-2 pages).
• A detailed proposal (5-10 pages).

Deadline: end of day on August 4, 2014.

Round 3:  Finalists participate in an interview with the CRI Advisory Board.

Case study series on dynamic pricing: Airlines

There’s no business like show business, but to better inform the shape of the dynamic pricing in this project, I decided to take a closer look at dynamic pricing in the other industries in a series of case studies. The airline and hotel industries famously use dynamic pricing (tens of thousands of times daily, according to some reports). Dynamic pricing has also spread to other sectors: some sports teams (the SF Giants), at least one restaurant (Next in Chicago), and transit (Uber). At best, this series allows the project to shamelessly crib best practices and sidestep pratfalls. We kick things off with a study of the airline industry. Just like movie theaters, airlines seek to maximize the revenue they can generate per person and balance the challenging operating metrics they must meet to maintain their thin, thin margins. Bad news: the differences between the airline and theatrical exhibition mean we should not replicate airline dynamic pricing practices. Good news: research on dynamic airline pricing has indicated price discrimination grows both revenues and consumer surplus (aka satisfaction) for airlines. This is encouraging news for the scope of our project.

Let’s dive into the pricing mechanics.

Up in the Air

Airline prices usually follow this trend: prices are cheap the earlier you buy, peak when demand is particularly uncertain, then dip again as the airline attempts to fill as many seats and minimize unfulfilled demand, and spike to take advantage of last-minute purchases and very inelastic demand.

The components of the airline ticket price are: cost of service, cost of not selling that seat on a substitute flight, and the forgone option of selling the seat later on the same flight. Airline purchasers must weigh the expected gain from delay against the cost of failing to acquire a seat. This is something that moviegoers are unlikely to spend much time considering due to a number of inherent differences.

The biggest difference is demand elasticity. The power of demand for the ticket is quite different. Theater attendance is more responsive to price changes than the airline industry because movie tickets are discretionary. Airline tickets are often purchased because the consumer must absolutely get there. Consumer demand is often unfulfilled until they buy the ticket, offering some leverage to airlines. In contrast, movie theaters can go empty because the audience just chooses to go elsewhere or see it on another platform.

The power of competitors varies greatly between the airline and movie businesses. The airline industry has very few competitors and few substitutes. Buses and trains tend to be perceived as cheaper and worse because they are quite demanding on personal time. This leaves airlines as the dominant mode of long-distance travel. The same can’t be said for movies in the content landscape. Everywhere you turn, there’s a new competitor for your hard-earned leisure time: television, video games, online video, and plays, just for starters. This ties back into how price sensitive moviegoers are versus fliers.

Though airline industry is a bad proxy for this project, there were some good takeaways from this case study, including:

• Airlines tend to do: peak user pricing and time of purchase – how can this be applied?
• Focus on the customer dynamics and use this to shape how we build this model
• Cannot assume that an efficient market will include fully sold out seats. The optimal amount may not be the case.

Next up in this research series on dynamic pricing: sports.

Whatever Happened to Multicultural Cinema and Television?

Gone are the glorious days when television programs like: A Different World,  New York Undercover,  and Living Single graced the airwaves and stimulated the small screen.  These TV shows (among many others) reflected broader depictions of humanity for people of color, and expanded visions of the possible for millions of Americans.  Since the early 2000s there has been a steep decline in the production and distribution of diverse entertainment in Hollywood overall.

DW

nyuc

And yet, it is important to note that the removal of multicultural films and television programs from mainstream screens has not removed the necessity for or the insatiable craving for multicultural images and stories from members of diverse communities.  Quite the contrary— the desire for diverse content has never been greater!

In fact, Black and Latina/o Americans watch 44% more film and television than other groups.  A recent survey conducted by the Harvard University School of Public Health reveals that, African-Americans rank the highest in terms of their dissatisfactionwith their current entertainment options.[1]  Historian Preston Lauterbach points out “entertainment is good for the soul [and] entertainment hits you the best and hits you the hardest when it’s directed toward you.”[2]   Can I get a witness?!?  However, for various reasons, dominant media continues to ignore multicultural audience members and this has created a tremendous void for people of color.

