by Alex Palmer | May 07, 2019

In ways large and small, artificial intelligence has been playing an increasingly important part in our lives. But while many steps are being made to incorporate machine learning into incentives, there has been a paucity of case studies describing best practices.

That is what makes HSBC's credit card customer loyalty program, this year's Grand Motivation Master winner, so exciting: It uses the full capabilities of Maritz Motivation Solutions' innovative data tools while offering examples of how machine learning can target messaging and rewards to better motivate participants. 

Organized each year by Incentive, the awards honor four category winners in the areas of sales, channel sales, recognition and loyalty. In addition, the Grand Motivation Master award celebrates outstanding overall achievement. The winners were announced in March at an awards ceremony held during Incentive Live, Northstar Meetings Group's incentive, loyalty and motivation event at the Fairmont Chicago Millennium Park.

When HSBC sought to encourage members of its loyalty program to spend their points on rewards, the challenge was to cut through their customers' email clutter to draw attention to the program. To solve the problem, HSBC turned to Maritz Motivation Solutions, which had been developing AI capabilities through its recently launched Decisions Sciences division.

Maritz Motivation Solutions Chief Data Officer Jesse Wolfersberger

"As soon as we mentioned 'we've been kicking around machine learning,' HSBC said, 'We were looking to innovate with machine learning, too,'" says Maritz' chief data officer, Jesse Wolfersberger.

For months, Maritz and HSBC's teams batted around questions like which data should be taken into account and which customers were worth targeting for this first attempt at AI-infused outreach. Focusing on the bank card's most mature customer segment, those with the most points, some 75,000 cardholders were sent emails based on one of four AIrecommended categories for individual customers' preferences: travel, merchandise, gift cards or cash.  

Open rates were strong, with most recipients clicking into the emails within the first two days - some 40 percent more than had opened the last rewards pitch. The strong response on redemptions also was impressive: Fully 70 percent of recipients chose gifts in their recommended categories. 

"This performed better than sending out an email saying, 'Here are your points and options,' " says Wolfersberger. "Now we really want to get more specific and broaden the program."