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Belk Unlocks Next-Level Ecommerce Conversion and AI Innovation with Constructor

belk-black
$35M
in revenue
Industry
Retail
Headquarters
Charlotte, NC
Solutions
Search, Autosuggest, AI Shopping Assistant
belk-black
$35M
in revenue
“Hey, did you see Belk has a shopping assistant?” has become a word-of-mouth driver that’s elevating the brand’s reputation as an innovator. In addition to the revenue increases, it’s generating curiosity and creating new reasons for shoppers to visit their site.
richard-spencer
Richard Spencer
CIO, Belk
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Summary

Executive Summary

Read on to learn how Belk, the largest privately owned department store chain in the United States, overcame three critical challenges in search and discovery:

  • Scaled beyond manual effort with a fully automated solution that delivered immediate ROI
  • Unlocked real value from conversational AI — not as a gimmick, but as a revenue driver via AI Shopping Agent (ASA)
  • Achieved sustained optimization through a Revenue Optimization Program that delivered long-term business impact, not just a one-time lift

About Belk

Belk is a long-standing department store chain with nearly 300 locations across the United States, offering a wide range of apparel, cosmetics, home furnishings, and accessories.

For more than a century, Belk has earned the trust of millions of customers by delivering quality products and outstanding shopping experiences, both in-store and online.

Go to the Results
belk-aboout@2x
belk-aboout@2x

For more than a century, Belk has earned the trust of millions of customers by delivering quality products and outstanding shopping experiences, both in-store and online.

Go to the Results

The Challenge

Meeting Growing Customer Expectations

As Belk’s digital business continued to grow, the team recognized that search and discovery would play an increasingly important role in delivering the seamless shopping experience their customers expect.

At the time, Belk’s existing search solution had been in place for many years. With shopper habits changing rapidly and almost 40% of sales now happening through mobile, the team saw an opportunity to explore what new technology could make possible. As their CIO, Richard Spencer, shared, “It had been a decade since we really looked at our search solution — we knew it was time for a change.”

Three urgent needs were top of mind:

  • Scale beyond manual work: Their team was spending countless hours fine-tuning queries and results. They knew they couldn’t continue growing while relying on manual overrides and guesswork

  • Modernize guided shopping: Customers wanted more intuitive, personalized journeys. Belk needed a solution that could offer smart, conversational guidance

  • Drive ongoing performance improvements: One-time fixes weren’t enough. The team wanted a partner committed to compounding returns over time through continuous optimization

The Challenge

Heavy Reliance on Manual Interventions

To maintain high standards for their search experience, Belk’s team put in significant work behind the scenes. They closely monitored queries, made refinements, and added redirects where needed to ensure customers found suitable alternatives.

For example, if a shopper searched for a brand Belk didn’t carry, the team would manually create a redirect to similar products they did offer. While this hands-on approach kept things running smoothly, it depended heavily on the team’s expertise and judgment.

Over time, they saw that even well-informed guesses were still broad solutions — they might help the majority of shoppers, but couldn’t always match what each individual shopper was looking for in that moment. The team knew that to meet shoppers’ individual needs, they’d need something more dynamic than manual fixes alone.

belk-challenge@2x
belk-challenge@2x

To maintain high standards for their search experience, Belk’s team put in significant work behind the scenes. They closely monitored queries, made refinements, and added redirects where needed to ensure customers found suitable alternatives.

For example, if a shopper searched for a brand Belk didn’t carry, the team would manually create a redirect to similar products they did offer. While this hands-on approach kept things running smoothly, it depended heavily on the team’s expertise and judgment.

Over time, they saw that even well-informed guesses were still broad solutions — they might help the majority of shoppers, but couldn’t always match what each individual shopper was looking for in that moment. The team knew that to meet shoppers’ individual needs, they’d need something more dynamic than manual fixes alone.

The Solution

Searching for a Partner — Not Just a Vendor

belk-solution@2x

When Belk began evaluating new options for search and product discovery, they looked at several solutions. One of the biggest draws to Constructor was its focus on shopper intent. After a rigorous A/B test across platforms, Constructor’s results stood out.

“Constructor won in pure testing,” Spencer shared. But it wasn’t just about the results — it was about the partnership. “They didn’t just hand us a product — they worked with us to set things up for success. We felt like we were gaining an extension of our own team that shared our goals and guided us to good decisions.”

When Belk began evaluating new options for search and product discovery, they looked at several solutions. One of the biggest draws to Constructor was its focus on shopper intent. After a rigorous A/B test across platforms, Constructor’s results stood out.