Living-Single-cast

Thus, with the support of the NYU CRI, I have officially launched Project Catalyst— an innovative transmedia organization that galvanizes amazing filmmakers, thinkers, and visual artists, to combine creative community building practices with cinema, art, and technology. Our mission is to provide alternative entertainment options for an ever-expanding multicultural population. Throughout my fellowship year, (and beyond) we will diligently work to put forth an exciting new model that unveils positive solutions to this very pressing dilemma.

 My aim through Project Catalyst is to cultivate an artistic and cinematic space rooted in the cultural affirmation of diverse communities.  A space where culture is produced and knowledge is shared that reflects the multivalent stories, experiences, and images that challenge traditional boundaries of what others conceive as valuable, not only for ourselves, but for the sake of generations of young people growing up in a media culture bereft of reflections of themselves.   Project Catalyst is a model for disruptive innovation.  A platform that fills the enormous gap in diversity that Hollywood has created.  We are providing a culturally expressive communal space that celebrates the spirit and diversity of American life!

Project Catalyst is an organization that serves as a vehicle for filmmakers who are creating works specifically for communities outside of Hollywood’s lamestream.  If you desire to reach a multicultural audience, we can help you. If you desire to share a powerful story from a traditionally underrepresented perspective we’re here to serve you.  Our goal is to amplify films, filmmakers and artists who create visual culture that possess high quality and strong humanistic voices, in order to transform our collective media invisibility into an undeniably visible cultural and cinematic force.

As always, I real(eyes) great ideas can changethe world, but it requires great people to make it happen. That’s why we need your help to share our message of positivity with others.  I thank you in advance for your continued support.  And I'm honored to take this amazing journey with you---

Check out our website for details on how you can become a CATALYST and spark your GREATNESS!!! www.projectcatalyst.com  Like us on Facebook at facebook.com/projectcatalyst  and follow us on Twitter: @pjcatalyst

[1]See Shereen Marisol Meraji’s article Black Americans Give Entertainment Options Failing Grades, NPR http://www.npr.org/blogs/codeswitch/2013/06/07/189603116/black-americans-give-entertainment-options-failing-grades

[2] Ibid.

Ubiquity

My final post for the Real Film Data series is coming soon, but in the meantime I'd like to share a post I worked on for VHX. For those who don't know, VHX is a platform for filmmakers on which they can release their own content, their way, for the price they see fit. I've been working as a Data Analyst with them since January and have had the opportunity to leverage their knowledge into some interesting insights.

One of those is in the following post. It pertains to how you should release a film and across which platforms. Turns out, so long as you do it right, it helps to have your content everywhere.

Exclusivity is dying. Long live Ubiquity! [Click here for the original post at VHX]

NYU Think-Tank Awards Artel Great Fellowship To Aid Underserved Film Communities | Shadow and Act

Indiewire's "Shadow and Act" featured 2014 CRI Fellow Artel Great this week, delivering an interview in which Artel outlined his plans to reach underserved film communities via his CRI Fellowship. NYU Think-Tank Awards Artel Great Fellowship To Aid Underserved Film Communities | Shadow and Act.

As part of his Fellowship, Artel founded Project Catalyst  to "meet the needs of passionate, emerging communities of color who yearn to be inspired by new productions of culture that they can take pride in." Project Catalyst will serve as a platform that leverages technology, performance, and exhibition in the service of media diversity.

This is just the beginning for Artel and Project Catalyst - stay tuned for updates and invitations to events!

Real Film Data (Part 2: VOD)

In my last post, I discussed the difficulties of getting data from theaters, primarily due to misaligned incentives. It is not due to malicious intent per say, rather that the costs of data collection and analysis do not contribute substantially to their bottom line. In the distribution window I will talk about today, I'm going to continue to follow the money. This will give a picture of where the incentives lie and why filmmakers get left out.

