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The Stack Behind the Shorts: How Chubbies Built a Best-in-Class Discovery Experience

10%

lift in add-to-cart conversions

Industry

Fashion & Apparel

Headquarters

Austin, Texas, USA

Solutions

Search & Autosuggest, Browse, Recommendations

10%

lift in add-to-cart conversions

“It’s a four-way partnership where everyone plays to their strength. We own the commerce platform, Constructor owns the intelligence layer, and Form Factory owns the delivery. Ultimately, Nishant and Chubbies get the strongest option at each layer instead of one vendor stretched too thin.”

Dustin Holmstrom

Field CTO at Shopify

Go to the Results

Chubbies has built a brand around personality: bold prints, bright colors, shorter shorts, matching sets, and a shopping experience that should feel as fun as its products.

But the same thing that makes Chubbies’ catalog exciting also makes product discovery more complex. With so many different styles and seasonal moments to shop, Chubbies needed to help every customer find the right product faster.

To do that, Chubbies partnered with Constructor, Shopify, and Form Factory to revamp its search, browse, recommendations, and merchandising experience.

Together, the four companies:

Drastically improved the product discovery experience for new and returning shoppers
Reduced manual merchandising work by letting AI optimize results based on shopper behavior and business signals
Allowed Chubbies to control the data they needed to keep improving the product discovery experience over time
Provided measurable improvements in key business metrics such as search-page-to-checkout conversion, including a 30% increase on mobile and more than 20% increase on desktop

Its catalog includes bold prints, patriotic collections, different inseam styles, matching sets, casual shorts, swimwear, and seasonal drops. All designed for shoppers who want clothes that feel anything but boring.

While that variety is a major strength for customers, it was creating a major challenge for their ecommerce team: how do you show shoppers enough of the catalog to inspire discovery without turning the experience into decision fatigue?

For Chubbies, the answer was to build a more guided, personalized discovery experience that responds to shopper behavior, search intent, and context in real time. The only issue was that they needed the solutions to do so.

Go to the Results

Go to the Results

Chubbies’ legacy keyword-based search engine couldn’t properly understand what shoppers meant, nor connect them to the products they wanted, leading to friction in the shopping journey.

For instance, a shopper searching for bold prints for a vacation should not see the same results as someone looking for a casual pair of shorts. Someone searching for red, white, and blue products ahead of July 4th should not have to decode a generic results page. And someone searching for “patriotic” should not be accidentally routed toward New England Patriots products just because the words look similar.

What they needed was a discovery experience that leveraged behavioral signals, query context, product data, and personalization to infer intent. One that made it easier to surface more relevant products and help shoppers feel confident that they were in the right place.

Chubbies’ legacy keyword-based search engine couldn’t properly understand what shoppers meant, nor connect them to the products they wanted, leading to friction in the shopping journey.

For loyal Chubbies customers, search can be very specific. They may know the name of a particular product, pattern, inseam, or collection. They may come to the site ready to search for exactly what they want.

But Chubbies also brings in new shoppers who do not yet know the brand’s vocabulary. Those customers may have a general idea of what they want — i.e., vacation shorts, a patriotic outfit, something casual, something fun for summer — without knowing the right Chubbies product names or category structure.

The new product discovery solution needed to support both types of shoppers, and this is exactly where Constructor’s ability to infer intent became especially valuable.

Chubbies kept the evaluation focused.

“We knew that we had to improve our search, browse, and recommendation experience,” Nishant Khanduja, Head of Digital & Retention at Chubbies, said. “So we kept it focused on that use case by doing due diligence across what we really needed to solve for.”

The team stayed on Shopify, kept the rest of its tools stable, and evaluated Constructor based on the lift it could bring as a dedicated product discovery layer — via the Proof Schedule®, a complimentary, non-intrusive, and fully supported process that provides actionable insights into tangible ecommerce ROI before signing a contract.

Constructor’s Proof Schedule® stood out for several reasons.

“The Proof Schedule® was really well defined. It was easy to go through the process. It was clearly defined in terms of what we’re looking for, what data, what results we should be keeping an eye on. Moreover, the [Constructor] team was great, So overall, [it was an] extremely pleasant and positive [experience]. Having something that’s so well defined really helped us also plan ahead and make sure that we could align resources and go through this evaluation in the right manner.”

- Nishant Khanduja, Head of Digital & Retention at Chubbies

Plus, the team could see the system working in a sandbox environment, even before they signed on the dotted line.

“Being able to meet with the team and understand what’s going on in a simulated environment, look at search queries, understand what would happen, what wouldn’t happen, and adjust some of the rules on the fly and see how the AI would adjust to ways people were browsing was really the key to us finding a sweet spot through that Proof Schedule®.”

- Nishant Khanduja, Head of Digital & Retention at Chubbies

Just as important, Chubbies knew that with Constructor, they’d have a Data Science team dedicated to their continual success. Constructor’s Data Science teams work around the clock to help clients like Chubbies further optimize algorithms and secure better conversions. It’s all part of Constructor’s complimentary optimization program (more on this later!).

The evaluation included the technical lift as well, which was low because Shopify provided the connective tissue that enabled Chubbies to sync its catalog and product metadata into Constructor more easily.

Overall, a combination of factors gave Chubbies confidence before fully committing: the process was structured, the data was visible, the support was continual, and the potential impact was tied to the actual discovery challenges the team needed to solve.

Chubbies brought the brand, business goals, catalog context, merchandising priorities, and customer understanding.

