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Business | R&D | Technology

3 ways Netflix is beating Hollywood at their own game…

Our in-house Motion Designer James has been thinking about the rise of Netflix, and what companies like ours who use data for marketing and improving our customer experience can learn from their success.

 

Over the course of 2018, Netflix have released 86 original films, far outshining the production rate of any other studio. Last year the heaviest hitters (20th Century Fox, Disney, Universal Pictures, Sony and Paramount) released only 106 films combined. To the casual observer, some of what Netflix chooses to fund might seem risky, flippant, or even downright esoteric; jumping from mumble-core Swedish teen dramas to crass Polish reality shows. How can they be so confident about such seemingly arbitrary choices? Giving Adam Sandler exclusive funding to produce 4 movies with full knowledge that they will be domestic flops and critical failures or spending 100 million on remaking an old British political show House of Cards aren’t the kind of gambles normal companies can afford to make. However, Netflix’s graceful handling of data and machine learning algorithms are able to turn these gambles into much safer bets. Here’s how they do it:

 

Microtargeting
Whereas movie studios have to rely on unreliable data from ticket sales and focus groups, Netflix has instant and direct access to the habits of every one of its 137 million viewers, broken down into clicks and watch-times which allows them to accurately pre-empt what we’ll click on next. Yes, Adam Sandler’s last ten movies give him officially the worst Rotten Tomatoes scores by a working actor in Hollywood history, but as they know he’s a superstar in Brazil and Eastern Europe (both major markets for the industry and ravenous online media consumers), it becomes worthwhile investing in whatever he does next.

A film or show can be successful for any number of reasons, but rather than just making best-guesses of what will be popular Netflix can see that the Venn diagram of ‘people who like Kevin Spacey films’ overlaps massively with ‘people who are into political thrillers’, ‘films directed by David Fincher’ and ‘have watched the original series of House of Cards’. This allows them to create the first in a new wave of data-driven productions, they know how successful Kevin Spacey in David Fincher’s House of Cards will be even before it starts shooting. As machines and not analysts are reviewing the data, these Venn diagrams of genre-trends and tastes can be broken down to the quantum scale, finding patterns in vast oceans of information. As Hollywood lags behind as a ‘one size fits all’ solution trying to appeal to multiple groups with each major film (‘Romance! Action! Thrills!’), Netflix can be more targeted, curating each one of their films to smaller, more niche markets and hitting them right on the nose.

Viewer Investment
Another factor is that choosing a film to watch on Netflix is much less of an investment for people than a trip to the cinema. If I don’t like it, in one click I can just choose something different. A whim can lead me into a film that I would have rapidly had second thoughts about if I had to go through the rigmarole of booking a cinema ticket, organising parking etc. Also, whilst I would be filled with shame walking into a cinema and asking for a ticket to Britain’s Biggest Wedding Cakes, with my Netflix account and in the privacy of my own home, becoming fully immersed in some marital icing-mishaps is a much more palatable choice. Yes, it may mean I’m not proud of my viewing history, but it also means that the data Netflix has on my private choices tells them a lot more about the inner workings of my mind than the limited data that major studios would have access to, allowing them to make better predictions of my next slightly shameful TV binge.

Personalised Marketing
Currently, an average major film studio release needs to spend around half of its budget on marketing and promotions. This is why so many films are forced to play it safe or resort to ludicrous product placement, just so they know they can make some of that enormous sum of money back. Netflix however do things differently – they are the marketing platform. They control the ads and know which ads will work on which viewers: in the streaming age, we no longer have to sit through ads that are entirely irrelevant to us and are therefore wasted advertising space and budget. Recently Netflix have taken this a step further, as they now curate and adapt film images and descriptions, specifically tailoring them to each account. My mother and I will be shown the same film, but with cherry-picked poster designs that will appeal more personally to each of us. However, their famous recommendation system does have some pitfalls. If I’m only recommended content which is similar to other things I’ve already seen, I could begin to stagnate, narrowing of my sense of what’s out there and closing my mind to new genres. There might be a great Bollywood masterpiece that could blow my mind, but I’ll never see it in my curated content because it’s not similar enough to the things I’ve watched before.

 

One thing that’s certain is that Netflix’s use of analytics has changed the industry forever. They’ve achieved what Hollywood studios have dreamed of for years: the ability to take their hands off the wheel and let the data steer them. Only now, as media consumption has begun moving online and we are more willing to give up our personal information in exchange for a better user experience, has this become possible. However, what’s good for Netflix may not be what’s best for us as viewers – if we’re only ever having our own ideas and beliefs rebranded and repackaged back to us, it could lead to a homogenous hardening of our worldviews and an inability to step outside of our own bubble. The hope is ultimately that people’s thirst for the unexplored will win out, encouraging them to scroll down into uncharted waters and perhaps fall in love with a whole new genre while they’re there.

By James McDonnell
Posted: 30th October 2018
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