Warning: This is going to be a long walk, but important in understanding where filmmakers and their representatives have different objectives. So hang in there! For those of you who aren't here to read, the next little bit a nice summary.

tl;dr - Platforms like iPhones, Netflix, and Comcast have the data we want, but as filmmakers our only link to them is through a distributor who has no interest in risking the loss of their value proposition by pushing for data transparency. Thus, it's up to filmmakers to find different strategies for getting data about their audience. These strategies are things are what I will be exploring in the next quarter of my fellowship.

VOD

The Video On Demand space consists of two separate models, Transactional VOD and Subscription VOD. The former is a one time payment that allows for the purchase or rental of video content. This includes both cable providers such as Comcast and Time Warner Cable (soon to be the same company) and online marketplaces like iTunes and Google Play. Subscription VOD consists of Netflix, Hulu Plus, and Amazon Prime who offer a library of content for a monthly or yearly fee.

Now that we've gotten the boring stuff out of the way, let's move into the fun part: cash money!

None of the platforms mentioned above will just let you throw your film on their service. These companies like to have some arbiter of the content that makes it on to their service, both to reduce their overhead in managing the films and also to ensure only the highest quality films are shown.

There are two ways to get your film on a VOD platform, either through a distributor or through an aggregator, each of whom has a different way of making money off of you.

Distributor

Distributors that work with indie film in the VOD space are numerous. Their method of acquisition is to (sometimes) offer a minimum guarantee to the filmmakers in exchange for rights to put the film up across multiple platforms. This MG is an upfront payment to the filmmaker that must be recouped by the distributor before any revenue from the sale of the film returns to the producers. Furthermore, distributors must also recoup the costs of advertising, marketing, and other services in advance of returns to the filmmaker. Finally, they take a split of those profits as well, generally between 25 - 40%.

If you sell your film to a distributor like IFC, for instance, they are likely going to ask for worldwide rights for all media. This means your digital VOD rights as well as any theatrical, physical media, television, etc. Other distributors like Gravitas work almost completely on digital VOD platforms, so you will be able to retain some of your rights to other venues, but likely with no minimum guarantee.

Aggregator

If you have the money to pay upfront, an aggregator like Distribber or Quiver will take your film, ensure quality to the necessary standards, package it with other films, and put them on various the VOD platforms. Because you pay them, they do not own any rights to your film and do not take share in profit participation. 100% of the sales that come in go directly to the filmmaker.

The cost for these services are usually between $1,000 - $2,000 and increase depending on the number of platforms you'd like the film be for sale/view. If you want in available on all satellite and telco platforms, this adds roughly $5000 to the cost.

Example

What is the benefit of going with distributor vs. that of going with an aggregator? In a frictionless market, this question is complicated but not impossible to estimate. Let's use online transactional VOD only and assume platforms are taking 50% of the sales. For a movie priced at $10 dollar, there is a clear point where one see the benefits of an aggregator over a distributor.

In this case, selling more than 1,600 copies results in a better outcome by going through an aggregator. Something certainly attainable for a film with decent marketing, publicity, and word-of-mouth.

So this is the answer, right? Plug in these numbers, get an answer as to how many units you'd have to sell, and make your decision. How easy!

Not Even Close

In the example, I mentioned something about "frictionless markets." Basically this means that all methods of putting content out there are equal and none is subject to any benefit or harm that isn't experienced by the entire market. Turns out, this is where distributors exhibit their leverage.

As businesses, they have relationships with platforms and can lobby for better placement of their titles and, depending on the platform, more favorable terms. And the difference between landing on the front page of iTunes and being buried under hundreds of other films can make a huge difference to your sales. So while 1,600 copies may be the break even point, a good distributor will shift the playing field in your favor to ensure you get more sales than you would without them.

You may be asking by now, "What does any of this have to do with DATA?!?" Well, now that we have walked through the value proposition that a distributor offers over a DIY model, we can talk about how that value proposition keeps them from getting filmmakers the data they need.

Why You Get Nothing

There are three points here. First, distributors' marketing arms are not concerned by and large with the film's audience, but rather with the platforms (iTunes, Amazon, Cable Providers, etc.) In order to pay off their value proposition, distributors have to be able to convince these other companies to act in ways that are advantageous to them, such as placing their titles in front of more people. Notice I said "more" people, not necessarily the "right" people.

