How Narvar is using AI and data to enhance post-purchase customer experiences inkeinspires

What happens after a customer clicks the “buy” button on an e-commerce site?

This is an area known as post-purchase, and it is often one of the most costly and impactful operational aspects for retailers. Post-purchase activities include determining delivery, customer retention and, if necessary, returns. Among the space pioneers is Narvar which has more than 1,500 global retailers, including major brands like Gap, Levis and Sonos. Across all of its different customer touchpoints, Narvar collects information on more than 42 billion consumer interactions.

Narvar is now expanding the intelligence of its services with a new AI-based platform it calls IRIS (Intelligent Retail Insights Service). IRIS combines data, AI and analytics in a highly optimized platform. The goal is to help retailers fight fraud, optimize delivery promises, streamline returns, and create more personalized customer experiences. Among the first services offered by IRIS is AI-powered Narvar Assist, designed to automate claims management and help reduce delivery claims fraud.

Initial results from a cohort of 20 retailers show dramatic improvements: an 80% reduction in fraud-related claims and a 25% reduction in calming measures, or compensation offered by retailers for problems related to shipping.

“We don’t just solve problems; we are transforming what has traditionally been a cost center into a strategic advantage for retailers,” Anisa Kumar, CEO of Narvar, told VentureBeat in an exclusive interview.

Why AI in Post-Purchase Operations is Critical to Retail Success

Kumar joined Narvar in 2021 as chief customer officer and became CEO in October 2024. Before that, she worked for a long time in customer operations at Levis Strauss and Co., Walmart and Target, where she saw first-hand hand the challenges of retailers. .

Retailers of all types typically spend a lot of time and effort thinking about consumer acquisition. Kumar pointed out that the big challenge, however, is retaining customers.

“Post-purchase is really about thinking about the next frontier to retain your consumers, and really treating them the way they need to be treated, giving them personalized experiences,” she said.

With all the data collected by Narvar, AI is now able to help retailers transform post-purchase into an activity that contributes to customer loyalty. The use of AI in retail operations has struggled overall; for example, a 2024 Forrester report found high levels of interest, but low levels of adoption.

As a SaaS offering, Narvar makes it easier for retailers to realize the benefits of AI. Kumar explained that the IRIS platform will help create hyper-personalized post-purchase experiences for retailers and their end consumers.

How Narvar uses AI to improve its results

The IRIS system uses a combination of AI and data services from Google Cloud, as well as proprietary machine learning (ML) and predictive AI algorithms.

Ram Ravicharan, CTO of Narvar, highlighted the power and importance of the data the company has to inform AI to help retailers. Narvar processes billions of consumer touchpoints, giving it unique insights into customer behavior and intent.

Narvar’s IRIS does not use generative AI, although it does use pioneering large language model (LLM) techniques, including the use of transformers.

“If you look at the transactions that people make during the purchase journey as a language, we now almost have a language for what the next sentence is going to be,” Ravicharan explained. “And that’s literally how we see it.”

Using predictive AI models and data, Narvar has a solid understanding of customer intent. This can be extremely useful for customer retention as well as fraud prevention.

Beyond reducing fraud, IRIS is also designed to help retailers provide more accurate delivery promises and build customer loyalty. Before IRIS, Narvar tended to rely on rules-based models, particularly for commitments such as estimated delivery date. With the new models, the entire retail network has more information to provide a higher degree of accuracy, Kumar noted. For example, the system is aware of weather issues and carrier delivery systems that may impact delivery.

“Everyone focuses on acquiring customers, but they lose them and pay to acquire them again,” Kumar explained. “IRIS helps retailers create lasting relationships by delivering personalized experiences when it matters most: after the sale. »

Early adopters see gains

Narvar Assist technology is not yet available to everyone, although it is being tested by existing customers.

Among these is Boston proper. The clothing retailer has been a Narvar customer for 6 years, explained DeAnne Judd, Narvar CIO. To date, Boston Proper has used Narvar’s Engage solution to proactively notify consumers of their order delivery and potential exceptions to improve visibility and customer experience. The company also uses Narvar’s Return and Exchange solution to automate returns processing and provide consumers with visibility into the status of their refund.

Judd noted that currently, Boston Proper uses IRIS’s premier solution, Assist, which leverages the Narvar ecosystem to reduce costs due to fraud.

“Since integrating Narvar Assist, customer contacts and costs have decreased thanks to its improved user interface and streamlined intelligent processes,” Judd said.

Connecting online and in-store

Looking ahead, Narvar plans to expand IRIS in several ways.

While the initial Assist product focused on online transactions, Kumar noted that Narvar is also working with a few retailers to expand in-store capabilities. The Narvar platform provides insights into data and interactions across online, in-store, and even warehouse operations.

“Our vision is to bridge the online and in-store environments, and the way we have built our models and the way we will develop transactional intent crosses channels,” she said.