Inside Amazon’s Open-Source Original Content Strategy

Roy Price, director of Amazon Studios, talks to Co.Create about the company’s new original shows, how users help decide what gets made, and why relying solely on data is no way to develop content.

Inside Amazon’s Open-Source Original Content Strategy

In December, while Netflix was gearing up to make its 2013 programming splash with House of Cards and Arrested Development, Amazon was also busy greenlighting six comedy pilots that are now in production. Five of the pilots were commissioned via traditional methods, with writers like former Daily Show head writer David Javerbaum, comedian Kristen Schaal, Doonesbury creator Garry Trudeau and others submitting scripts to Amazon via their agents. Casting is already under way for the pilots–John Goodman will star in Trudeau’s entry, Alpha House, about four U.S. Senators living under one roof.


The other pilot, Those Who Can’t, about three teachers who are more immature than their students, was submitted via Amazon Studios. All of the pilots will be posted to that site this spring and, based on user feedback, the studio will pick which pilots will be made into series and made available via Amazon Instant Video. Currently, Amazon Studios is deciding on movie projects in a similar fashion, with users commenting on trailers and animatics from the filmmakers of approved projects.

Roy Price, director of Amazon Studios, has been through the traditional development cycle–he ran programming for Disney TV animation–and after helping Amazon get its highly successful Instant Video service online, has been spearheading the company’s original content efforts. Price spoke to Co.Create about the new pilots, the user feedback process, and what data can and can’t do.

Co.Create: What was the process behind Those Who Can’t? Did the creators actually take feedback from users and modify their script or how did that work?
Roy Price: You know, the key to getting large-scale feedback from people is to make something visual. There just aren’t a ton of regular people who are going to read your script and give meaningful feedback. Right now, the process of identifying promising scripts is driven in a somewhat traditional process where we select those projects, we invest in them and make them visual, and then customers get to weigh in. One way to look at it is it’s hopefully kind of the best of both worlds in terms of combining what is good and value-add about having experienced television executives and enriching that with more customer feedback. But that said, as we look forward, we will always be trying to find opportunity to get customer insights earlier in the process.


When you’ve done this with the movie projects you’ve put through this system, what have you learned from the user feedback in developing those projects?
RP: We have a couple formats that we present movies in. We can do a test movie, which is full length; usually a storyboard, sometimes live action but it has full dialogue, tracks of music, sound effects. So it’s a version of the movie. Then as an alternative, we have something called a mini-board. It’s almost like a motion comic of the movie. We’ve done a few of those and we have a few more coming shortly. Those are really interesting because as people go frame to frame in the storyboard player on Amazon Studios, they have the opportunity, as they click forward, to click the green button, the blue button, or the red button, which simultaneously moves them forward through the story and also indicates whether they’re enjoying this particular section or they’re not enjoying this particular section or they’re kind of neutral on it.

So it’s like the dials you see in the feedback sessions that networks do when they do audience testing?
Yeah. It’s like that but on a frame-by-frame basis. It’s been very interesting to go through some of the feedback on the three storyboards that we have up. One is that there are a lot of people who are interested in looking at movie ideas in an earlier phase. That’s very encouraging. You get some idea when you see that one of the projects just gets a lot more clicks than the others. That tells you something about its marketability. But then as you observe people’s feedback over the course of the story, that tells you something about how the actual story is working out, as opposed to whether it’s a marketable concept.

What are people saying about the the aspects of stories that they’re liking or not liking?
Well, there are some aspects that they find intriguing or exciting and other story beats that they don’t find credible or that don’t ring true for them. Maybe if the story seems to be sliding and not making forward progress, people definitely point that out in the comment section. In the storyboard player there are the buttons I described, but then if you like you can also write a comment on individual frames. It’s not visible to other people but it goes to us. So you can put together all those comments and definitely get a sense for where people think it’s taking a right turn or taking a wrong turn, having a little soft patch.


Does that feedback inform where you’re going to tighten things up in the story?
Definitely. It’s very helpful. I mean we can read it and do our own nudge but it’s very, very helpful and it’s what is distinctive about our process–to be able to have actual movie-goer feedback at the stage where you’re still in script. Usually, you’d be getting that feedback as you were standing in the lobby of the Mandarin theater at your test screening, having already invested $80 million. So I’m very happy to be getting that feedback now instead.