Secondly, and stemming from the first point, is that distributors have not been pushing for data regarding the audience that purchases the film. This is because the platforms run by cable companies focus more on service uptime and connectivity than user interaction. Those run by tech companies flatly do not share their data.

And perhaps most important of all, were a distributor to expose to a filmmaker ways to measure and connect with an audience, the would immediately weaken their own position. Distributors would like filmmakers to believe that they have some expertise in finding an audience for a film and would suffer greatly if the creators could speak directly to an audience.

For these reasons, the data filmmakers want is either not being collected or not being released. Information about a film's audience on VOD is therefore kept by entities that the filmmaker never directly works with (platforms), and their ambassador to these companies (the distributor) has no incentive to push for transparency.

Unite!

As filmmakers, what can we do? First, we can begin to share the data we do have. Knowing what data is out there, and how little there is, will begin to motivate new filmmakers to demand more. Secondly, we can migrate to platforms that are more transparent with their data. Which, coincidentally, will be the topic of next week's post.

Stay tuned!

New web apps off Rotten Tomatoes' API

You and a friend are talking about a movie. It looks great. Rotten Tomatoes says it's fresh. Inevitably, one of you will say, "I really want to see that!" For every time you say that, how many times did you actually buy the ticket? Would you if you knew it was leaving the theater soon? This week, my focus shifted from pricing to the movie consumer's decision process. There are multiple pain points, but for the purposes of this week, the focus was information. It's not effortless to keep track of what movies are still in or not in theaters. Plus, if you aren't sure what movie you want to see, but just want to see something, a quick-and-dirty display might be more effective than a comprehensive, detailed display.

Here are two quick web apps off of the Rotten Tomatoes API that might help. The first is called QuickRT. It's a quick snapshot of current releases and how their scoring, presented in a simple, user-friendly design.

The second web app

is a sand timer for movies. It's the result of my final project for an ITP class. Here's a snapshot:

CRI Post #3.2

First, it grabs all the in-theater moves from the Rotten tomatoes API and filters out movies greater than 90 days old and rotten movies, leaving only the best and freshest. Then the movies are sorted by how long they've been in theaters. The current display is "90s chic" but it could be redesigned to a user-friendly, visually appealing design. "Almost gone" movies could be displayed in red boxes, "On-its-way" movies in yellow boxes, and "Just in" movies in green boxes. Would knowing a movie is almost gone entice you out of couch inertia? While this feature might not be baked into the final product, it's a start to understand how movie habits might be shifted. The app assumes that most people want to see movies that are "certified fresh." It certainly doesn't account for dissatisfaction with the movie itself. After all:

CRI Post #3.4

Risk, Normalization and Building a Sandbox

Constructing a useful film index amidst a constant fluctuation of industry conditions feels a bit like drawing a box in the sand on a windy beach. Any grains of data that fall within the box would be included in the index because of their perceived usefulness toward projecting future performance. However, with current viewing habits and production and distribution practices continually shifting, the outline of that box continues to transform. I’m currently concentrating on two key challenges in defining the boundaries of the sandbox: normalizing the index scoring system and distinguishing films according to their level of risk.

Normalization of the index score

Simply looking at box office performance at a given point in time tells you very little. It tells you something about the strength of titles currently in theaters. It tells you a lot about the importance of the release cyclicality (i.e., Thanksgiving and July 4 weekends are huge overall ticket sellers), which then becomes a self-fulfilling prophecy for distributors planning their release timing. Film investors fully expect to see ticket sales spike in at certain times because that’s what they’ve consistently done historically. But they need more context to begin to understand more about performance of specific titles and categories.

Scoring this year’s data against the same week from the year prior begins to give a little more information. I’m of the belief that comparing the current year to anything further back than the previous year would begin to warp the conclusions one might draw. For instance, consider how much Netflix, HBO Go, Hulu and other platforms have shifted viewing patterns over the last two years. To blindly weigh 2013’s July box office performance against 2005’s would be to compare two very different environments and would confuse or mislead any investor trying to draw meaningful conclusions.

