Bandersnatch: The Marketing Weapon
Bandersnatch is an episode of Black Mirror, one of the best TV series on Netflix. I don’t want to make spoilers about Bandersnatch, so I won’t tell you the endings and how did it go in my experience.
It is an interactive “choose your own adventure film” that had nearly one trillion different storytelling combinations depending upon the choice you choose. The script was made using Twine.
“Twine is an open-source tool for telling interactive, nonlinear stories.” You don’t need to write any code to create a simple story with Twine, but you can extend your stories with variables, conditional logic, images, CSS, and JavaScript when you’re ready.
You can check it out later at https://twinery.org/
Data Mining
Netflix is a Big Data Company and everyone knows it uses the user’s collected data well enough. Its recommendation engines, its popularity models, understanding these user preferences was instrumental in dominating the market it created, keeping subscribers within its ecosystem and guiding original programming slates.
So, what is Netflix doing with the user data it gathers from “Bandersnatch”?
Just think about all the possibilities…from choosing products like cereal to choosing your creepy decisions along with the story. By putting the same kinds of interconnected decision-making to work within one title, Bandersnatch can generate more robust pattern discovery and insights into trend analysis than traditional content cannot.
Where the company previously focused its data gathering on the ways users engage with its content — what they watched, when, and for how long (Recommendation Engine)— this new data is indicative of real-world decisions like product preference, musical taste, and engagement with human behavior.
In Bandersnatch, one of the most visceral decisions users make is whether games programmer Stefan (Fionn Whitehead) or his associate Colin (Will Poulter) will jump off a balcony. How users handle this decision — how long it takes them to click on one choice or the other, how often they return to (or avoid) a given option during replays — can be matrixed with the choices they make in resulting timelines. Those choices offer unprecedented insight about what Netflix’s subscribers want out of a story and what choices they most want to see characters take.
Bandersnatch represents a new form of data mining that gives Netflix richer, more specific audience information than it’s ever had before. That could be used to steer choices in the writers’ room or even in discussions about what kind of projects Netflix greenlights in the first place.
“NETFLIX CAN MARKET TO ITS USERS WHILE STUDYING THEM AT THE SAME TIME”
The first choice Bandersnatch involves is choosing a cereal between Frosted Flakes or Sugar Puffs?
It showcases the most blatant marketing technique Netflix can deploy with interactive content: “programmatic product placement”.
These moments are opportunities for Netflix to market to its users while learning from them. It will be able to directly test product designs which is a service Netflix could sell to brands before production begins. Netflix will be able to erase marketers’ greatest obstacle by hand-holding them to their most receptive audiences.
Another early decision in Bandersnatch calls on users to choose which cassette Stefan will listen to while traveling to the gaming company Tuckersoft: Thompson Twins or Now That’s What I Call Music, Vol. 2.
Now Netflix can simply just show you the pictures of both these brands to promote it. Why make it so complex and merge it in options?
You choose it for the lead character and hence controlled him. But what if you are also part of a bigger Bandersnatch, what if the choices you are making in Bandersnatch not only affect what happens in the life of Stefan but also in your life? It's like a Life Hack!
Recommendation Engine
I am not going into details how the recommendation engine works through collaborative filtering or content filtering, but I am gonna focus more on Netflix recommendation engine
In 2009, Netflix awarded $1MM to a team of researchers who developed an algorithm that improved Netflix’s prediction accuracy by 10%. Netflix has been trying to get their hands on data from the user in every possible way.
In a way, Hastings was a tech-age Willy Wonka letting any curious hacker into his digital Chocolate Factory. Instead of a chocolate river, he offered a gushing stream of data. But the winning “Golden Ticket” wasn’t hiding in an ordinary candy bar. It was locked away in your brain.
