No matter the business, bold choices come with a risk. Decision makers will want to minimise this risk by consulting reliable statistics, research, and advice as early in the process as possible. This wariness of risk is amplified in the high cost TV industry, where shows can easily cost millions to produce, and audience reaction can be tough to predict.
Step forward Fred Graver, a four-time Emmy winner whose use of Twitter and Audiense has made it possible for him to reduce risk further than ever before in the creation of his new TV series, while also extracting real world inspiration for his characters.
After a career filled with major writing credits (Cheers, The Jon Stewart Show, Late Night with David Letterman), and over four years as Twitter's global head of TV, he's now turned his focus back to script writing and combined it with his interest in technology. We caught up with him to see why he thinks social data holds a pivotal role in show creation, how you can use it for creativity, and how Audiense played an integral part in his new show's creative process.
Audiense: What sparked your interest in the connection between social data and TV?
Graver: In the mid 90s I became fascinated by the Internet, totally fell in love with it. I was working at Disney, and spent a lot of time researching the possibilities of this medium and how Disney could be prepared for its imminent expansion into our society. I then moved to MTV, where I assembled the team that built the first website for VH1 and achieved some other internet-firsts in my role as SVP of digital content. Learning how TV channels could make the most out of the Internet became an obsession.
Fast-forward to the present day, where at Twitter I saw tons of TV studios using Twitter data to analyse the performance of their shows, and who they were connecting with. I helped them to build strategies for marketing shows before they aired, engaging with the audience while they aired, and measuring the response afterwards. It dawned on me, why not use this data in the creation of the show too? So I wrote a show where I did just that.
What can you tell us about the show?
It's a comedy set 40 years in the future. I've seen a lot of dystopian films or shows where computers have gained sentience, become evil, and taken over. I wondered what it would be like if they were as neurotic, erratic, insecure, and charmingly flawed as the people who made them, us. What's that future like? What situations arise? How do these self-conscious robots deal with the emotional issues that we face every day?
Why did you need to use Twitter data to make the show?
In my original draft, I noticed it was skewing very strongly towards one demographic, and I wanted it to be relevant to a bigger audience. The characters I was creating needed to appeal to those people. But writing these varied characters is about more than just clothing or token references, you really need to know who they are on a more personal level. I wanted to explore new ways of building that understanding, and with Twitter being an open network I was familiar with, it was a natural choice.
How did Audiense assist?
Firstly, I identified an audience of 850,000 people who resembled the audience I was trying to appeal to. Next, I used Personality Insights powered by IBM Watson in the Audiense platform to get a rich depth of insight into their characteristics, needs, and values. I fed in certain sets of interests too, and it told me what the people who liked them were like.
Why was this useful in the creation of the show?
Analysing different segments of any demographic in Audiense corrected the over-indexing in the audience that the show would originally appeal to. It gave me extra inspiration for some characters and their plot points, as well as confirming ideas I had for others.
Moreover, this new way of creating a show will get a lot of interest from potential sponsors. Once you embrace your audience openly, you can bring in advertisers as you can clearly point to who your show is likely appeal to with far greater accuracy. This is of great value to them, and thus it's valuable for the studios too.
At what stage is the show at now?
I've been working with the entertainment company Anonymous Content (Mr. Robot, The Revenant, Eternal Sunshine...), who have totally embraced this concept of data intelligence in show creation. I handed in a final pilot yesterday, and we're now ready to go out and sell it.
What are some specific examples of how you used the personality traits?
One of my lead characters is a Latin-American woman who handles the U.S. database of computer networks, but I wanted to understand the audience to help write her accurately. We identified 850,000 people within this niche of Latino women interested in technology. Something we noticed was that although they were highly tech-savvy, they skewed towards being less impulsive and having more traditional values. Without giving too much away, this conflation helped us mould the plotline in the pilot of the show.
How do we balance the relationship between creative gut feeling and using data for good stories?
Firstly, you're always going to need good script writers, showrunners, and actors to bring ideas to life. I don't think robots armed with data are going replace them any time soon. But here's where it helps: I often sit and wonder how to write a show for audience X, and how the different segments of that audience would like it, or how to write a character from a certain background or culture. But I don't always know what they're really like or how to portray them accurately, and a focus group wouldn't necessarily give me a broad, accurate picture.
How does social data analysis differ from conducting focus groups with those audiences?
There's still room for that direct level of focused research, but they'll only tell you what they know they want, and it can't be done at scale. By analysing the social data, you find invaluable things about them that they might not know themselves; we can see en masse what they like, what they respond to, what they value, what makes them laugh, and what their overall personality traits are. You can then use that understanding to inform your writing, and see if your interpretation of that data tallies with the audience in real life.
Do you think that senior executives in the entertainment industry are ready for this?
Legendary Pictures use data like this all the time, as do MGM as one of their investors is a big data guy. It's growing, but there's some roadblocks, which is a shame because this approach removes a lot of big question marks. The problem is that there's still some executives in charge of the networks that got used to being a gatekeeper, when there was a limited amount of media to compete with. They understood a model for making television that worked in the past, and they're cautious about deviating from it.
Why do you think they should deviate from it if it worked in the past?
There's now an unlimited amount of media competing for our attention; anybody with a camera and an idea can make a TV show. It might be on YouTube, Twitter, or Snapchat rather than a traditional TV channel, but what's the difference nowadays? It's all competition for eyeballs. So in order to attract an audience you have to do extraordinary things, and really work hard to prove you're valuable. You prove that value by listening to the audience, and showing the results of it in your work.
What's the current relationship between the creators of TV shows and Twitter?
It still has limitless potential, both producers and showrunners I speak to are still really interested in using Twitter alongside their TV shows. It's where the conversation is, and it offers new ways to build an audience. They're looking at how to use other social networks too, and the best practice for each platform differs, but the overwhelming view is that for real-time engagement about the show, Twitter is still the second screen of choice.
How are they currently using that conversation to shape their shows?
I've talked with a lot of writers and producers about this. Many are already on Twitter, talking to the audience and are comfortable with hearing how they're feeling. It's like a third eye that looks at what viewers think about plot, characters, and episodes. To make it a truly useful feedback loop, the producers then have to ask, why is the audience REALLY saying that?
How do TV producers answer that question of understanding the underlying reasons WHY the audience give the feedback that they do?
Answering that question is very much the craft of writing and producing something. It's not a strict, connect-the-dots process and that's why you're still going to need top quality creative talent. But to me, that process can be hugely assisted by analysing the audience having those conversations using IBM Watson, which Audiense enables, and implementing your discoveries into the show's creation.
- "Audiense," we hear you cry, "this is fascinating, but I'm not making a TV show. What does this mean to a marketer like me?" Well, here's some takeaways that apply to all marketers:
- AI-enhanced psychological analysis of an audience will tell you things about them at scale that they might not even know about themselves.
- This level of understanding should be used to inform creative strategy and ensure your communication matches the audience you want to reach.
- There's more competition for attention than ever before, placing a greater importance on brands to know their audience in order to cut through the noise by being memorable and relevant.
- Personality Insights also indicate sections of an audience who are more likely to respond to your campaigns in a certain manner, more info here.
- Audience data is an invaluable aid to creativity and insight, but it shouldn't replace the innovative spark in your top talent. Let one power the other, and vice versa.
- Staying still is not an option, best practices and technologies that were sufficient in the past will become outdated. So an eye needs to be kept on new marketing platforms and ways to use them.
- TV audiences are still highly active and vocal on Twitter, allowing for substantial audience research and building.
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