Many other forms of normalization will likely need to be employed as I develop the index’s underlying formula – analysis of the statistical significance and reliability of each type of data available will help lead toward meaningful normalization factors. For instance, I might account for inflation and/or remove 3D titles from consideration. Eventually, a model might be able to account for more nuanced factors like macro weather patterns and events. In the end, simply comparing one year to another provides limited information for many reasons. Release patterns are in constant motion. Aside from several standard big weekends, which are likely to remain bellwether box office indicators, releasing a specific film during a specific week tends to be based on a host of considerations unique to that period. Not to mention the fact that holidays don’t appear as the same “week” each year. When viewed as a graph, this calendar variation will create peaks and valleys that don’t make sense in comparing two years. Such a comparison also doesn’t speak to the actual volume of revenue earned. Clearly, while scoring one year against another can provide certain information, it is only one tool in the toolbox.

BO Compare

To the left is a basic representation of 2013’s weekly box office as compared to 2012’s. Any positive percentage indicates 2013 performed better that week than the same week in 2012.

* For those curious about the pre-Thanksgiving dip, 2012’s opening of Breaking Dawn, Part 2 dwarfed anything 2013 had at the box office that week.

Risk categories

A common factor used to categorize various investments is level of risk. Risk level is a core consideration for investors, who need to be able to compare other holdings in their portfolio with the one under consideration and weigh the entire basket against their overall risk tolerance. Film investors attempt to identify these same risk characteristics as they relate to specific projects. Sophisticated film investors attempt to create diverse portfolios to try to ensure several flops don’t overshadow the hits. A film portfolio, typically referred to as a slate, is not a new idea. However, successful film slates are not nearly as common as lauded mutual funds because visibility into specific films’ actual level of risk is typically not great.

Rather than getting bogged down with limitations of identifying real projects to make up a film slate, I want to first describe the categories I might employ, using stock category definitions as a model.

- The least risky category of stocks is often referred to as “income stocks.” These are typically thought of as slightly higher risk and return potential than bonds. Utility stocks are in this category, since investors have faith that people will continue to need things like electricity and water.

- “Value stocks” are those that have historically been a good investment and which are thought to be undervalued at their current price. The idea is that buying undervalued shares allows you to enjoy additional upside as the price returns to its proper level.

- Stocks with strong historical and projected growth rates are categorized “growth stocks.” Investors expect a strong return on equity with these. Many technology and alternative energy stocks are placed in this category, assuming they’re at a scale offering reasonably low volatility and established enough to have historical data to reflect a trend of high growth.

- Then there are riskier types of investments, including smaller companies with no proven track record or significant market presence and companies from emerging markets. These investments are exposed to a higher than average level of volatility due to lack of liquidity, political and currency issues that might disproportionately affect them and generally uneven growth, often due to their small scale.

Sandboxes

I believe there are some analogies to be drawn between risk categorization in films and stocks - translating these definitions may help me in drawing lines around films for my own index. Once the boundaries themselves are clearly defined, determining the content to be included within becomes much easier.

Misanthropes should go to movies on Tuesdays

The movie theater business is a weekend-centric one. It’s no surprise that movie tickets sold on weekend (Friday to Sunday) are triple the number sold on weekdays (Monday to Thursdays). To better define what type of dynamic pricing this project will pursue, I dove into data about attendance by date. The trends of the past tend not to chart the course of the future, but I hoped the data would yield some clues.

There are two primary sources online – BoxOfficeMojo.com and BoxOffice.com. I chose the former because the site also includes a cornucopia of data on attendance per title per date that will be helpful going forward. The data set is estimated tickets sold (top 10 gross divided by average ticket price) by day of the week from 2002 to 2013. Total estimated tickets is preferred, but since the top ten movies account for as much as 90% of total gross, most courts would say it’s a pretty solid dataset for industry trends. Here are the results:

CRI Post #2 Weekday Top 10

CRI Post #2 Weekend Top 10

Source: BoxOfficeMojo.com

Some takeaways:

-Ticket sales averaged lowest on Tuesdays. One of the most surprising trends is that over the last two years, ticket sales on Tuesdays have ticked up. It’s not clear if this is a shift from folks tired of wrestling with large weekend crowds.

