Stories

A little Market ( By Etsy )

Uses Algolia to empower local craftsmen by connecting them with buyers.

About A little Market ( By Etsy )

Online marketplace for artisans and buyers in France and Italy


Highlights

Problem

A little Market needed a search solution that was fast, relevant and at the same time not resource-intensive.

Approach

Initial stress test followed by a full fledged implementation.

Result
30ms
Search Speed on the the website
10%
Increase in Search conversion

A little Market is a fast-growing marketplace which focuses on connecting local artisans with buyers all over France and Italy. Founded in 2008, A little Market has millions of products on their website and connects thousands of artisans to millions of users.

The Birth of A little Market

The seeds of A little Market were sown when Nicolas d’Audiffret and Nicolas Cohen met a craftsman named Igor in the South West of France. Igor was passionate about his work - crafting dishes from slate. However, Igor had one problem - he wasn’t able to reach a wide enough customer base for his craft, being based out of a relatively remote area.

After meeting Igor, Nicolas and Nicolas decided to make it their mission to empower artisans like Igor everywhere in France, by creating an additional channel for their craft to reach the right audience all over the country and beyond. After a year of groundwork, co-founders, Nicolas and Nicolas met Loic in December 2008, and A little Market - a platform designed to empower craftsmen and artisans - was born.

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We implemented a legacy search technology 5 years ago and had been trying to tweak it to fit our growing needs. We had selected Solr for its flexibility. However, overtime, that flexibility translated into constant maintenance and modifications, and lower relevance in our search results.

Why Search?

A little Market was designed to empower craftsmen and artisans and a large part of this meant that they had to ensure that relevant products were shown to people on the website through the search bar. However, this was one area that the team hadn’t focused heavily on. In 2013, following a steady rise in community complaints about search speed and relevance, Vincent Paulin, R&D manager at A little Market began to explore search solution providers on the market to help tackle this problem.

The team also decided to revisit their goals so as to determine the nature of their search results. “One of our goals was to kill the ‘0 search results’ response and completely remove it from our vocabulary. The other goal was to find a system that was easy to integrate and could handle the demands of a responsive ecommerce site,” said Paulin.

A little Market’s Unique Requirements

The team at A little Market started evaluating search solution providers, keeping these new goals in mind. However, time was of the essence and resources limited. Paulin quickly realized that it wouldn’t be an easy task to find a solution that would fit his unique business needs. “We heard a lot of good things about open source options and wanted to give it a shot. Open-Source is complex, yet powerful,” said Paulin. “As I dived deeper into it I realized that I could quickly gain an ‘ok’ search experience. However a powerful search experience would mean investing more time than we had to configure it. Then I did a little math. Learning the platform would take a few weeks, configuring servers - a few days, and configuring and finetuning semantic search perfectly - several months. This was a delay we couldn’t afford.” said Paulin.

As I dived deeper into it I realized that I could quickly gain an ‘ok’ search experience. However a powerful search experience would mean investing more time than we had to configure it. Then I did a little math. Learning the platform would take a few weeks, configuring servers - a few days, and configuring and finetuning semantic search perfectly - several months. This was a delay we couldn’t afford.

Discovering Algolia

And then they discovered Algolia. With the hosted nature of the service, Paulin learnt that maintenance work was not needed to ensure a superlative search functionality. He then decided to conduct an initial stress test to ensure that Algolia could help the team scale as well as handle the load of search queries...and was sold on Algolia after the results came through. The average search response time was 30 milliseconds for the couple of million products on the website.

They quickly went through with the implementation and almost immediately began to see an increase in conversions that could be attributed to search. This could be attributed to the real-time, “instant” nature of search queries. Says Paulin, “It was awesome. After this integration of the Algolia API, we saw an increase in our conversion rate on search by 10%. In only a few weeks of work, we had replaced our main search engine with a better solution.”.”

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How Algolia Changed A little Market’s Business Metrics

Implementing Algolia made way for A little Market to start evaluating their performance in an entirely different manner for example, it allowed them to further understand and identify popular objects using Algolia’s search analytics. In fact, this was a part of Paulin’s original objective: “We wanted to improve the overall quality of the search engine and the search experience in general, UI/UX included. But we also wanted to go a little deeper and include ecommerce metrics with a popularity score. Algolia allowed us to achieve just that.”

Today Algolia powers the search for A little Market, and has been instrumental in the reduction of search load by 70%. In addition to this, the growth of the platform can in part be attributed to the search conversions brought about by Algolia. At roughly 10%, this enhanced conversion rate represents tens of thousands of euros worth of turnover every month. Algolia is proud to have been a part of the growth journey of another startup, with French roots.

We wanted to improve the overall quality of the search engine and the search experience in general, UI/UX included. But we also wanted to go a little deeper and include ecommerce metrics with a popularity score. Algolia allowed us to achieve just that.

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