People’s expectations around their digital experiences are changing rapidly. Media and entertainment companies have often been at the forefront of this change – understanding and then adapting to changes in culture has always been crucial for their long-term success.
Adapting to changing expectations and desires is increasingly reliant on data. It relies on less of a “gut feeling” or on qualitative analysis, but rather on collecting and then acting upon large quantities of data.
Netflix and Hulu are leaders in streaming services and provide different approaches to using data to provide an improved viewer experience.
Netflix did it again: Using interactive content to take experiences (and data) to a whole new level
In many ways, Netflix has been the poster child for better understanding people and then quickly adapting to changing desires. As was highly publicized in the past, they collected data on what and how much people were watching and started identifying the attributes for success. Initially, this started with simple tagging but progressed to combining multiple tags to create a more filtered experience. It’s for this reason that after watching a fantasy film, you’ll probably be recommended a series in the same or related genre.
The challenge here however, is that even though you have started to get to know your customer, and have some basic knowledge of them, you’re still a long way away from getting the level of understanding of individuals that has become commonplace at internet giants such as Facebook and Google. Many media companies lack access to secondary data markets with which to build richer profiles of the people they are serving. In comparison, other companies with broader assets are able to use a more diverse range of sources.
Researchers at Netflix found they have a window of between 60 and 90 seconds to help a viewer find something to watch before they give up and go somewhere else. So the issue is not just one of having, or creating, the shows and films that people want to watch. It’s also one of ensuring that people see almost immediately something that they want to watch. This means providing a highly personalized service at scale.
One of the most innovative ways to increase this knowledge of what people like, is with interactive content. In Netflix’s 2019 interactive film, Black Mirror: Bandersnatch, viewers choose the direction of the film’s protagonists. This presented a treasure trove of useful information. In the future, we expect to see more partnerships between brands and OTT companies like Netflix – providing opportunities for everything from testing new brands with viewers, to collecting more detailed information about tastes and desires.
In demonstrating this level of knowledge about viewing habits, in one of its most infamous (and also criticized) tweets, Netflix asked:
The Hulu approach to boosting the ad-based model through smart data.
While Netflix has garnered a lot of press attention for its use of data analytics, Hulu is also a noteworthy example worth analyzing. Its platform remains highly ad dependent – Hulu’s ad-supported subscriber option remains its most popular, although as of July 2021, Hulu had over 40 million paying subscribers. In 2021, it has been estimated that Hulu could generate $3 billion in ad sales, a 30% increase over 2020.
To have a successful ad-based model means Hulu has to not only understand their viewers, but also make it possible for advertisers to create highly-targeted ads, similar to the level of targeting possible on platforms such as Facebook.
A few years ago, Hulu started with dynamic ad insertion – essentially offering different ads to different people based on their characteristics. To be able to do this effectively requires much more granular data about individuals – and today they are able to provide customized ads in real-time. More recently, with their GatewayGo service, for example, they are enabling advertisers to make the leap from just presenting ads on a screen to a person’s cell phone – a much closer, and more intimate, connection.
Hulu also has products such as its “ad selector” which enables people to choose what kind of advertisement experience they want. Again, this serves to more closely target ads at individuals.
What wins – data and segmentation or program quality?
Going forward, the winners of this new world will depend on two factors. Firstly, the quality of data about individuals and how this can be segmented, analyzed, and acted upon at scale. Platforms need to provide people with what they want, when they want. The other key factor is, of course, having the original content that people want to watch. Bringing these two elements together will be the key to success for media companies going into 2022.