Your Brain On Film

One of the hardest things to do is convince someone that experiences can be (at least partially) objective. This is especially true in the arts, where the most passionate fans and critics tend to have deeply held personal beliefs about the qualities of the art they observe. This makes it especially difficult for someone like myself who tries to find the commonalities within film and use them to predict what someone may like or dislike.

There is no way that I can predict with any real accuracy how another human being will respond to a film, right? I mean, since we're all such unique, precious snowflakes.

As it turns out, our brains present the opposite argument. In much the same way our occipital lobe is active as we sense visual activity, so to do certain areas of our brains respond as we watch a film. And according to Uri Hasson, a psychologist at Princeton, they activate in pretty much the same way for all of us.

Hasson showed an audience a scene from (the incredible) The Good, The Bad, and The Ugly and measured the viewers brain activity using a functional MRI. He saw that the same parts of the participants' brains lit up when responding to the film. When doing this experiment with Dog Day Afternoon, "there was a significant correlation in activity across nearly 70 percent of [the particiants'] cortex." 

What does this really mean? Well, much of the similarities in brain activity are related to things like visual and auditory cues. Audiences of highly directed narrative films tend to look at the same places and listen for the same things all at the same time. Not quite as foreboding as it first appears, but there are plenty of other areas of the brain (more devoted to high level thought) that are also activated.

People often scoff at the idea that films have personalities, and as such can be parsed into chunks that can be used to find an audience. But consider the fact that, for some films at least, most people have identical patterns of brain activity. And if we determine that someone enjoys a film that activates those areas of the cortex, could we assume that different films with similar effects would also be enjoyed by that viewer?

Of course I'm not advocating that everyone step into an fMRI machine in order to get movie recommendations. To me, this study simply provides the foundations for the idea that, maybe, audiences are more similar to each other than they are different and there is a better way to explore those similarities. 

Film Personality

The following was originally written for the VHX Developers Blog as part of a writeup about a "Hack Day" project where employees are encouraged to explore a project that interests them. I used this time to develop a working MVP to determine Film Personality for already released films.

As the resident data scientist, I get to do a lot of interesting things, mostly centered around understanding how to make our platform better for our publishers and their customers. But for our last hack day, I was looking for a way to better understand the content itself. Enter Film Personality.

FILM PERSONALITY

The ideas stems from something in Brand Strategy called "brand personality," which postulates that there are five major dimensions of personality: Excitement, Sincerity, Competence, Sophistication, and Ruggedness.

Sounds a little hokey, no? While reducing all human traits into five dimensions isn't a great way to describe people, I thought it might serve as a better shorthand for discussing films than the current standard of genre, where the description "Drama" could apply to almost anything (so long as no one is enjoying themselves.)

There are a few key elements needed for putting this together: A common language used to describe films, enough people using this common language, and the ability to quickly parse their conversations to extract the key descriptive words. I found it useful to consider critics' reviews as that source of common language. They say similar things about similar types of films, even if they disagree on the quality of the film. The use of words like "exciting," "intelligent," and "imaginative" are still used, even if the critic then follows it up by saying, "but I still hated this movie."

I figured the simplest way to test this out was to use the Rotten Tomatoes API to pull in reviews for a given film and parse those using the lovely Python package Natural Language Toolkit, or NLTK. I'll walk you through a bit of the code, which turned out to be surprisingly simple for an MVP:

The first API call to Rotten Tomatoes returns the JSON of the movie the user requested, based on matching title. It's dependent on two things: 1) the Rotten Tomatoes search, and 2) that the user actually spells the film title correctly. Once we have the movie ID, we call the API again to get the reviews.

Once we get the JSON containing the review snippets, we need to tokenize the parts of speech using NLTK. This returns a list of tuples, each containing an individual word paired with an identifier ('NN' for nouns, 'VB' for verb, etc.) The parts of speech that will be most descriptive of the film's personality are verbs in the gerund form, that is ending in "-ing," and adjectives.

In order to associate these words with the film dimensions we defined earlier, I created a small dictionary including some seed words and added synonyms from NTLK's Wordnet synonym set. I also removed the words "good" and "bad" because that's, like, your opinion, man.

What we get when we run all this madness is a list of descriptive words from the reviews, and a score for each of the five dimensions. While this is currently nothing more than a proof of concept, it shows that we can mine this data for specific words, link those words to personality dimensions, and that this dimensions actually align with our conceptions of the films that are input.

There are definitely areas for improvement. The dictionary needs to be much larger to account for more words, and I would love to bring in full reviews rather than just the snippets from Rotten Tomatoes. Hopefully these iterations will show that there is a better way to define films, and that perhaps film personality is it.

