The Importance of Customer Centricity for Customer Lifecycle, Customer Lifetime Value and Customer Experience in Media and Entertainment

When it comes to using data and AI to learn about customers, the media and entertainment sector is ahead of the game. Digital media in particular has made it easy to measure, track and log customer choices, giving the sector insights into how to optimize and personalize the experience. But as customers start to show a clear preference for relevance over personalization, how can the media and entertainment sector adapt?

Ahead of the Curve

As increasing amounts of media has become digitalized over the past 20 years, from books and music to TV programs and websites, the media and entertainment sector was amongst the first sectors to truly understand the benefits of logging and tracking their customers and finding ways to give customers a unique experience.

Monitoring and measuring media usage gives the sector insights into how to manage their customers, or, in other words, how to improve customer acquisition, retention, engagement, and monetization. For example, by looking at the gathered data, organizations are able to engage their customers by making content recommendations and act proactively to retain customers if they notice their engagement dropping off. Monetization of customer data captured via third-party cookies, prior to their phase-out, was sold to advertisers to generate additional revenue.

The Importance of Customer Centricity

Data and AI increase the amount of data and insights that the organization has about its customers, enabling a customer-centric approach. This has an impact on the customer lifecycle, customer lifetime value, and customer experience.

By focusing on the needs of the customer, organizations are able to move customers through the customer lifecycle from being an occasional to a regular customer and then to being a brand advocate. It also enables the organization to control and increase its share of the customer’s wallet. A customer-centric approach can increase the customer’s appreciation for your organization when things go well. However, if something doesn’t go as planned, it can be more challenging for your organization to recover.

How Customer Centricity is Changing the Curve

While the media and entertainment sector was the first to realize the potential of using data and AI, the pendulum is currently swinging in the opposite direction. From its more conservative new perspective, the media and entertainment sector is now asking two questions.

Firstly, what can the sector do? As third-party cookies are becoming a thing of the past, organizations are now working out the most optimal solutions for monitoring customers to deliver targeted and personalized content.

Secondly, what should the sector do? This question looks at what is and isn’t possible from an ethical and legal standpoint. While it sounds like a smart idea to use content optimization to drive customer engagement, there is a fine line concerning data usage that shouldn’t be crossed.

Behind these questions and the new conservative perspective, is the realization that customers are looking for relevance, not personalization. A lot of the actions previously taken by organizations, for example, the way they handled third-party cookies, had been done simply to gather customer data instead of improving the customer experience. By turning this around and making the customer experience the priority, organizations are using the data they gather to discover new ways to engage and retain their customers, ultimately creating customer intimacy.

The Role of Data and AI in Customer Centricity

The pendulum of customer centricity needs to find a new equilibrium between customer lifecycle, customer experience and customer lifetime value. Data and AI remain vital for providing a customer-centric approach that encompasses the entire organization, including all customer touchpoints and interactions. Some of the ways that data and AI provide a customer-centric approach include:

First Party Cookies

Instead of relying on third-party cookies to pursue customers online to gather data on them, organizations now have to rely on first-party cookies to gather rich data on individuals that can be analyzed for insights. While this has potential benefits for both publishers and customers, it reduces opportunities for advertisers who previously sold space based on third-party information.

Reinventing Advertising

In addition to losing the data that is currently gathered by third-party cookies, advertisers are facing the challenge of new shopping habits including hyper-localization. This new trend is forcing advertisers to adopt a more data-driven approach in order to entice customers with relevant, local content. The prime driver is now figuring out why customers act in the way that they do.

Managing Revenue Streams

The way that content is valued has changed. Instead of media and entertainment organizations earning the majority of their income at the launch of each asset, the on-demand aspect of media provision means that organizations are now receiving a more predictable revenue stream. This has resulted in major media organizations being more assertive in their decisions about the type of content they commission and how to distribute their content.

Deep Learning and Other Technologies

The media and entertainment sector has been taking ideas from other sectors to find ways to implement existing management and risk techniques and innovative technologies to improve the customer experience and their business outcomes. For example, film studios are applying deep learning techniques and pattern recognition to scripts before they are produced to predict how profitable they are likely to be.

5G and Edge Computing

5G and Edge are putting a lot of power into customers’ pockets and devices while simultaneously opening up many opportunities for gaming and the rest of the media and entertainment sector.

Smart Mergers and Collaboration

Organizations within the media and entertainment sector need to look outside the confines of their marketplace to find synergies in other markets that will help them to retain and engage their customers by improving the customer experience and increasing the customer lifetime value.

Message Personalization

Insights from data combined with AI can help organizations decide on the right way to personalize messages and guide customer interactions, whether this is online or a conversation with a call center representative.

From Prediction to Prescription

AI can help to predict likely future events and help evolve that to a prescription of what the organization would like to see happen. For example, a media organization can look at the data from one customer, including viewing habits, billing information, length of remaining contract and media usage, to be able to predict the customer’s churn rate. Based on this insight, the organization can decide if they need to act to prevent a customer from switching to a competitor.

Calculate Potential Customer Lifetime Value

The same data that is used to go from predictions to prescriptions, can also be used to calculate the potential customer lifetime value for individual customers. The organization can use this to decide how to retain a customer – or encourage them to leave.

Risks of Over- or Underuse of AI

It is important to note that there are risks to both over and underusing AI. If an organization uses AI without having a clear strategy and objective, there is a good chance that the organization won’t be able to create the return and the value that they are looking for. Alternatively, by underusing AI, the organization will not be able to differentiate themselves from their competition, giving customers no reason to remain with them.

Taking the Next Steps with Data and AI

This mandate shouldn’t wait until all the necessary data assets, from relevant infrastructure to accessible data sources, are available. Instead, the organization should look for an issue that they can solve with the available resources, before moving on to the next issue while simultaneously improving their data resources step by step. This will enable the organization to benefit from data and AI sooner.

Looking to the Future of Data and AI in the Media and Entertainment Sector

As we have seen, the importance of customer centricity has become even more important. It looks at more than just what organizations are doing for the segment of one, to understand why each segment is interested in a certain product or service. Data and AI continue to play an important role in achieving this to enable organizations to provide a customer-centric approach that has a positive impact on customer lifecycle, customer lifetime value and customer experience.

Is your organization ready to benefit from data and AI? Learn more about how AI can play an important role in staying relevant and seizing business opportunities in the future.