Perceived value doesn’t always align with real value. Take Amazon Prime Video, for instance. As it comes bundled with the Amazon Prime service, it’s fair to say few people are paying directly for it. Yet perceived value is high because it’s offered as part of an ecosystem.
Apple TV+ is another example. It’s priced at $4.99 per month, but you can get it for free for a year if you buy a new device, which many of its users would have done anyway. Even if the content library is light, Apple then has a 12-month window to win consumers over with new launches.
On the flip side, the price of Netflix has steadily increased over the years. But so too has its domination of the market. And many people are happy to pay the monthly fee even though it’s not in an ecosystem, in part because Netflix is so good at knowing the right content to put in front of the right viewer at the right time. Perceived value is high because consumers feel like there’s always something to watch.
The new definition of perceived value
So, what does this mean for niche streaming services? Well, perceived value has become more about the customer’s view of how well a service meets their requirements.
Ease of use and targeted content discovery are now key drivers behind users choosing one streaming service over another. If a subscriber pays $5 a month for service A and $10 a month for service B, but they rarely find anything they’re interested in on service A whereas they can always find something to watch on service B, the key driver for churn won’t be cost: it will be perceived value.
Increasing perceived value with content analysis
What can streaming services do to increase perceived value? It’s not just investing in new, blockbuster content – although that’s important. Getting the most out of your entire catalog is the key. And the content discovery experience in terms of editorial curation, promotion, and recommendation has a big role to play.
Consider the following:
- How closely aligned is your content library to the needs of your customers?
- Is relevant content easy for them to find and engage with?
- What content performs best at different stages of the subscriber journey?
- What assets are best at keeping users engaged overall?
Working out the answers to these questions and others like them is key to increasing perceived value. This means taking a deep dive into how your users are exploring content; what’s holding their attention, what isn’t, and how that can be used to make more intelligent curation and promotion decisions.
Unlocking actionable intelligence
Collecting and structuring all the information you need can be a tall order. However, an audience insights platform like Wicket Scorecard can do all the heavy lifting for you. It has the necessary integrations to easily automate the aggregation and harmonization of data from across your systems.
Once in place, this dashboard makes it easy to unlock the data-driven insight needed to measure the effectiveness of your content library. By using machine learning, platforms like Scorecard can also help you to spot trends that may have flown under the radar but have an impact on user retention, content effectiveness, and perceived value.
Boosting engagement with data-driven insight
Pulling insights from across your tech stack will help you to better understand what your users are looking for. By identifying the motivation behind content selection and what assets hold attention most, you’ll be able to more effectively promote similar content to the right subscribers at the right time.
Using platform analytics in this way will also help to maximize the value of your catalog content. This can include knowing when to promote guilty pleasures – classic and popular content users have seen before, yet they would be happy to re-watch – based on consumption trends. An analysis of trial user viewing habits, for example, may suggest that promoting these assets after they have binge-watched their way through your blockbuster or original content will keep engagement high and get them to that all-important first payment window.
Data helps you go deeper into the overall effectiveness of your content library, too. More advanced insights platforms like Scorecard enable you to run complex data queries to work out the contribution of different assets on your service, the relative performance of new arrivals and whether they’re likely to hold consumer attention in the long term, and more.
This level of insight can then be used to create or license new content that’s more likely to be a hit. It’s a powerful way to expand your content portfolio based on what viewers are hungry for. Similar to how Netflix has always used data analysis to create and promote new content based on engagement and viewer insights.
Ultimately, if content is king, data insight is queen. Being able to leverage the wealth of data at your fingertips in this way is not only critical to increase perceived value, but also to maintain a competitive edge amidst a growing number of similar subscription video services.
The opportunities outlined here barely scratch the surface of what’s possible when putting your platform data to work. If you’d like to know more about how to use data to maximize your content investment, check out our latest expert guide on how to make your library work harder.