Customer Loyalty Trend: Artificial Intelligence

Brands want consumers to commit to them, but one study shows that consumers turn the tables and demand that brands show commitment to them. While brands are focused on how many customers visit their site and download their apps, a study from Wunderman found their time might be better spent convincing customers that they care about them. How do brands make this shift and persuade customers that they care to increase customer loyalty? Artificial intelligence (AI) can help bridge the gap between what brands are currently doing and what customers really want.

Artificial Intelligence is the field of computer science associated with the concept of machines “thinking like humans” to perform tasks such as learning, problem-solving, planning, reasoning, and identifying patterns.

Is Machine Learning the same as AI?

When people refer to artificial intelligence, they often really mean machine learning. Machine learning is a subset of AI. Machine learning (ML) involves creating algorithms that can recognize patterns in large, evolving data sets and draw conclusions from past experience using that data.

ML is often used to predict future outcomes based on historical data. For example, organizations use machine learning to predict how many of their products will be sold in future fiscal quarters based on a particular demographic; or estimate which customer profile has the highest probability to become dissatisfied or the most loyal to your brand. Such predictions allow better business decisions, a more personalized user experience, and the potential to reduce customer retention costs.

Related Article: Customer Loyalty Trend: Shared Values Matter

AI-Driven Personalization

The rise in customer loyalty programs and big data means that companies can gather more information than ever before about customers. However, it is more data than a human can take in. One of the applications of artificial intelligence is analyzing this data and predicting customer wants to be based on this analysis. AI-driven personalization has a high success rate.

HSBC used AI to predict rewards for its cardholders. “We launched a new suite of cards to provide the ultimate support for our customers’ lifestyle. By using AI to predict our consumer’s redemption behavior, we’ve refined our loyalty program to ‘speak’ to our customers by promoting the perfect reward or experience for them,” said Pablo Sanchez, head of retail banking and wealth management for HSBC in the U.S. and Canada.

Walgreens Balance Reward’s loyalty program has had a similar level of success. Walgreens uses personalization within its loyalty program to present relevant offers based on customers’ purchase histories, create awareness of promotional events, point and reward status updates, etc. “We have a continuous culture of improvement,” Lisa Zhao, senior manager, supplier direct marketing at Walgreens, said. “Scale and improve through a test-and-learn approach — channels, offer types, creative, format/vehicles, etc. Identify what works, what doesn’t. This influences future campaigns.” Machine learning and testing mean that AI can constantly refine its customer profiles for greater personalization levels based on what customers respond to. “We have a continuous culture of improvement,” Zhou said. “Scale and improve through a test-and-learn approach — channels, offer types, creative, format/vehicles, etc. Identify what works, what doesn’t. This influences future campaigns.” Overall, AI enables brands to create better customer experiences with a customized and targeted loyalty program.

Related Article: Walgreens Launches Beauty Enthusiast Loyalty Program

Artificial Intelligence Reduces Fraud

Loyalty fraud is an issue that flies under the radar of many customers, and companies are all too familiar. What makes loyalty programs even more vulnerable is the fact that they often go unchecked. Many program members check their accounts every other month. But, members still expect to be protected. According to a consumer survey conducted by Connexions Loyalty and Ipsos, almost all (93 percent) consumers expect their rewards programs to have fraud protections in place. 1 in 4 consumers would cancel their rewards membership if they fell victim to loyalty fraud. Consumers expect companies to have measures in place to protect them from fraud and 33 percent of consumers said they would stick with the program but expect the company to replace their points or miles.

Gartner Security Analyst Avivah Litan told NBC News, “Fraud is moving away from banks and into big e-commerce companies. Criminals are learning how to turn rewards programs, points, and prepaid cards into cash.” Miles and rewards are valuable targets for hackers and others who try to game the system. 72 percent of loyalty program managers had experienced issues related to fraud, and one-third believed that loyalty fraud is a fast-growing phenomenon.

Both findings illustrate a growing awareness of the threat and reveal the need for fraud prevention measures. AI can be used to predict the risk of fraud and to identify potentially fraudulent redemptions. These redemptions can be stopped and examined. Machine learning means that changes in fraud patterns can also be detected and algorithms adjusted in response. Machine learning helps loyalty marketers keep a close eye on both recent behavior and changes to the member profile, historical point transactions, or redemption history and be proactive about the potential for fraudulent activity before it happens.

Artificial Intelligence Drives Customer Experience

When customers express a desire for companies to care about them, they are really asking for a better customer experience. Companies provide a better customer experience by deepening their understanding of the customer. Artificial intelligence drives customer experience by helping companies understand customers, predict what they may want or do next, and respond effectively to the customer. Maximizing the customer experience should happen at every stage of the interaction, from marketing to sales to service. Personalization using AI of the customer experience with information the AI has gathered and analyzed means the most effective message can be delivered to customers by the most effective means. High-value customers can be targeted for both sales and premium service.

Brands like North Face have successfully launched online shopping assistants (Watson) to help customers find exactly what they are searching for. “The retail industry, like many others, is awash in structured and unstructured data — from social media to text messages to customer reviews. By tapping into Watson, retailers now have the power to turn this data into meaningful insights that can make the shopping experience more intuitive, informed, and enjoyable,” said Stephen Gold, IBM Watson VP Business Development & Partner Program.

“At The North Face, our mission is to inspire a global movement of outdoor exploration,” said Todd Spaletto, President, The North Face. “By tapping into the power of IBM’s Watson, we can ensure our customers get the best jacket for the activities they love, whether that’s ice climbing in Montana or skiing in Vermont. This not only improves their online shopping experience, it ultimately maximizes their outdoor experience.”

The landscape of customer loyalty and related programs is changing, but it promises to be a win/win situation for both customers and companies. The ability to gather data via these programs and the accuracy of AI analysis and predictions means that companies can deliver what customers most want to them in the way they most want it delivered. Over time, AI will offer increasingly sophisticated analyses of customer wants and needs and assist companies in demonstrating that they are indeed loyal to their customers.