END. is a global retailer focused on leading fashion, sneakers, sportswear and streetwear based out of Newcastle, England.

Founded in 2005 by based on a shared passion for fashion, sneakers, and the surrounding culture, the company has grown over its nearly 20-year history. Today, it has a strong and valued relationship with more than 500 brands and designers and has built a community of fashion-conscious young customers. The company has branched out from its origins, with eCommerce sites in the U.S., Canada, and around the world. In 2022, END. launched womenswear which is now part of their main site.

“We want to be able to buy clothes that aspire to the customer group that we serve and then sell them in a way that’s quick and easy, with a really top-class service,” says Ruairi Mc Veigh, Head of Product, Payments and Fraud at the company.

“The bit that’s a little more challenging is that we are more of a community-oriented company. Our customers connect through the clothes we sell and the moments we create across multiple activities. That’s what brings our customers back.”

The Challenge

A bid to improve customer experience

To create the best experience for its growing customers, END. strives to provide a sleek website that makes the customer journey seamless and relevant across multiple locales, from discovery to payment.

“It was really about building a partnership,” Mc Veigh says. “That’s why we went with Algolia.”

“Algolia spends a lot of time, money and resources on research and development, and making sure that it is the best in class for not only product search and findability but also recommendations. And there’s some really cool things happening with AI that we’ve been privileged to beta test.”

The solution

Algolia hits the mark

END. deployed Algolia across its site wherever it requires search and indexing functionality The company implemented Algolia for Search, Browse and are working to surface Recommend into its Adobe Commerce-based site. 

The solution not only overcame the challenges the company faced, but its wide range of features opened new opportunities for END.

Mc Veigh says Recommend has provided particularly great value: “It’s something we’ve been working on for two years, and I think we’re in a great position around sending the right amount of information to Algolia —customer information, transaction information, price, stock level, etc. — to feed this into Recommendations so that we can get good product recommendations out without teams needing to manually curate' which is what they previously did!”

END. has tweaked Recommend over the years to meet its unique needs as a clothing eCommerce business. “That’s a great thing for us, we anticipate that this will be a big win for the business as we can then recommend other products for sold out or dead end journeys”

Instead of turning to a competitor for an out-of-stock product, customers are now given alternatives that meet their criteria.

The result

Expanding Algolia’s value

While Algolia is entrenched in its business, Anna Lowe, eCommerce Trading Manager at END., sees the opportunity to take even greater advantage of the platform.

“I think we are only touching, scraping the surface, with what we can do in Algolia at the moment, and I think the extent we can gain value is much bigger,” she says. “For example, this week I’ve just started working on failed searches, and I didn’t know how much I could manipulate it myself without using a developer.” 

One of her first activities when she joined the END. was to test Algolia’s Dynamic Re-ranking (DRR) capabilities against manual merchandising. She found DRR performed “really, really well,” which has reduced the workload for her team. Testing is continuing around revenue driven by DRR, and the next step is to reduce excess indexes with the help of Algolia.

She says END. will soon duplicate indexes between its UK and US websites and localize content. “DRR will be a massive lever for that, because it can help with product localization and optimization by region which is a massive step for us as a business.”

Algolia is helping drive measurable improvements in key performance metrics, including product listing page and product detail page click-through rates (CTR). According to McVeigh, A/B testing with DRR led a 1.47% increase in site conversion rate.

Lowe says Algolia support, including bi-weekly calls with her Algolia CSM, has been “super helpful” as she learns more about the solution and its capabilities.

END. continues to implement and take greater advantage of Algolia. As the company works to deploy carousels to its website, it’s investigating how Algolia Rules can test their effectiveness. For greater customer segmentation, Lowe and her team are currently testing and becoming more comfortable with Personalization.

She says Algolia’s value to the business is “priceless,” noting, “I thought Algolia was just a search platform, but it is so much more than that.”