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

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

It's an area called post-purchase, and it's often one of the costliest and most impactful aspects of operations for retailers. Post-purchase activities include delivery tracking, customer retention and, if necessary, returns. Among the pioneers in the area are Narvar which counts more than 1,500 global retailers, including big brands like Gap, Levis and Sonos among its customers. Across its various customer touch points, Narvar collects information from more than 42 billion customer interactions.

Narvar today expands the information of its services with a new one An AI-powered platform he calls it IRIS (Intelligent Retail Insights Service). IRIS combines data, AI and analytics in an optimized platform. The goal is to help retailers combat fraud, optimize delivery promises, streamline products and create more personalized customer experiences. Among the first services that IRIS is enabling is the AI-powered Narvar Assist, which is designed to automate claims management and help reduce claim delivery fraud.

Early results from a group of 20 vendors show significant improvements: 80% reduction in fraud-related inquiries and 25% reduction in settlements, or the compensation vendors provide for related issues to shipping.

“We don't just solve problems; we are transforming a cost center that has traditionally been 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 sales success

Kumar joined Narvar in 2021 as chief customer officer and became CEO in October 2024. Prior to that, she had a long history working in the trenches of customer operations at Levis Strauss and Co., Walmart and Target where she saw the challenges of salespeople firsthand.

Marketers of all types usually spend a lot of time and effort thinking about customer acquisition. Kumar noted that the big challenge, however, is retaining customers.

“Post-purchase is really thinking about what's that next frontier to keep your customers coming back, and really treating them the way they need to be treated, providing personalized experiences for them,” she said.

With all the data that Narvar collects, AI is now able to help sellers to turn a purchase post into an activity that helps to retain customers. The use of AI in retail operations has struggled overall; for example, a 2024 report from Forrester found high levels of interest, but low levels of adoption.

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

How Narvar is using AI to improve the bottom line

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

Ram Ravicharan, CTO of Narvar, emphasized the power and importance of the company's data to inform AI to help retailers. Narvar processes billions of customer touch points, giving it unparalleled insight into customer behavior and intent.

IRIS Narvar does not use generative AI, although it uses techniques that have pioneered large language models (LLMs), including using transformers.

“If you think of the transactions that people make during the shopping trip as a language, we now have almost no language in which the next sentence is going to be,” explained Ravicharan. “And that's literally how we look at it.”

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

In addition to mitigating fraud, IRIS is also designed to help retailers make more accurate delivery promises and increase customer loyalty. Before IRIS, Narvar tended to rely on rules-based models, especially for commitments such as an estimated delivery date. With the new models, there is more information from across the retail network to provide a higher level of accuracy, Kumar noted. For example, the system is aware of weather issues and carrier delivery systems that affect deliveries.

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

Early adopters see benefits

Narvar Assist technology is not yet generally available, although existing customers are piloting it.

Among those are 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 customers about the delivery of their orders and potential exceptions to improve visibility and customer experience. The company also uses Narvar's Returns and Exchanges solution to automate return processing and provide customer visibility into refund status.

Judd noted that Boston Proper is currently using the first IRIS solution, Assist, which leverages the Narvar ecosystem to reduce costs due to fraud.

“Since integrating Narvar Assist, customer calls and costs have decreased due to the improved user interface and streamlined intelligent processes,” said Judd.

Transition online and in store

Looking ahead, Narvar plans to expand IRIS in a number of ways.

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

“Our vision is to bridge online and in-house environments and the way we've built our models and how we develop transaction intent cuts across channels, ” she said.