Grouped: Marketing for the share of information

I recently read Grouped: How small groups of friends are the key to influence on the social web by Paul Adams, a social researcher at Facebook, and I’d like to share a few of the important takeaways from what he found. I apologize in advance for the very Bob Lefsetz-style of this post. Changing Consumer Behavior

“[People are] spending less time interacting with content, and more time communicating with other people”

Think about what you do most frequently on the internet. Is it typically a search for products, news, and information? Or is it specifically to see what your friends are up to and talking about? Whether it is checking photos, comments on the news of the day, or social gaming, more people are interacting with other people than they are simply consuming content.

The film industry has had a terrible time of trying to integrate social sharing and experience into the industry, it will be something absolutely necessary for the success of the next generation of content.

“Most of our consumer behavior models are structured this way— people acting independently, moving down a decision funnel, making objective choices along the way. Recent research in psychology and neuroscience shows that this isn’t how people make decisions.”

The general concept of customer acquisition in marketing is based on a funnel. People supposedly convert from the larger to the smaller end of the funnel and those that make it the whole way are your customers.

New-Marketing-Funnel1

Turns out “the classic sales funnel is based on a view of humans as rational thinkers, making rational decisions as they move down through the funnel…. is simply not true.” Human being are influenced far more by emotion that ever accounted for in standard economic models. “We need instead to market towards emotion.“

Film marketers seem to know this, but only sometimes. In the four P’s of Marketing (Product, Price, Place, and Promotion,) the movie industry only appeals to our emotions with first, the Product. They seem hesitant to recognize that Price changes will become necessary, especially as the Place changes further from theaters to homes via phones and tablets. And Promotion has to change from the current top-down “barking at customers” model to a more community-based one.

“We share feelings, not facts”

Adams goes on to state “this included positive emotions such as awe, and negative emotions such as anger and anxiety. Emotions that were not arousing, for example sadness, did not trigger sharing of content.”

Could this be why dramas are typically so much harder to market than spectacle-based action movies or horror films? It is, in my opinion, why the trailer for Gravity was so effective. It spoke to viewers on an instinctual level of fear and survival. Not that every film can do this, but the even the ones who could don’t seem to understand the simple fact.

“Reason is dependent on emotion.”

Not only are feelings important in what we share, they are actually important in what we chose to buy and not buy. “Research has shown that offering people a smaller immediate gain activated different neural systems in the brain than did offering them a larger gain in two to four weeks.”

Think about this in terms of crowd funding you film. You can offer rewards to backers, sure. But what if you can provide Instant Gratification in the form of a small video as soon as they support your project. That is just one example of understanding the intricacies of human behavior that result in increased audience engagement.

Speaking of which, before you can speak to an audience in the right way, you have to know how to find them…

How To Reach Your Audience

The Myth of the Influencer

“Targeting large numbers of these people , potentially in the thousands, is more likely to spread ideas than trying to find a small number of influential individuals. These people won’t be visible on an individual level. You won’t necessarily know them by name. But you will know that they have the right attributes to be interested in what you have to say. Using many of these people to set off many small cascades averages out the random factor, and is more likely to produce consistent positive results.”

This is the general ethos for my research. By defining groups of similar people, similar in the right ways, we can determine how appropriate a film is for that group and realistically constrain marketing budgets. For more about this, check out my post on the cohort analysis done on the OkCupid data set.

The Real Influencer - Everyone

We tend to focus on those that have a seemingly large influence (think Oprah and her book club,) but it turns out what we should be focused on are groups of people who have a low barrier to being influenced. In other words, focus on to whom you are talking, rather than who is doing the talking about your film.

Ideas spread when people have low adoption thresholds. For ideas to spread widely, you need connected groups of easily influenced people. These easily influenced groups are called “Innovative Hubs.” Think of anyone who was an early adopter of technology like Betamax or Mini-disk players (shamefully, I was an owner of the latter.)

Innovative hubs are people who are highly connected and have a low threshold for new ideas. They embrace new ideas after being exposed to them a small number of times. The next group in the path to adoption are “Follower hubs” which are more common. These groups consist of people who are highly connected but have a high threshold for new ideas.

“As we increase our reliance on our social networks to make decisions, we won’t turn to strangers, nor will we turn to recognized experts. Instead we will turn to the same people we have been genetically trained to turn to for help— the people we’re emotionally closest to.”

Segmenting is Changing

 “Marketers currently segregate by demographics and psychographics, but in the future they’ll need to segregate by social network structure.”

The connectedness of a network is one component of prediction the spread of information through that network. The other is the ease at which the nodes in the network are influenced. These are not trivial questions to answer currently, but hopefully the work I’m doing during my fellowship will begin to increase the understanding of how to determine these metrics.

