Deliver a customer experience fit for royalty with data science and AI
“The customer is always right” is a familiar refrain. And customers deserve the best experience possible. But in a world where customers can churn on a dime, delivering a great customer experience is more important than ever. Gartner reports that 81 percent of companies will mostly or completely compete on the basis of customer experience in the next two years—but only 22 percent say their customer experience efforts have exceeded customer expectations.
So how can companies offer the kind of experience that will keep customers satisfied and loyal? Independent research and analyst firm Forrester has an answer: artificial intelligence. In a report called, Optimize customer experience metrics with 12 AI-enabled use cases, Forrester analysts write, “AI has advanced to a point where disruptive technologies can help transform the customer experience by enabling organizations to target and personalize their offers and differentiate themselves against the competition.”
Here’s how you can use a combination of AI and data science to overcome three major customer experience challenges.
Challenge 1: Getting a 360-degree view of the customer
For the exceptional customer experience that delivers competitive advantage, you need a holistic view of the customer. Getting it is a tall order, however. You are practically swimming in data—some internal, such as call logs and surveys, and some external, such as social media posts and conversations. But in most cases, the data resides in different departmental and geographical silos. Not only that, it’s in different formats: structured in rows and columns, and unstructured in free-form texts or images. It’s a mess, and it’s one that most predictive analytics solutions couldn’t clean up.
However, with a combination of AI and data science, you can make data like this work for you. You can pull together all your data and analytics, provide one consistent experience, and your teams can collaborate across business and technical functions on an end-to-end data science platform. Imagine leveraging all that data to identify and predict preferences and then using them to recommend the right solution for each customer. That’s the kind of customer experience that can set you apart from your competitors.
Challenge 2: Offering customers the hyper-personalization they demand
Continuously delivering the hyper-personalization that today’s customers crave is a challenge. It requires segmenting customers according to profiles; analyzing their interactions, history, preferences, and demographic data; and identifying engagement opportunities at every stage of their journey. Broad, simple clustering is just not effective. Yes, you get customer insights, but you can’t see customer behavior patterns—nor can you provide real-time offers and solutions.
With AI and data science, you get faster discovery and deployment for more people in your organization to adopt advanced analytics on a single platform that supports an end-to-end AI lifecycle. You can segment customers according to their profiles. You can analyze customer data such as interactions, history, preferences, and demographic data to better understand what each customer wants. And you can identify engagement opportunities at every stage of the customer journey. The result is highly-accurate recommendations for the personalized experience that treats customers as individuals with personalities.
Challenge 3: Delivering a consistent customer experience journey
Think of a recent customer experience that went smoothly, especially one that started in a store or on an app and ended somewhere else. Now take a moment to savor the memory. Why? Because, according to Forrester, such experiences are provided by only 18 percent of U.S. brands. Delivering a consistent customer experience is a huge challenge. Trying to gain an understanding of interactions across a variety of touch points is difficult because of all the different data types, locations, departments and manual processes that are involved. In fact, many companies attempted to analyze these interactions after-the-fact.
But with AI and data science, you can gain deeper understanding from unstructured data such as text and images with advanced analysis, faster model training and development. Equipped with these insights, you can get a better understanding of the customer experience. You are also able to make the faster and more accurate predictions needed for a smooth customer experience (CX), just like Caixa Geral de Depósitos France did.
Ready to take on these customer experience challenges?
If you are looking for a solution that can provide a 360-view of your customer, make predictions of user behavior, and recommend best next actions, consider IBM Watson Studio. IBM Watson Studio helps transform customer experience with richer context and deeper insight and a single platform for all model development and it supports all levels of expertise.
As a result, business and technical teams from different departments can work together to deliver the consistent, hyper-personalized customer experience that will delight customers and give you the competitive edge.
To learn more, visit the Watson Studio web page, be sure to check out AutoAI, our newest feature that automates repetitive and time-consuming data science tasks. And for a deep-dive into customer care experience, listen to the “New Definition of Client Care” episode of the Making Data Simple podcast available on Apple, IBM Big Data & Analytics Hub or Spotify.