For over 50 years, HBM Machines has been providing makers and builders with reliable, affordable tools they need to do exceptional work.

Founded in Gouda in 1972 as a small tool shop, the family-owned business has grown to operate in seven European countries and offer more than 8,000 products, from humble hammers to full-size lathes and workshop-scale machinery. With such a wide selection across a range of trades, Tessa Vergeer, HBM Machines’ Manager Digital, calls it a “candy shop” for trades professionals.

“You can really browse, get everything into your hands, feel it, see it, experience it,” she says of the physical store, an experience her team works to emulate across the digital world.

The Challenge

Retooling from Homegrown to International Growth

Recreating the tactile experience and sense of exploration found in HBM’s brick-and-mortar flagship showroom in Moordrecht, Netherlands is no small feat, and it’s one that the company’s homegrown website wasn’t built to handle.

It was like a monolith; everything was in one system," Tessa says. "It started as a CMS that gradually had more and more functionality bolted onto it. It grew into a decent webshop, but it was never set up to scale, and it wasn't ready for all the different countries."

On the backend, HBM’s webstore lacked the content management system, product information system, facets and structured data required to power scalable search and merchandising. This made even simple tasks slow and required developer intervention. Tessa explains that the system was inflexible and every change, no matter how small, had to go through development, adding significant delays.

In contrast with its more specialized competitors, HBM’s massive, category-spanning catalog added further search complexity and discoverability challenges. Its existing search tool, Tweakwise, required too much heavy lifting to support and forced the company to hire more resources with each international expansion.

“We needed to create a lot of business rules to get the best results in search,” Tessa notes. “That didn't really help us. We wanted to have a tool that did it for us.”

The Solution

A Complete MACH Rebuild with CommerceTools and Algolia at the Core 

To build the outstanding customer experience that supported its expansion goals and mirrored its physical presence, HBM redesigned its digital platform from the ground up with an API-first, MACH architecture enabling greater flexibility, scalability and speed to innovate while allowing teams to evolve and optimize the experience without dependency on monolithic systems.

It selected Netherlands-based Lab Digital as an implementation partner for this critical replatforming, but not before deciding on the industry-leading tech stack that would be vital to its success: CommerceTools for ecommerce and Algolia for search and discovery, with the latter selected in large part due to its API-first foundations, flexibility and performance, Tessa says.

“Our setup was about choosing best-of-breed options with separate tooling, each focused on a specific part of the website, so we could find the best match for our platform. The API-first setup and the MACH architecture really facilitate that. And of course, that made Algolia an easy choice.”

Tessa was already familiar with Algolia, but it was a demonstration of how the search and discovery engine handled HBM’s product feed before they had tracked events, a PIM or a new data structure that cinched the decision. “Algolia blew us away by showing us what they could do with what we had. It was already so much better than the old platform.”

Implementing Algolia was quick and painless thanks to Algolia’s API‑first model, with Lab Digital handling the technical setup and integrations over one or two sprints (roughly three to six weeks in total) to set up search and browse. “Without them, it wouldn’t be the success it has become,” Tessa says of the partner.

Together, HBM and its partner deployed Search, Facets & Filters, Collections and Recommend across the company’s digital presence. To handle its multilanguage needs, the company decided to build a custom API connection. With its new search solution in place, merchandisers can now hone discoverability, manage sequencing, boosting, banners and collections independently. 

The team is using behavioral signals from views, purchases, and add-to-carts to better tune relevance and influence rankings. 

The Results

Stability, Performance and Merchandiser Empowerment

As the Dutch say, good tools are half the work; Algolia proved to be just that in HBM’s digital transformation.

“It was really quick,” Tessa says of the speed to value from its new search engine. “We were so happy already with the initial results once we had Algolia live. It was a big, big eye-opener that we could see results so quickly.”

She says the MACH-aligned rebuild, with Algolia and CommerceTools at its core, has brought much-needed stability and scalability to the company’s website, consistent across locales. Tessa notes that it now takes only about an hour to have its site ready to enter a new country, something the company has done several times in the past three years since deploying Algolia.

“It’s so easy and automatic, you almost forget you have to do anything to spin up a new country, and that really speaks to the value of Algolia for us.” HBM can now seamlessly support its multinational, multilanguage scope with one unified site and backend, and merchandisers can continually refine product discovery without relying on developers.

“We can increase visibility of products, influence priority, and support online merchandising without the help of developers, which is what we wanted from the start. Merchandisers don’t have to call a developer now every time they want to place a banner, change the sequence of products, or add an asset.”

Tessa says the shift to more data-driven optimization using search data has reduced time-consuming manual workloads and enabling smarter merchandising. 

She notes that Recommend has proven even more important than Search in helping customers navigate HBM’s vast product portfolio. She was especially impressed by Algolia’s ability to deliver useful recommendations based purely on product titles, brand, and descriptions, even before collecting significant behavioral data.

Algolia-powered recommendations are helping imitate the essential in-store experience she and her team strive to recreate, resulting in a significant boost in customer experience.
“It’s hard to deliver that same experience online; that’s where discoverability and recommendations are really important,” she notes.

The work on using search to improve the customer journey is never over, she adds. HBM has formed a small internal team that meets weekly to continually optimize Algolia as merchandisers gain confidence with the platform.

As part of these ongoing improvements, the company plans to test Dynamic Re-Ranking once conversion events are fully in place. Tessa notes she’s curious to see how the feature can support a retailer like HBM, even with a largely non-seasonal assortment.