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How media, entertainment & telecom players can apply AI to boost customer experience

September 30, 2019 - 131 views

How media, entertainment & telecom players can apply AI to boost customer experience

By personalizing the customer experience, AI can help companies in high-churn sectors acquire and retain customers, leading to business growth.

AI is great at cutting operational costs. For media, entertainment and telecommunications companies, in fact, some of AI's best uses to date have focused on reducing fraud and squeezing inefficiencies from IT infrastructure. Yet the greatest potential for AI lies in its ability to generate growth. By personalizing the customer experience, AI can help companies in high-churn sectors acquire and retain customers. Which content does the customer prefer? Which channel? AI can help organizations zero in on answers. 

Perhaps the greatest driving force behind AI’s shift into customer experience is young consumers’ expectations for all-digital interactions. By determining personalized next-best actions generated by sophisticated prescription engines, AI opens new avenues for cross-sell and upsell and anchors the experiences that Gen Z consumers increasingly expect. Consider that the overwhelming majority (60%) of Gen Z is open to experiencing virtual reality in movies, shows and games.

Companies in the converging media, entertainment and telecom space have been slower to explore the application of AI to customer experience for several reasons. One is that the data environment is more complex. In addition to readily available operational data, AI-driven customer experience requires larger ecosystems of data, such as social media and third-party sources that reside outside the company.

Another reason is that applying AI to customer engagement means not just more data but also better data through data cleaning and enrichment. It’s also not uncommon for customer experience-based AI initiatives to take media, entertainment and telecom companies beyond their comfort zones and into nontraditional environments such as mixed-reality experiences.

Getting Started on a New Focus for AI

To realize the benefits of applying AI to customer engagement, organizations should start with some foundational tasks and mindset shifts:  

  • Remember that engagement includes prospective customers. AI levels the playing field: Infusing machine intelligence into each point of the customer journey – website, mobile, in-store and call center – enables traditional companies to match the intuitive customer experience of digital-native competitors, many of which implicitly understand customer behaviors, needs and interests across touchpoints (exhibit A, B and C are Amazon, Netflix and Google, just to name a few). For example, as a provider of lead generation and campaign services, the data management arm of a billion-dollar digital agency sought a better way to identify prospective consumers across channels over time. With a modern data and AI ecosystem, the agency could spot customer activity across digital platforms and apply it to the personalized real-time offers it generates for clients’ customers. By moving its customer engagement platform to the cloud, the agency eliminated licensing expenses and reduced operational costs. Its improved lead qualification resulted in better campaign lift.
  • Understand the customer journey. How do customers move from one point to another as they interact with your company? What motivates them at each step? AI helps you connect the dots through data. A regional theme park encountered just how much data when it set out to learn what inspires park-goers to visit. Our team of social scientists documented the park experience for several dozen guests and then combined these findings with third-party demographic data and the park’s transactional information. Through that data lens, we identified three visitor needs the park could deliver on. Equally important, we created key performance indicators (KPIs) for each need. The AI-driven metrics enabled the business to track customer experience in the right context. To improve customer satisfaction, we also provide an avenue for analytical interventions such as sentiment and word-association analysis and hypothesis testing. The park’s projected outcomes include a 100% targeted increase in footfall in four years. (For more information, see our report “Through Thick and Thin: Making AI Work in the Real World.”)
  • Start now to collect the data you will need. AI has a learning curve. It takes time to build the foundation you need to reap its benefits, particularly given the complex nature of customer experience. Launch initiatives now to begin collecting the structured and unstructured data that current touchpoints don’t provide. For example, social media platforms offer valuable insights into consumers’ social circles, the celebrities they follow and causes they support. Be sure mobile platforms are in the mix. Mobile data’s real-time information on location opens up opportunities to push the right offer at the right time. Don’t forget traditional data sources such as transactions and interactions across physical and digital channels and among third-party partners.
  • Consider how your organization can personalize content more creatively. Once you know who your customers are and where they’re coming from, you can shift into personalization with insights into what they want. Start with the easy wins, such as polishing your recommendation engine to develop smarter, more accurate suggestions. Know your customer (KYC) is another fast path to improved customer satisfaction. A customer service chatbot that identifies customers based on their phone numbers is a straightforward task in software development and should be an early addition to personalization services. Hyper-personalized content ups the ante. It puts data to far more detailed use – and discovers far more tailored options. For example, as part of its retention management program, a large U.S. telecom company dug deeply into what causes customer churn. It created sub-churn identities such as “conditionally loyal subscriber” and “lifestyle migrator.” AI further improved the telecom’s personalization efforts by combining data on real-time sentiment analysis and past interactions to proactively anticipate customer queries. With the new information, the company designed retention strategies, such as customized search results per past shopping cart activity, and improved campaign lift by 7%.

For the high-churn environment of the media, entertainment and telecom industries, attracting and retaining customers is key. AI offers the next level of capability when it comes to creating the experiences that will keep customers’ attention even as the options continue to expand and evolve.

Digital Business & Technology , AI & Analytics customer experience , customer engagement , artificial intelligence , telecommunications , AI , entertainment , media , telecom

Badhrinath Krishnamoorthy

Market Leader, Cognizant’s Communications, Media & Technology

Badhrinath (Badhri) Krishnamoorthy is a Market Leader in Cognizant’s Communications, Media & Technology business segment....

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