Density is as important as spread

“Focus on getting your message shared within a group as much as you focus on getting it to spread between groups…. When we’re planning marketing campaigns, we should concentrate on content that is likely to spread among friends, and friends of friends, but we shouldn’t expect it to spread to people more than three degrees away from the people who first encountered the message.”

This is the key for independent film without huge marketing budgets or publicity campaigns. You should focus on getting everyone, yes everyone, in you direct group involved and interested in your film. Only by obtaining critical mass in a small, closely connected group can you then expect to reach secondary groups.

I’m currently trying this strategy with a Kickstarter campaign for Anatomy of an American Dream, a feature documentary I am producing. Considering this as my case study, I hope to fill you in on the progress as I test these strategies over the next month.

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.

stats

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.

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.

Screen Shot 2014-04-13 at 3.44.11 PM

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.

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]

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!

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.

The real meaning of "data" in film (a prologue)

I begin most of my conversations about film these days with one topic in mind: data. As anyone who has read Moneyball will remember, access to data doesn't necessarily make for better decisions. Thus, my research is not just about getting to the data, but making sure that what we get is useable. And we have already seen some larger companies begin to do this.

Google, Apple, and Netflix make strategic and product decisions around their vast data resources. Hollywood studios have largely ignored the proliferation of data analysis, even as several individuals in the industry have made a half step toward increased data transparency. While this makes for interesting reading, what does this mean for an individual filmmaker?

Over the next week, I will be breaking down data by window (theatrical, VOD, online, etc.) and by who currently has access to that data (distributors, exhibitors, filmmakers, etc.) In doing so, I will illustrate the sheer lack of information in the industry in total. Then comes the scary part.

I will show how little of this data, both financial and marketing, trickles down to the individual filmmaker. We should care about two things after a film's release: who saw it and for how much. My next few posts will show just how in-the-dark most of us are.

There are 5 venues I will be discussing: -Theatrical -Physical Media Sales -VOD (both transactional and subscription) -TV (pay TV, cable, network licensing, etc.) -Direct Sales

Each of these exhibition avenues is a different market and poses a different set of problems. As I go through each of these areas, I'm going to treat them with a hacker's eye. I want to see how close much of the traditional system can be replicated piecemeal.

My primary question is: How can one release a film in as many places as possible while maintaining control over both revenue streams and individualized data? And what are the side effects, both positive and negative?

By the end of this week, I hope to have clearly laid out where the industry stands. This will show how far we need to go to get what filmmaker's need to be successful.

Why Filmmakers Are Crazy (and how I plan to help)

A graphical look at the the success/failure of 2013's Sundance acquisitions. [credit Seed&Spark]

Anyone who decides to produce a film, market a film, or distribute a film is taking a giant risk. If they are taking that risk with their own money, one might consider institutionalizing them. The likelihood of making your money back is exceedingly low in the independent film world. Investors spent $3 billion on the 4,000 feature films submitted to the Sundance Film Festival this year. They will likely recoup 2% on aggregate. The risk is high and even the most successful projects return revenues less than what other industries provide. This is why filmmakers are crazy. Not because they chose to enter this business, but because the business itself is broken.

I'm no Ron Swanson-esque supporter of unrestrained capitalism. But the free market at least provides a transparent link between seller and buyer. One of the largest problems in the film industry is that filmmakers do not sell to the people watching their films. They sell to distributors.

Distributors exhibit oligarchical power over market demand. Given the few number of buyers, they pressure filmmakers into selling films below market rates. Distributors go on to control the cash flows from that point on. They offer limited data on expenses and revenue, no input on strategy, and no information about the audience.

In the end, the filmmaker trades knowledge of their audience and control of their brand for a few dollars. They are playing the lottery instead of working for a living. They do this because there is no other way.

That is, until now.

There has been a groundswell in artist services over the last few years. Preproduction help in financing comes from Kickstarter and Indiegogo. Digital filmmaking has lowered production costs. Direct distribution platforms like VHX and Vimeo On Demand allow for direct selling. Each of these services aims to help the artist find their audience and engage them.

My research will hopefully propel this sea change to the logical step: direct marketing. The goal is to allow filmmakers to reach an audience based on data and exhibited preferences in purchase behavior. It is a massive undertaking, but necessary for the sustainability of the independent film market.

I will present my research in three parts:

1.   The examination of what data about audiences exists and is available, as well how to use it
2.   The redefinition of films in a more complete, actionable format around the ideas of branding and personality
3.   The connection of those films, using this classification, with the audiences who would pay to see them

By the conclusion of my fellowship I intend to show filmmakers a better way to reach their audience. I will demonstrate ways to leverage their own markets without selling their rights to another entity. Finally, I hope to create a framework that artists can follow to take advantage of new technology and information.

Stay tuned, it should be a fascinating year.