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Can AI deliver increased loyalty effectiveness?

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By: Mike Capizzi, CLMP™ |

Posted on March 15, 2018

At the recently completed 3rd Annual Loyalty Academy Conference, featured speaker Dr. Rachel Royal from Owens Corning engaged the audience with a conversation starting session on AI and its future in loyalty marketing.  The discussion was lively following Rachel’s outline of where we are and where we likely going with AI.

By Mike Capizzi

This week, Loyalty Academy Conference Sponsor, Maritz Motivation Solutions, announced a leading-edge AI application to predict the redemption of loyalty program awards associated HSBC’s new suite of credit cards. While there hasn’t been a lot of development with AI in the loyalty space, the collective sense of last week’s conference audience is that new tools are coming, and they are coming fast. Armed with mountains of data about member preferences, transactions, demographics, past reward redemptions and social/digital behaviors, any loyalty marketing program would benefit from the use of machine learning to predict or enhance future outcomes.

Key quote from Jesse Wolfersberger, Sr. Director of Decision Sciences at Maritz,

"This use of AI with HSBC's card program is one of the first in the loyalty sector and demonstrates that artificial intelligence and machine learning are the future of business. We're going to witness more companies using AI to engage people in new and innovative ways.”

Maritz's AI algorithm, also known as machine learning, predicts the rewards a loyalty program member is likely to redeem over the next year. The AI then suggests a redemption category to promote to each member and calculates the percentage of clients likely to redeem in different categories. Both relevancy and efficiency are enhanced by this approach – speaking directly to likely member wants, with a reduced cost of catalog options.

But can AI deliver increased effectiveness?

The HSBC promotion involved 75,000 credit card rewards members. Cardholders were sent e-mails based on the AI recommendation in one of four categories: travel, merchandise, gift cards and cash. A control group received an e-mail with a random category. Of those who received the targeted messages and redeemed, 70% redeemed in the AI recommended categories. The number of opened e-mails increased 40% among the AI group.

Wolfersberger added, "In the HSBC campaign, we found that the AI promotion was three times more efficient than the control group. In today's competitive landscape, instead of a scatter-shot approach, companies and brands now have the latest tool to engage and delight customers, make their rewards programs more effective and increase the return on their loyalty investment. From the brand perspective, the use of AI allows companies to serve customers better with a more customized and targeted loyalty program that results in significant operational cost savings."

Rewards are typically the most expensive element of any loyalty program, especially in the credit card space.  Catalogs need to cover a huge range of possible redemption options increasing expense and operational complexities while adding to a communications stream suddenly bloated with irrelevant offerings.  While recent talks suggest everyone just wants to convert all this redemption behavior to a frictionless form of cash at POS, AI offers the promise to dramatically improve the traditional redemption process.  No human being could possibly sort through the myriad of variables and options, but the machine can, and it learns quickly.  From a loyalty marketing perspective, don’t sound the death bells yet for travel, merchandise and experiential rewards redeemed and delivered in the traditional non-cash methods.

From the business perspective, any tool which helps increase relevancy, efficiency and effectiveness in a loyalty marketing program is a tool that should be adopted.  We can’t wait to see what’s coming next down the AI pike.

Mike Capizzi is a Certified Loyalty Marketing Professional™ (CLMP) and Dean of the Loyalty Academy.