Delivering a predictive customer experience in 2021: Tools, use cases, and ROI

Avatar for Jody GilliamBy Jody Gilliam|Dec 22, 2020|7:30 am CST

Your company has a lot of data, and it’s safe to say you expect that amount to increase considerably in the near future. Yet how much of this data are you storing away without even considering its potential use? The incredible demand we’ve seen for more intuitive and anticipatory customer experiences will only continue to grow over the next decade as artificial intelligence (AI) gets infused into every inch of the enterprise. The time to level up your customer experience (CX) strategy with predictive service is now.

Without question, predictive service will shape the future of customer experience over the next decade. Healthcare systems can improve overall quality of care with more proactive engagement. Financial institutions can more quickly detect and thwart fraud. Brands can better predict customer churn and take positive action against it. In so many ways, predictive tools offer massive value. Yet organizations need a solid understanding of the fundamentals–the tools and strategies required–for success. Here’s a quick breakdown…

What are the core components of a predictive customer experience?

What tools are needed?

There are many tools that can be used to drive predictive customer experience outcomes. We recommend starting with three key solutions:

  1. Conversational intelligence
    • Conversational intelligence draws from a group of AI-based technologies including speech recognition, text-to-speech, voice biometrics, natural language processing, machine learning, predictive analytics, behavioral analytics, and more. The solution applies these AI technologies around voice conversations to generate key insights into customer interactions. The solution helps evaluate barriers and service experiences (better understand the types of experiences customers are having across certain communication channels and where agents are struggling to service them), supplements agents with predictive insights (ex: the past 100 callers who used the phrase “50% off” had questions related to a holiday promotion) and enables brands to stay ahead of churn risk and purchase intent. Overall, the conversational AI market is set to be worth $15.7 billion by 2024.
  2. Virtual agents
    • Virtual agents can emulate human customer service or sales personnel, often based on AI technologies, using either a speech (spoken) or chat (written) interface to “talk” to customers. When virtual agent platforms are infused with conversational AI technologies, contact centers empower predictive self-service that helps reduce total number of contact center calls as well as labor costs (research shows that implementing a virtual agent solution can reduce contact inquiries by up to 70% and save companies up to $23,000 annually compared to human agents). With conversational AI, virtual agents can more effectively leverage data to predict customer needs, deliver more personalized interactions, and upsell and cross-sell. Gartner predicts that 25% of customer service operations will be using virtual agents by the end of this year, compared to less than 2% in 2017.
  3. Predictive routing
    • Predictive routing uses AI and machine learning to match customers and agents based on next-level variables like personality, similarities, and the skill level of a particular agent (how likely they are to sell, subscribe, upsell, retain, etc.). In this way, you can provide VIP service to your most important customers by routing them immediately to someone who can help. Or, automatically route a customer identified as being at-risk to an appropriate service member to avoid churn. The No. 1 application of AI in the contact center is predictive routing, according to Nemertes, with 95% of top-performing companies currently using or planning to use the solution by 2025.

So, how do these predictive tools drive ROI? This is the most important question at the end of the day. There are three keys to generating tangible return from predictive customer experience, and we share them in our white paper: Predictive Customer Service. It expands on this information with an in-depth evaluation of predictive service tools, strategies, use cases and what you need to do step-by-step to ensure success. Get the paper here.

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