-Ticket sales are highest on Saturdays, followed by Friday and Sunday.

-Monday and weekend attendance trends are fairly stable

-Tuesday, Wednesday, and Thursday trends show fluctuation and volatility (as confirmed by calculating standard deviation)

-Wednesday ticket sales have been the most volatile over the last decade.

If a dynamic pricing model does not cannibalize the preexisting audience, especially the weekend crew, a scheme focused on Tuesday-Thursday tickets for non-blockbuster event movies may capture extra demand. The goal and the big question remains: how can we grab those that hadn’t planned on going to the movie theater at all?

Real Film Data (Part 1: Theatrical)

The theatrical film market is dark and filled with terrors. At least I think that's how the quote goes. By "dark" of course I mean in regards to data. The purpose of this blog post is to look into who has data about audience theatrical viewing habits and whether filmmakers are able to access it. While we live in a world where a good number of our actions are tracked, calculated, and processed so that our actions will be better understood, 94% of people still walk up to a theater, pay for a ticket, and watch a film without another soul in the world knowing they did so.

Privacy advocates may love this homespun tale of a world without information, but to filmmakers it is incredibly troublesome to find yourself lacking the knowledge of who your audience is.

Currently, there are a few groups of people who have information about theatrical audiences:

1) Exhibitors - First off, it's important to understand how theaters make money. Concessions! Because studios take almost all box office revenue from the first week of a film run, theaters have to charge a massive amount for food and drinks just to stay in business. That's why the single most important metric theaters track is called "per-head," which measures amount spent at the concession stand.

If you are a member of a rewards program, however, congratulations! You've just exchanged your data for the occasional free bag of popcorn.Companies mostly use loyalty programs to keep customers coming back, but also to collect and understand their purchasing behavior.

As a filmmaker, you get none of this.

2) Ticketing Websites - Sites such as Fandango and MovieTickets.com* will presale tickets to a film, therefore knowing quite a bit about you (email, geographic information) and will use this to directly market to you. They do a pretty scatter shot job, as most correspondence is through non-targeted email campaigns. That said, they have demographic, geographic, and direct contact information for actual customers, and may even be able to draw more information about them through site interactions.

As a filmmaker, you get none of this.

* Fun Story: Fandango is owned by Comcast; MovieTickets.com is a joint venture by many companies, including AMC theaters, Viacom, and Time Warner. If you think they are in any way interested in sharing data with filmmakers, well, just wait until we get to TV...

3) Tech world - Finally, some people that might be interested in helping filmmakers. Some are specifically film based like Moviepass. Their subscription service allows users to pay a monthly fee for the ability to use a pre-paid debit card to pay for movie tickets.

In order to use the service you have to have a smart phone with their app, which uses your location to "check-in" to a theater, thus allowing you to purchase the ticket with their card. This gives Moviepass direct information about who is seeing which films and where in real time. They also have an in-app ability to invite friends, which allows them to track word-of-mouth. Unfortunately it seems like Moviepass is more interested in selling this data to studios and theaters than directly to filmmakers. You can check out a great primer on Moviepass and their value add by clicking here.

Taking a step back from film-centric apps alone, location-based apps like Foursquare could be helpful, allowing mobile users to check in for specific events at a given location.

Imagine that for a second. Someone checks in to a theater for your movie. You can then see where else they have checked in begin to make strong conclusions about what type of person this is. In the aggregate, this allows someone to forecast what types of people see what types of films and be able to types of places they most frequently eat, shop, and spend time.

I hope that the use of existing data sets alongside newly created technology will be able to utilize what is available from these newer models of data collection.

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Of course the largest issue with all of these methods is that they take place after the film has been released. They might be able to help a smaller platform release target its marketing as it grows from city to city, but at that point a shift in strategy can do more harm than good.

