How streaming analytics is helping companies decide which shows to produce

Streaming platforms are all the rage these days with every major media company now offering their streaming services for their audience.

Netflix used to be the only major player in the streaming industry a few years ago, but newcomers like Hulu, Apple TV+ and Disney Plus have now started to break the monopoly of Netflix.

To understand how much the new streaming services have grown, one need only look at Disney Plus. The service has seen a meteoric rise in viewership and subscriber base, which is very impressive considering Disney only started its streaming service in 2019.

Its impact has been such that it now looks like every single show Disney is offering on the streaming platform will be successful.

The influx and the success of streaming services on the market, though, is the result of changing audience preferences and the increased accessibility to the internet, which is likewise fueled by the widespread use of smartphones.

The streaming industry is even eating away at the market share of theatres. All this boils down to the quality of content provided on these streaming platforms. 

One tool that is helping creators create quality content is data analytics, more specifically, streaming analytics.

In this blog post, we will explore how streaming analytics is helping these platforms produce successful TV shows, movies, and documentaries.

Streaming platforms are using viewing statistics to improve their existing offerings

Streaming platforms have multiple flagship shows which they bank on to attract new viewers. Stranger Things, Sherlock Holmes and Peaky Blinders are such shows, and each has millions of fans. There is a good reason for this phenomenon.

These shows ran for multiple seasons and got progressively better with every season, which was the only reason fans kept tuning in.

Sherlock Holmes, for example, was picked up by Netflix from BBC because decision-makers at the streaming giant figured out that there is a demand for clever shows like it. Netflix not only bought the show but also increased the production quality. A factor that contributed to creating higher customer engagement.

Data analytics played a huge role in Netflix picking up the show. If streaming analytics hadn’t revealed the potential of the show, the streaming platform would not have picked it up and the show would have stayed a small-time production on the BBC. The same is true for Peaky Blinders.

The point here is that streaming analytics is helping these companies validate their decisions and improve the production quality of their existing shows.

Data analytics is helping produce new shows

Annually, streaming services spend billions of dollars on content creation. The financial stakes are high, which is why decision-makers at these organisations use streaming analytics to ensure they make the correct production decisions and avoid investing financial resources on potentially unsuccessful productions.

Netflix, for example, has realised there is demand for shows that are grounded in reality or shows that are based on real events. In response to these findings, they have allocated millions to making movies and TV shows in this genre.

An example of this kind of decision making is Netflix’s decision to make a docuseries about the Gamestop and Wall Street saga.

Disney Plus too is making more Marvel TV shows, because analytics have revealed that there is demand for long-form superhero entertainment. Initially, Marvel only planned on making TV shows on Disney Plus. This has now been increased due to positive reception by fans for shows like Wandavision, and The Falcon and The Winter Soldier.

The bottom line here is that streaming companies use streaming analytics to make creative decisions on how they produce entertainment.

Streaming analytics is helping streaming platforms produce higher quality content

It seems like ever since Netflix became a phenomenon, more and more companies are trying their hand at streaming.

Most of these streaming services are using data analytics to make decisions on what content to produce, axe or improve.

As for us, the audience, streaming analytics is giving us quality entertainment to binge on.