Legen…wait for it…dary…

With the rise of online, digital and social media marketing, it is incredibly and increasingly difficult to cut through the clutter and reach one’s target consumer. This is even more pronounced in the entertainment space, where the overall number of theatergoers is on the decline, blockbuster movies dominate and battle with each other for audience share, and smaller budget films just do not have the marketing horsepower to compete with blockbusters.

Legendary Applied Analytics (LAA) was founded in 2013 as part of Legendary Entertainment as the “Moneyball for Hollywood” with the goal of using statistical analytics to put an entertainment product (Legendary Pictures) in the best position to succeed. In order to achieve this, LAA’s method involves identifying viewers who resonate with the topic, finding the most effective advertising messaging to engage them and converting them to paying consumers. So far, LAA has been successful in innovating on traditional marketing methods to push their products to succeed in an increasingly crowded digital world.

LAA primarily creates value by providing higher return on investment for its client’s marketing dollars by employing lean A/B testing across online platforms. LAA aggregates and owns data (such as name, addresses, social media handles, interests, habits) about the population from lenders, retailers and social networking sites. For a particular movie, its proprietary analytics identifies and test thousands of different mini ads (messages, images, teaser trailers, etc.) with consumer groups and traits to determine response and efficacy of campaigns. It picks the winning messages and delivery channels to design marketing campaigns for the product. Then, these are scaled and distributed to the wider population or they may choose to more targeted messaging to deepen engagements with focused groups.

However, the efficacy of their methodology will still highly depend on humans and marketers asking the right questions, selecting the right consumer parameters, and designing the right tests to run.

In addition, for Legendary Pictures, LAA also uses its database and analytical capabilities to advise on which movies to make, which actors to cast and when to release movies. In order to determine if there is an audience for the movie’s particular topic or point of view, LAA scours social media sites to determine the rhetoric and tries to estimate how big the audience is prior to a movie being made.

As they were building out their capabilities and business, LAA worked primarily for Legendary Pictures movies. They now contract with other movie studios, and other industries such as carmakers, sports leagues and politicians to perform analytics work for them, employing a fee-for-service model. To further leverage the data, platform and proprietary analytics algorithms they have built out, LAA aims to grow and broaden their client base and therefore revenues.

The more projects for different clients LAA is able to run, the more learning will be achieved across their volume of testing, and the more valuable their analytics platform will be for future client projects. Additionally, the bigger their dataset is and the more sophisticated the analytics engine is for scouring the online and social media landscape, the more value the Legendary Analytics platform will be able to create for both internal and external clients.

Looking forward, prospects are bright for LAA; it has the potential to grow and scale significantly: many companies across industries are searching for more effective ways to deploy their marketing dollars.


Sources: https://www.bostonglobe.com/business/technology/2016/03/31/making-movies-moneyball-way/Uzgwh2cdGthA1N3nZHqz0N/story.html; http://data-informed.com/big-data-takes-a-star-turn-at-legendary-entertainment/


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Student comments on Legen…wait for it…dary…

  1. Thanks, Ophelia. Very interesting post. I didn’t realize that Legendary was engaged in this type of business.

    The idea of using analytics and crowdsourcing to determine new movie ideas is a thought-provoking one, and we certainly talked about it at a lot at Warner Bros. The Kickstarter campaign which ultimately funded the Veronica Mars film released in 2014 was a pretty unique example of this—the film project raised $5.7 million through Kickstarter donations, providing “proof of concept” that fans were highly engaged and were willing to contribute financially to support the film being made.

    I think the challenge for filmmakers, however, is that even if you know that your film has a huge potential market, the actual creative content and execution of the film will still drive the box office; to a certain extent, even box office projections are relatively unpredictable, even after studios have tested the film with sample audiences. I think it is probably very difficult to prove value-add with these analytics services, especially because it isn’t clear what the “status quo” case would have been if a film had been released on a different date or had a different cast. To that point, how successful do you think Legendary has been by using LAA’s technology? (And is it partially responsible for giving us The Great Wall and Warcraft?)

  2. Hi Opheliac–

    First, this is beautifully written. You certainly have a way with words. I also love the pseudonym. Very clever, and gives me ideas.

    Now, about Legendary…

    The idea of a “Moneyball for Hollywood” SOUNDS great, but at the same time, I wonder how many more of these marketing / data analytic companies the world really needs. Many organizations, large and small, now have their own internal analytic teams, and externally, you have everything from large consultancies to small boutique analytic companies that I’m sure have more than enough data to play around with.

    Not only do I think the market is oversaturated with marketing / data analytic companies (this is purely speculative; I could be wrong!), but with the internet and open source platforms, I also think there already exists so much public data that companies either don’t know about or simply overlook.

    I would like to see companies get more creative with the wealth of information that’s already out there, and I would like to see companies stop thinking about breadth (“let’s just get as much information as we can and then figure out what to do with it!”) and more about depth.

    I thought that was the way LAA was going, until I read the part in your blog post about expanding the organization’s capabilities to carmakers and politicians.

    Interesting how you can be so positive about LAA’s future. As a division of Legendary Entertainment, I suppose it won’t be going anywhere anytime soon. But if it were a standalone entity, would you still consider it a winner? And does scaling really enhance LAA’s value proposition? That is, does expanding LAA’s capabilities beyond entertainment differentiate it more or less from other data analytic organizations?

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