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Optimizing data-driven customer experience is essential in the age of reinvention

Neerav Vyas
29 Sep 2022

The challenge for the media and entertainment industries is finding the signals amid the noise

Media and entertainment (M&E) powerhouses like Amazon, Netflix, Spotify, and Disney have successfully disrupted the industry, and streaming platforms have become a core focus of their businesses. As M&E companies try to stay ahead of the curve by diving into data, they need to discover how to differentiate the signals from the noise.

What I’ve found in helping Capgemini’s clients is that reinvention is an ongoing, iterative process for M&Es, with the data-driven customer experience generating the most change. The ultimate goal is continued reengagement with customers and a strengthened value proposition for the company. To get here, companies need to understand the dimensions of streaming platforms to apply their data more effectively.

Personalizing the customer experience

Companies need to consider the end-customer experience they need. How do you differentiate your streaming platform beyond your content library and maximize its benefit for customers? Netflix, for example, has enough content to entertain viewers for years, but surfacing the right content and recommendations for each customer is the critical challenge.

Using AI to unify fragmented data can help companies create a more personalized, responsive, and relevant customer experience. This could mean recognizing a customer has shifted from searching for shoes on Amazon in the morning, and offering them recommendations for athleisure products, to updating those recommendations in real-time when they’re browsing for baby products later that day.

Another way to please customers is through experimentation, which may mean recommending a TV series based on what a customer is watching andalso taking a risk to suggest a complementary show. What we found with one platform was that if you could get someone to dig deeper into their recommendations, they were 10 times more likely to engage with the brand and significantly more likely to trust recommendations afterwards.

Transforming data into actionable intelligence

Massive amounts of data are collected by M&Es, so teams need to become data literate and also need the tools to navigate, interpret, and act on the content collected. Interconnected data breaks down silos and creates a more unified view of how a customer interacts with the brand.

Along with the explicit signal that the consumer enjoyed a show – like Netflix’s thumbs up or thumbs down – there’s the implicit side to analyzing consumer data, which is sometimes more valuable. Did customers finish the show they were watching? Did they come back to the series? Another element of data intelligence is crowdsourcing, which companies like Spotify have used effectively. It’s not just user reviews but also open-source playlists, almost a curation experience for people who follow another customer’s personal tastes. The data from this user-generated content also delivers insights that you can employ to guide recommendations for all the people who don’t engage in that playlist.

Increasing and optimizing monetization

Streaming platforms are increasingly moving to hybrid payment models. For example, a customer could choose to download a free version supported by advertising or pay for the product and stream ad-free. The company starts to develop maturity to function as a digital advertiser, similar to Facebook and Google, targeting someone at the right time with the right context. This creates a relationship with both the end consumer and the businesses advertising on the platform.

The challenge becomes leveraging the signals to effectively market to various customer segments and deliver the appropriate contextual experience at each touchpoint. Marketers already focus on attracting new customers and nurturing existing ones, but there will be an increasing marketing component to reacquiring customers who subscribe to a platform for a specific series and then unsubscribe when it’s over.

Rethinking ROI

Recommendation engines have evolved, so measuring ROI has to shift, too. When looking at metrics and KPIs, the question used to be, is the consumer going to watch the show we suggest? Now, the metric is whether the consumer will watch that recommendation this week.

ROI has to be linked to business outcomes, and M&E companies struggle with the holistic measure of returns. The traditional financial metrics all come into play, but the other element centers around engagement with content. That needs to be measured in multiple ways and with an understanding of what the connections are between those options and your business KPIs.

Capgemini’s data-driven customer-experience solution can help media and entertainment companies tune into the right signals. We can help bring together fragmented data and systems to create a real-time personalized experience your customers have come to expect.

Please contact me if you have any questions or comments about data-driven customer experience.


Neerav Vyas

Global Head of Customer First, Insights & Data, North America
Neerav is an outstanding leader, helping organizations accelerate innovation, drive growth, and facilitate large-scale transformation. He is a two-time winner of the Ogilvy Award for Research in Advertising and an AIconics 2019 and 2020 finalist for Innovation in Artificial Intelligence for Sales and Marketing.