However, if we begin to study the actions of an audience over time using platforms like the ones mentioned above, we can aggregate data to expose patterns of behavior. Once we do that, we can define films in such away to exploit those patterns and put films in front of their audience first without breaking the bank on advertising.

Is Hollywood Out of Touch?

Take a look at the unusually high number of recent box office failures and the problem becomes clear.  Hollywood is mired in a big budget, post apocalyptic, superhero, robot, sequel, prequel, 3D, blockbuster, comic book film cycle.  Yet, since last May (the start of the film industry’s high-stakes summer season) Hollywood has sustained several big-budget flops including, Jeff Bridges’ R.I.P.D., Will Smith’s After Earth, andJohnny Depp’s TheLone Ranger, just to name a few.

ripd

After

the_lone

It is my contention that today’s moving-going audiences have been beleaguered into a Hollywood induced state of mega-budget, remake, sci-fi, CGI movie fatigue.  This problem is even more pronounced in many multicultural communities as Black, Latino,  Asian-American, and Native-American experiences rarely find voice in such Hollywood blockbusters.  Even further, over the last fifteen years, there has been a steep decline in the sheer number and variance of multicultural films on the silver screen.  This reality is in stark contrast to say, for instance, the burgeoning Black cinema that produced a successful wave of talent,  highly acclaimed, and financially successful films in the 1990s.

Many of these films were financed by Hollywood studios, as well as independently, and were helmed by Black filmmakers who presented diverse stories that were multivalent, powerful, and reflective.

A few prime examples include: To Sleep With Anger (Charles Burnett, 1990),  the teen comedyHouse Party (Reginald Hudlin, 1990),  Julie Dash’s epic Daughters of the Dust (1991), which became the first feature film directed by an African-American woman, the animated comedy Bebe’s Kids (Bruce Smith, 1992), the Black westernPosse (Mario Van Peebles, 1993),  the film noir period piece, Devil in a Blue Dress (Carl Franklin, 1995),  the college-based drama Higher Learning (John Singleton, 1995),  the feminist leaningWaiting to Exhale(Forest Whitaker, 1995),  the family oriented Soul Food (George Tillman, 1997),  and the humanizing Black romanceLove Jones (Theodore Witcher, 1997).   I could keep going, but I’m sure--- you get the point!

love-jones1

waiting

In today’s media marketplace, however, this type diversification in cinema has ostensibly evaporated as, journalist Michael Cieply points out in the New York Times, " New Line Cinema, Warner Independent Pictures, Metro-Goldwyn-Mayer and other companies that specialized in midbudget comedies and dramas have shrank or disappeared."  Consequently, for many multicultural audience members (read Black, Latino, and Asian-American) the basic enjoyment of Hollywood films has been harmed by the limited and often regressive roles reserved for nonwhite actors (read slaves, addicts, whores, thugs, caricatures, or men dressed in drag--- ehmmm, Madea).

bebe

While there is, indeed, nothing inherently wrong with slapstick comedy or the recent wave of slave films per se, there is, however, a burning desire for more variety within multicultural communities to see films that just do--- more!   For many people of color it is virtually impossible to find a Hollywood film containing the stories of love, dignity, laughter, struggle, redemption, intelligence, and humanity that reflect the fullness and diversity of our lives.

 With this in mind, my work with the Cinema Research Institute (CRI) this year is aimed at interrogating and challenging the antiquated notions of dominant cinema.   My research is aimed at excavating innovative film distribution strategies to address issues of diversity in media culture.  Not only for the benefit of underserved communities (Blacks, Latinos, Asian-Americans, and Native-Americans) but also for all audiences who simply enjoy great stories and great films.

And so I say, to the vibrant multicultural audiences who are sadly neglected by dominant media, and to the talented and progressive filmmakers with diverse voices, and to the broader audiences who have multicultural tastes--- I see you!!!   I know you’re out there (despite what Hollywood purports) and together we will make a positive impact.

After all, I real(eyes) great ideas can change the world, but it requires great people to make it happen.  That’s why I’ll need your help. I thank you in advance for your support.   And I look forward to traveling this amazing journey with you!!!