Going back to the TV side, first of all, why comedy and animation and not drama? What stuck out about these pilots that made you say, “Hey, these are the ones we’re going to try out in this system?”
I think a lot of people like comedy in general and a lot of Amazon customers certainly do. But I suspect over time we’ll pursue a variety of genres because that reflects customer interest and enthusiasm. I think to stand out a show has to be really well executed, it has to have a really distinctive vision, characters that you really want to follow and spend time with, and in general a show that really stands out from the pack. That’s more like what we’re looking for. That is what the shows have in common. They’re doing well on Amazon.

So something like Alpha House is hilarious but it also has a depth of insight about that community that Garry Trudeau of course brings. A show like Browsers is really fresh, young, literally a breaking-into-song musical comedy that feels very new and engaging and fun. The characters I think are really relatable and interesting. So all of them have something really distinctive about them and something that customers could really get attached to.


What kind of feedback are you looking for from the users that will let you know that you want to make the pilot into a series?
Are people interested in the concept? Are people interested in the character and in watching subsequent episodes? Does the pilot episode sustain interest? I think all of those expressions of interest and enthusiasm will be important in making the decision whether to send something through a longer order.

How are you going to get this kind of feedback?
Well, these are videos so we don’t have the frame-by-frame buttons that we have on the storyboard player. But of course, we do have ratings and reviews. We can observe how many people watch each one. So all of those will be part of the mix in terms of understanding customers’ reactions to each show.

You had mentioned in previous interviews wanting to avoid bombs by using this kind of method and using some of Amazon’s data. Are you concerned that “bizarre genius” type of shows–like Louie, for instance–are not going to make it through this filter?
I think with any kind of feedback or research you have to interpret it intelligently. There may be shows that have a smaller but very intensely committed following. I think you want to be open to that and try to perceive where it might exist. Let’s just take a theoretical show where a number of people did not take to it but then there was one part of the audience that just loved it. Well, you’d want to take that into account. If there’s a really passionate following, that might be a good choice. As I’ve said in the past, the only thing that really helps in this context is to have a great show, whereas, it’s not that helpful to have an okay or pretty good show. You really want a great show that people love. That’s what makes the difference in the current world where you reach out to find the programming; it doesn’t reach in to find you.


A lot’s been made about how Netflix has used data to try to figure out what its audience is going to want. Obviously, Amazon has a massive database. How will that come into play when it comes to either selecting the pilots or in the selection of the pilots that go to series?
Well, the data might be telling us that green cars, live-in housekeepers and men born in August are incredibly popular. You know, I think there are a lot of ways to use that and there are some ways to misuse that kind of data. You have to be careful about observing someone who was an extra in Transformers and Iron Man and now the computer tells you that they’re the most popular actor in America. Really for a show to be distinctive, over time what we’ve observed, and the data would support this, is that you have some very talented creators who are passionate about an original idea. You can certainly demonstrate over time that shows with those characteristics tend to do well. I think that’s the important lesson and the important data to be looking at. If you try to get the computer to write your script you might get frustrated.

There is a human element. It’s an art and a science. Otherwise, we would have our show called Cownton Abbey or Afternoons in Surrey about sort of Downton Abbey’s neighbors who have very similarly dramatic lives. Copying has not historically been a fruitful road to success in television. I guess we could debate that but maybe another time. You have to be careful when using historical data to observe principles more than details. You can’t, for instance, stick someone in a role that is not right for them and have it work. The key is to stick with the real qualities that make shows great. Don’t get distracted by some of the other details.

When it comes to distributing these shows, once you get a show past the pilot stage and you’ve got 10 episodes or 13 episodes, are they going to go up on Amazon Instant Video all at once?
I don’t know about that yet.


Okay. When you take a look at the landscape of how these companies are doing distribution, do you think there’s going to be a sea change that’s starting now in terms of how people consume television and the traditional cable and broadcast model is going to change drastically or go away?
You know, I’m just not really speculating about that a lot right now. Our job is to come up with some great shows that customers love. That’s what I’m totally focused on. Some of those questions are kind of outside of the scope. I’ll leave that kind of speculation to you.

How do you think this system is going to yield different shows than the traditional network models?
Well that, we have to stay tuned to find out.

What was the aspect of the traditional network and studio development model that Amazon wanted to change? What were the inherent strengths and weaknesses of that model?
Well the weakness of the model is that it’s relatively closed. Our observation was in the current situation where we can all so easily communicate with one another on a large scale, it should be easy both to solicit ideas from creators and solicit opinions from movie goers and TV lovers. Why isn’t that part of the development process? That’s why we pursued development in this particular way.


About the author

Joel Keller has written about entertainment since the days when having HBO was a huge expense and "Roku" was just Japanese for "Six." He's written about entertainment, tech, food, and parenting for The New York Times, TV Insider, Playboy, Parade, and elsewhere.


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