SAP, Forter Ramp Up Use of AI for Customer Experience

Meghan Hall
·4 min read

Ahead of the NRF “Retail’s Big Show” conference, two major software-as-a-service (SaaS) providers in the retail space announced Thursday that their offerings have been enhanced by further addition of artificial intelligence (AI).

Forter, which focuses on fraud prevention for e-commerce businesses, shared that it had launched a new abuse prevention program, which will help online retailers identify and block policy abuse up front, while still providing high-quality experiences to existing, genuine customers.

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The company, which counts brands and retailers like Eddie Bauer, PacSun, Nordstrom and Reebok among its customers, will use AI-powered technology to enforce its customers’ return policies in a way that takes into account a user’s purchase and return histories.

“We enable our partners to define what policies they want to see. And they can have a very simple UI to do that. They can say, ‘No user can buy more than five items and then return up to three of them.’ We just make sure that we enforce that, and they can decide whatever policy they want,” said Doriel Abrahams, the company’s head of risk.

Abrahams said companies’ policies run the gamut, but regardless of how they manifest, Forter’s new program helps enforce them.

The program comes partly as a result of the persistence of a problem brands and retailers despise: wardrobing. The practice, which occurs when consumers return items after use, adds to an already difficult reverse logistics landscape.

New data from a survey done by The Harris Poll on behalf of Forter shows 36 percent of surveyed consumers said they have returned apparel after using it, and 25 percent of consumers admit to returning footwear after use.

That problem, the data shows, will continue to plague retailers in the early weeks of 2024. One in four consumers purchased products during the holiday season with the intent of wardrobing.

But when considering how to handle repeat wardrobing or policy abuse offenders, brands should consider personalizing experiences on a customer-by-customer basis, Forter contends.

Abrahams said Forter’s new program allows retailers to implement personalized experiences for shoppers based on data a company has about them. If a brand considers a shopper risky, they can put forth different sanctions than they would for a loyal customer with a glowing reputation, Abrahams said.

“Blanket restrictions are typically very, very harmful for the business. In most cases, they’re more punitive towards good users,” Abrahams told Sourcing Journal. “Our tool enables you to basically define what is the desired behavior that you would like—at any specific threshold—so you can identify good users versus suspicious users versus bad users and essentially provide each and every one of them with a different type of experience.”

Customer experience seems to be capturing third-party software providers’ interest in early 2024; SaaS Goliath SAP, which counts companies like Carhartt, Puma, PVH Corp. and Wolverine among its clients, announced Thursday five AI-enabled capabilities to enrich consumers’ interactions with brands and retailers.

SAP added tools for predictive demand planning, predictive replenishment, optimization of sourcing strategy, omnichannel order flow management and digital ad integration into TikTok and LinkedIn.

While the predictive demand planning and predictive replenishment tools are currently in beta, the three other capabilities have already launched.

The capabilities can be integrated for use together, Shardul Vikram, SAP’s chief technology officer and head of data and AI, industries and customer Experience, said.

Each enterprise that uses the data has the option to customize the model for its interests and use cases, Vikram explained.

“We don’t use one customer’s data to train a model to help someone else. Each model is actually trained with the customer’s data only, and then we also give an option for the customer to bring in external sources. The external sources…could be seasonable, it could be things like geographic location, it could be weather, it could be demographic changes, or even news. You could bring in any other sources that you as a customer choose, to begin. Then, the model will take the external as well as your own internal data into account [for its output],” Vikram told Sourcing Journal.

SAP said it anticipates clients that use the capabilities will see boosts in customer satisfaction between 15 and 40 percent; up to 50 percent improvement in order fulfillment and up to a 20 percent surge in employee productivity.

Thus far, Vikram said, SAP has seen a strong amount of interest from retailers and brands in using the technology.

He attributes that to the amount of trust users can place in the systems. SAP’s AI capabilities provide rationales for output, so that users better understand how the systems arrived at a conclusion, as well as what it could mean for a business.

Vikram noted the systems are meant to help optimize humans’ work, which SAP hopes will help retailers and their employees embrace adoption of the technology.

“There is always in the loop because we want to help the store managers and the catalog managers and the e-commerce managers and the retailers to do their job better. We only do that by having them work with [AI] to get them to build trust in the system,” Vikram said.