Which content does the customer prefer? Which channel? What motivates them on their journey? 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. Yet, the greatest potential for AI lies in its ability to generate growth – especially so through amplified personalization. However, companies in the telecom, media and entertainment 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.
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. 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.
- 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 means when it set out to learn what inspires park-goers to visit. Our team of social scientists documented the guest’s park experience and 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. (Learn more in the 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 your customers, you can shift into personalization. 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. Learn more about Cognizant's telecom offerings here.