10 Examples Of Predictive Customer Experience Outcomes Powered By AI

10 Examples Of Predictive Customer Experience Outcomes Powered By AI

Data is everywhere. Companies today have access to more data about their customers and products than ever before. In some cases, it’s an almost overwhelming amount of information. In fact, most companies only use 1% of their data. But with the help of predictive analytics and AI, companies can dig deeper into their data to provide personalized customer experiences. Predictive analytics use science to predict what will happen in the future—everything from what customers will want to how the market will perform and the biggest trends. Brands can use this information to target the right customers and provide personalized service and recommendations.

Here are 10 examples of AI-powered predictive experiences that are changing how brands interact with customers.

1. Sprint Uses AI To Lower Churn Rate

Predictive analytics have transformed how Sprint interacts with customers and dramatically improved the customer experience. Sprint customer service agents used to manually analyze customer data, but it was cumbersome and ineffective. The company now uses an AI-powered algorithm to identify the customers at risk of churn and proactively provide personalized retention offers. AI predicts what customers want and gives them the offer when they are most at risk for leaving the company. Since switching to AI, Sprint’s churn rate has dropped dramatically, and customers have given the company great scores on its personalized service and targeted offers.

2. Harley Davidson Targets Potential Customers With AI

The popular motorcycle company relies on predictive analytics to target potential customers, generate leads and close sales. When customers are targeted directly, they can have a more personalized experience that leads to higher satisfaction. Harley Davidson uses an AI program called Albert to identify potential high-value customers ready to make a purchase. A sales representative can then contact the customers directly and walk them through the sales process to find the perfect motorcycle. It’s a win for both sides: customers get personalized service at the moment they’re ready to make a purchase, and the company can focus on serious customers.

3. Volvo’s AI Program Detects Faulty Parts

The fastest way to ruin a car experience is to have something break down unexpectedly. Volvo uses data to predict when cars need to be serviced and what parts need to be repaired or replaced. Volvo’s Early Warning System analyses over one million events every week to predict each part’s breakdown rate. With that information, the company can recommend service and maintenance plans to customers before the part breaks and creates a bigger problem. Volvo also uses AI-powered data to track and predict the most popular and most comfortable features for drivers.

4. Netflix Uses Data For Personalized Recommendations

No list of predictive analytics companies would complete without Netflix. Everything Netflix does is based on data, from the shows it creates to the movies it promotes. Netflix collects huge amounts of data on each user that it puts into an AI-powered algorithm to predict what they’ll want to watch next. Data like demographics, watch history, ratings and preferences influence what the algorithm will predict, and it’s almost always accurate. About 80% of what is watched on Netflix is due to the recommendations. Having such a strong system saves the company $1 billion a year in customer retention.

5.  Sephora Helps Customers Find The Right Products With AI

Finding new makeup and beauty products can be overwhelming for customers, but with Sephora’s many technology offerings, customers can be confident they’re getting the right products for their lifestyle and skin tone. Sephora’s data creates personalized profiles for each customer based on their purchase history and preferences. AI then sorts through that data to predict the products customers need and puts them in a customized “Recommended for You” section on its home page. Sephora also uses data on how much customers have spent that year to predict their loyalty and send targeted rewards and marketing messages. The systems are working; 80% of customers are completely loyal to Sephora.

6. Royal Bank of Scotland Combines Data To Proactively Solve Problems

Banking is all about numbers and patterns. Royal Bank of Scotland uses those patterns to predict what products a customer may want and what issues may arise. Real-time data analytics help the company track complaints so it can understand the big issues and predict what questions or complaints customers may have. It can then deploy the right resources and ensure that customers are taken care of quickly. Having all of the data together in one dashboard makes it easy to understand customers, predict what they want and then make it happen automatically.

7.  American Express Uses AI To Predict And Stop Fraud

Credit card fraud can ruin a customer’s experience, and customers want to know they have a card they can trust. American Express uses analytics to predict potential fraud and identify customers at the highest risk. The company can then take proactive action like personal calls or direct marketing. By finding potential attacks before they occur and helping customers stay safe, American Express creates loyal customers and one of the lowest fraud loss rates in the industry.

8. Caesars Palace Predicts The Best Guest Upgrades

The high stakes world of customer experience at a top hotel and casino is a gamble. In order to know the best upgrades to offer guests, Caesar’s Palace uses AI-powered analytics. The company collects data on its guests and then uses that to predict what types of upgrades would be most effective for each guest. A free meal could be enough for one guest to have a great experience, but someone else may require a free night’s stay. Predictive analytics helps the company know what upgrades to offer to get a potentially big money guest to stay at its hotel.

9. Progressive Turns Customer Data Into Accurate Policies

Insurance customers can opt into sharing their driving data with Progressive. The company has collected billions of miles of driving data, which it then puts into an algorithm to understand the factors that contribute to certain driving issues. Data predicts what customers are at a higher risk for accidents. When policies are more accurate, all customers save money. Progressive can better understand the insurance marketplace and adjust its offerings based on predictive trends to get rid of bottlenecks and focus on providing quick, accurate service.

10. Gogo Air Predicts Customer Trends and Demand With AI

If you’ve flown on a major airline, you’ve likely been exposed to Gogo Air, the company that provides internet access and in-flight entertainment. Gogo Air collects data from all of its customers to better understand how to improve the service and customer experience. The AI-powered algorithm shows what products customers are using most and how they will be used in the future. Gogo’s system predicts what customers want, which means it can tailor its services to best match customer demand and create a superior customer experience.


Predictive analytics powered by AI have the potential to change customer experience. It’s a powerful tool for companies to have in their tool belt and one that they should use strategically and often to create amazing customer experiences. These companies show that it’s possible to predict the future and do it in a way that keeps customers happy and coming back for more.