“Constructor won in pure testing,” Spencer shared. But it wasn’t just about the results — it was about the partnership. “They didn’t just hand us a product — they worked with us to set things up for success. We felt like we were gaining an extension of our own team that shared our goals and guided us to good decisions.”

belk-solution@2x

Seamless Integration with Powerful Data

Constructor’s Proof Schedule™ gave Belk the ability to validate improvements in real time before making a final commitment. With Constructor’s testing and optimization approach, the Belk team could confidently shift away from manual guesswork and toward data-driven results.

Search results became more dynamic, automatically adapting to what shoppers were really looking for, which freed up the team to spend more time on strategic initiatives.

The Results

Proof of Performance

Belk saw measurable results right from the start. During the Proof Schedule™, the team validated an initial uplift of $21 million in revenue from core search, giving them the confidence to move forward with Constructor.

From there, Belk and Constructor launched a Revenue Optimization Program — an ongoing cycle of testing and fine-tuning designed to build on early wins and find new ways to improve. By closely analyzing real shopper behavior, Belk’s team and Constructor identify what’s working, what could work better, and where to test next — turning search into a steady source of incremental growth.

$35M
in revenue
+7.4%
revenue per visitor
>2X
CVR from AI Shopping Assistant

So far, this program has delivered an additional $35 million in revenue, bringing Belk’s total compounded Revenue Per Visitor lift from Constructor’s search optimization to 7.4% at the time of writing.

The Challenge

Driving Innovation with AI Shopping Assistant On The Mobile App

One area where Belk’s team had been eager to innovate was guided shopping. A few years ago, they began building their own version of a product finder to help customers discover the right items more easily.

belk-wide@2x-1

They were excited to experiment with AI for this, since traditional form-based or chatbot solutions required mapping out countless pathways by hand — a process that wasn’t practical for their team to maintain or scale.

However, the toolkit they were using didn’t fully support their mobile app, which was critical given that nearly 40% of Belk’s business comes through mobile. That gap made it challenging to fully realize their vision for a more personalized, conversational shopping experience.

Constructor’s AI Shopping Agent (ASA) helped Belk overcome both challenges on the mobile app. Instead of relying on fixed scripts, ASA uses real-time data to understand each shopper’s intent and guide them to the best results.

Today, ASA is delivering impressive results. Conversion rates for shoppers using the assistant are double or better than standard search.

Customers love the experience, too. According to Spencer, “Hey, did you see Belk has a shopping assistant?” has become a word-of-mouth driver that’s elevating the brand’s reputation as an innovator. In addition to the revenue increases, it’s generating curiosity and creating new reasons for shoppers to visit their site.

belk-asa@2x

Constructor’s AI Shopping Agent (ASA) helped Belk overcome both challenges on the mobile app. Instead of relying on fixed scripts, ASA uses real-time data to understand each shopper’s intent and guide them to the best results.

Today, ASA is delivering impressive results. Conversion rates for shoppers using the assistant are double or better than standard search.

Customers love the experience, too. According to Spencer, “Hey, did you see Belk has a shopping assistant?” has become a word-of-mouth driver that’s elevating the brand’s reputation as an innovator. In addition to the revenue increases, it’s generating curiosity and creating new reasons for shoppers to visit their site.

belk-asa@2x

Moving Forward

What’s Next for Belk

Belk is continuing to expand what’s possible with Constructor. The teams are already collaborating on new ideas — like an in-store version of the AI Shopping Assistant that can help customers find the perfect gift and locate it right on the shelf.

Visual search is another area of opportunity that Belk is exploring to bridge the gap between browsing and search on their app. As the CIO put it, “Kat and the Constructor team have been really supportive when we bring new ideas forward. We’re excited to keep growing together.”

belk-moving-forward@2x
belk-moving-forward@2x

Belk is continuing to expand what’s possible with Constructor. The teams are already collaborating on new ideas — like an in-store version of the AI Shopping Assistant that can help customers find the perfect gift and locate it right on the shelf.

Visual search is another area of opportunity that Belk is exploring to bridge the gap between browsing and search on their app. As the CIO put it, “Kat and the Constructor team have been really supportive when we bring new ideas forward. We’re excited to keep growing together.”

Is there room for improvement with your current search vendor?​ Find out.

Reach out to a Constructor Product Discovery Specialist to learn how our testing helps surface gaps so you can make a data-driven assessment.

Book a Demo

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