How Media Companies Are Transforming Subscription Models with AI (and Increasing Revenue)

For customers to be able to enjoy an above average media viewing experience, it used to depend on the TV and entertainment set up, location and the availability of cable and networks. Now as long as a person has an internet connection and a viewing device, such as a tablet or mobile phone, they have the option to subscribe to a wide range of media on demand.

Netflix may have pioneered the trend for media streaming back in 2007 and have now established themselves as the leader in the industry. But the consumer trends towards media streaming have led to many communications and media service providers seeking to expand their offerings and capture market share.

By the end of 2019, the video streaming market was valued at $342 billion. In 2020, Netflix registered more than 37 million new subscribers more than quadrupling their growth targets. In recent months even more media streaming channels have established themselves in a variety of niches. It is estimated that by 2027, the video streaming market will grow to more than $842 billion. The industry has become so competitive that both new providers and established media brands are having to work harder to attract and retain subscribers. Especially with customers expecting increasingly improved digital experiences.

Focus on Digital Experiences

A huge benefit of on-demand media is that subscribers can choose what they want to watch and when they want to watch it. They are no longer dependent on a broadcasting schedule and can even binge watch an entire series in one go if they choose. This aligns with the trends towards greater personalization and choice. The question is: how do media providers create digital experiences that’ll live up to expectations and win more subscribers when there’s already so much on offer?

When new website visitors are browsing subscription options, there is a very small window of opportunity to grab their attention and lead them towards signing up for a subscription.

Expectations are high, attention spans are low and there is no one-size-fits-all marketing message that guarantees conversions. Having the ability to experiment with a large number of different ideas on specific landing pages has a significant impact on optimizing the digital experience and driving conversions. Being able to see how visitors respond to ideas unlocks the capability to clearly identify top-performing ideas or combinations. These ideas and combinations can be changed and new ones added to generate even more conversions. They can also be adapted for mobile which enables media companies to really leverage their experimentation ability.

AI-Driven Optimization Case Study by Numbers

A major advantage of optimizing with artificial intelligence (AI) is having the ability to significantly scale experimentation. For example: our team recently worked with a leading on-demand media company in the US and the experiment looks as follows:

•  3 optimizations
• 11,896 possible designs were explored
• 1.36 million unique visitors entered the optimization
• 183 variants and variant combinations were served up real visitors
• 10 variants and 17 variant combinations had statistical significance

Phase one of the cart / checkout optimization generated a 1.98% increase in sales which amounted to almost $500,000. The top performer, however, achieved a 7.7% increase in sales, estimated at more than $550,000 additional monthly revenue.

The desktop landing page optimization achieved an 11% increase in progression to buy with the top performer peaking at an 18% progression to buy. But what was really impressive was the mobile landing page optimization which achieved an average 19% increase in progression to buy with the top performer hitting 25% increase in progression to buy.

When targeting 1.36 million website visitors who each have unique preferences and interests, serving up just two options can never satisfy their expectations for personalized digital experiences. Having the ability to scale experimentation to 11,896 possible designs means that exponentially more ideas can be explored to see which ones visitors respond to.

As the experiments progress, AI-driven optimization continues to learn which combinations perform best and small changes can be made to improve the ideas even more. All without having to stop and restart the experiments. As consumer preferences change, or competitors make more compelling offers, the experiments can be adapted so that they’re optimizing continuously, always improving, with the aim of continuing to increase sales.

Media streaming is predicted to grow by 12% in the next 6 years with a strong probability of the industry getting even more competitive. Companies with aggressive growth targets will need to focus on optimizing the digital experience when aiming to increase subscriptions. AI-driven optimization can continuously adapt experiments to respond to changes in the marketplace. But more importantly it’s the technology that’s proven to drive a consistent increase in sales.