As much as we filter, prepare, provision, powder and preen the web, not every user is able to find what they need at the right point in time across the device they prefer (or are compelled to use) in every use case. For Everlane, that’s a pain point that needs to be addressed. Why? Because it is a retail clothing company that promotes sustainability and transparency at every level… so every lost click is (in effect) a waste of user time and electronic resources too.
Looking to sharpen (pun intended) its dress sense in the search intelligence space Everlane has now worked with Algolia to grasp its end-to-end AI search and discovery platform technology. By adopting Algolia NeuralSearch, Everlane is said to be using the power of vector and keyword search with end-to-end AI processing on every search query.
Using Algolia’s AI Search, Everlane says it has achieved a 45% decrease in the return of ‘no results’ (i.e. when a customer searches for a product or service on a website and gets a zero listing result in response), which is a 5% increase in conversions and an 8% increase in its click-through rate.
“No matter what the shopper is seeking, we want them to find their choice quickly and easily – and that is what Algolia helps us do. We want to deliver a distinctive, frictionless customer experience efficiently across our digital channels,” said Rachel Maxwell, senior manager, digital merchandising at Everlane. “Algolia helped us boost our performance while reducing the engineering lift across the merchandising team. This has helped us to optimize the search function on our site.”
As we know, results are important and speed is important too. According to a Deloitte Digital commissioned report that analyzed mobile site data, a seemingly negligible 0.1 second improvement in site speed generated an 8.4% increase in conversions and a 9.2% increase in average order value among retail consumers.
Manual synonym maintenance
“By using Algolia’s AI Search it has simplified data cleanup and manual synonym maintenance and meant that our lean in-house site merchandising team can focus on other priorities. Algolia’s technology has helped to streamline operations and allow our teams to focus on what truly matters—our customers,” added Maxwell.
Through the prowess of Natural Language Understanding (NLU), automatic vectorization, adaptive learning and what are known as ‘ingenious query suggestions’, Everlane’s e-commerce platform now deciphers even the most complex, long tail queries. These are the queries that reflect the way people speak and think – conversational, dynamic and real. In fact, they constitute a staggering 55% of searches.
“Gone are the days of grappling with unwieldy data cleanup and laborious manual synonym maintenance. The introduction of Algolia’s AI Search has orchestrated a paradigm shift, liberating Everlane’s lean merchandising team from this time-consuming ordeal. It’s a testament to how Algolia’s technology, when wielded with precision, can streamline operations and allow teams to focus on what truly matters – nurturing and delighting customers,” added Maxwell.
Since NeuralSearch became part of its strategy, Everlane no longer has to spend time and resources cleaning up its data. The day-in and day-out maintenance across all teams is significantly reduced.
“We are thrilled to partner with Everlane, a trailblazer in the fashion industry. Their commitment to sustainability, creativity and excellence aligns seamlessly with our own ethos of pushing boundaries and delivering unparalleled customer experiences,” said Bernadette Nixon, CEO, Algolia. “Everlane’s voyage with Algolia AI Search is not just a tech upgrade; it’s an embrace of a future where retail seamlessly blends with technology, making every search a delightful journey for the discerning shopper.”
Within Algolia’s end-to-end AI Search and Discovery platform, the company’s engineers invented a breakthrough use of AI to create exponentially better search & discovery. Algolia’s proprietary NeuralSearch tech combines vector-based natural language processing & keyword matching in a single API.