Shopify provided the commerce foundation needed to support enterprise ecommerce at scale.

“Shopify gives partners like Constructor and Form Factory the commerce primitives that they need in order to not have to rebuild anything from a commerce layer. Our storefront APIs, our web pixels, the combination of Hydrogen and Oxygen and event streams specifically for Constructor means you can plug in your ML directly into the catalog and our behavioral signals, and you can focus on quality product discovery. And we’ll handle the checkout and the payments and everything at scale and compliance.”

- Dustin Holmstrom, Field CTO at Shopify

Form Factory served as the systems integrator, helping translate Chubbies’ business needs into a scalable implementation across Shopify’s composable stack.

Constructor provided the intelligence layer for product discovery, including Search, Browse, Recommendations, merchandising controls, behavioral optimization, personalization, and the broader platform powered by Constructor’s Commerce Reasoning Engine.

Chubbies brought the brand, business goals, catalog context, merchandising priorities, and customer understanding.

Shopify provided the commerce foundation needed to support enterprise ecommerce at scale.

Form Factory served as the systems integrator, helping translate Chubbies’ business needs into a scalable implementation across Shopify’s composable stack.

One of the most important implementation goals was giving Chubbies control without forcing the team back into constant manual merchandising.

“Prior to using Constructor, there were a lot of manual merchandising rules that needed to be set up, slotting, if you may,” Nishant said. “We had to look through the data to understand search queries, create synonyms, so that we would have some results showing up when customers searched for products or certain keywords that weren’t matching exactly with what products we had in the catalog.”
That kind of work can help in the short term, but it becomes difficult to sustain as catalogs grow, customer behavior changes, and trends move quickly.

With Constructor, Chubbies could let AI handle more of the optimization while still giving the merchandising team the transparency and controls they needed.

“After implementing Constructor, we definitely saw that the work was less manually extensive,” Nishant said. “We didn’t have to be in the platform on a regular basis making all of these changes. We allowed AI to make a lot of the optimizations and surface results that were relevant to the customers.”

The result was a more powerful operating model: less unintentional manual work, greater data-backed visibility, and greater confidence that search and browse results were being optimized for shopper behavior and business outcomes.

“At the same time, we also had a lot of data to explain what was done and how things were performing,” Nishant continued. “Less manual merchandising that was not really intentional, combined with having the data to show the results, was a powerful combination for us to really unlock value.”

Those gains reflected the project's core goal: helping shoppers find relevant products more consistently, feel more confident in what they saw, and take action.

“Improving search consistency, search results, accuracy, and getting people more confident in what they’re searching for and what they see, and allowing them to take certain actions based on that is really important,” Nishant said.

The metrics also reinforced a larger point for enterprise ecommerce teams. Search and browse are not just UX features. They are conversion levers. When shoppers use search, they are often showing high intent. If the experience helps them find the right product quickly, the business impact can be significant.

Constructor’s approach made it clear that product discovery should keep improving after implementation. Search and browse are not set-it-and-forget-it experiences. Customer behavior changes, catalogs evolve, seasonal demand shifts, and new use cases emerge.

Through Constructor’s Continuous Optimization Program (COP), Chubbies has already run A/B tests to fine-tune the algorithms powering the site experience.

“So far, we’ve run a few A/B tests to really optimize overall algorithms. One of them was to show results with more accuracy based on what users were searching for. And then another one was to really prioritize some of our browse pages based on different products that would rank again based on relevancy and intent. Both of those have shown about a 10% lift in add-to-cart conversions, which has been great. All of it translates to overall revenue for the business.”
- Nishant Khanduja, Head of Digital & Retention at Chubbies

For Chubbies, that ongoing testing mindset is key. It gives the team a way to keep learning from customer behavior, improve discovery incrementally, and translate those improvements into revenue.

“It’s never done,” Nishant said. “You always think about what’s next, and you’re always optimizing to be better at what you can do.”

Nishant described two priorities for the future: 1. improving product discovery through deeper personalization, including omnichannel intent signals, and 2. enriching product data so both humans and machines can understand the catalog.

This is where Constructor can continue to play an important role.

“We’ve already integrated Constructor into our tech stack. They understand our product catalog, they understand our hierarchy, they understand the complexity, they understand what our use cases are. And now being able to bring that intelligence layer, feed that into LLMs and agents, would unlock a lot of value.”

- Nishant Khanduja, Head of Digital & Retention at Chubbies

Chubbies didn’t start by chasing a broad platform change. The team started by defining the problem.

“For anyone considering a project like this, I would say make sure you do your due diligence,” Nishant said. “Making sure that you can really break down the problem to its core, understanding what you need to solve for, defining your use cases and requirements, and then finding the right partners and tools to work through the problem collectively.”

In Chubbies’ case, no single partner had to stretch beyond its strengths — nor should they need to. Instead, each layer of the stack should do what it was designed to do.

As Nishant further explained, “Everything needs to align. The roadmaps need to work together. When you think about a tool, you need to make sure that this is how we are envisioning scaling up our program, and this is where the tool is going to help us get to the next level.”

For retailers with complex catalogs, that kind of partnership can make the difference between adding another tool and building a stronger commerce experience.

If your team is looking to build a smarter, more connected product discovery experience that drives revenue, book a demo with us. We’ll help you make the right connections and take the necessary actions to reduce manual merchandising work, personalize shopper experiences, and prepare your catalog for the next era of AI-assisted commerce.