is an online bookstore based in Brooklyn, New York, with a mission to support local, independent bookstores financially. By design, gives away over 80% of its profit margin to stores and affiliates of stores: publications, authors, and others who make up the thriving, inspirational culture around books. As more and more people buy their books online, creates an easy, convenient way for customers to get books and support local bookstores at the same time.

By partnering with Meilisearch Cloud, the team can enjoy improved search relevancy, reduce maintenance and operational costs and have its engineering team focus on its core business.

The search experience on
"With our prior search engine (Elasticsearch), 14% of searches resulted in a purchase, and with Meilisearch, 20% of searches currently result in a purchase. That's a huge improvement without a lot of development time: 1 out of 5 customers found the book they were looking for and purchased it."
- Andy Hunter, CEO at

Challenge carries an impressive inventory of over six million books. It’s essential for the customer experience that anyone searching for a specific book on the website can find it as fast as possible. A considerable number of books available in the inventory means a proportionally high amount of items that need to be indexed and ranked in the search by the internal team.

You only get one shot at it. We have a lot of visitors that care enough about their communities and ethical consumption - those buyers are specifically choosing to use Bookshop, and we have to make sure that they can find a book as easily as they could find it in other major bookstores or else we're gonna lose them.

- Mason Stewart, CTO at

Prior to switching to Meilisearch, was utilizing a search engine solution provided by Elasticsearch. However, with a small team of eight engineers and many unique customers, needed a solution that would require less maintenance and fine-tuning. Additionally, a more streamlined solution would enable workers across the company to contribute to the ranking rules and configurations, improving the search relevancy on a rolling basis.

Why chose Meilisearch

1. A streamlined process that keeps the decision-makers involved

For the team, the advantage of Meilisearch lies in its simplicity and ease of use, making it possible for decision-makers and non-developers to be very close to the ranking rules. This was necessary to accommodate the ever-changing book search criteria during the busy holiday period and keep the search results relevant at all times.

The fact that we can iterate back and forth quickly and have speedy re-indexing times when we change our rules was a new way of working with search. Previously, only our engineers had the expertise to tweak the rules for book search.

- Mason Stewart, CTO at

2. Quick iterative product cycle

The team also highlighted the quick iterative cycle that has enabled them to solve issues faster. Bookshop's team can directly interact with the Meilisearch team whenever they need to resolve issues or introduce quick fixes. According to CTO Mason Stewart, the company values the combined agility of a compact search engine backed up by a highly responsive team.

3. Ability to outsource hosting and infrastructure maintenance to the Meilisearch team

Ensuring stability in search is essential for the success of the business. After meeting and interacting with the Meilisearch team, the CTO felt confident in entrusting them to manage their Meilisearch servers through the Cloud offer.

Initial value came from the fact that Bookshop started using the Meilisearch open source solution, hosting the infrastructure locally. However, working with it in staging environments and test environments was a harder task for a small team like ours that can't focus on search year-round. We did eventually switch to Meilisearch Cloud because it was better for us to outsource.

- Mason Stewart, CTO at

By transitioning from the open-source version of Meilisearch to Meilisearch Cloud, the team can now concentrate on its primary operations while delegating the management of the search infrastructure to experts.

4. Ability to support the scale and business model fit

The’s extensive inventory, coupled with a high amount of monthly users, made some pricing models that exist on the market untenable for the bookstore’s distinct business model. For a business with low margins, very high volume searches, very high volume users, and a high number of documents, Meilisearch proved to be a perfect fit.


After reassessing its main challenges with book search, the team conducted research and evaluated alternative solutions to address their need for a more user-friendly search solution that requires less maintenance. They came across Meilisearch, which was recommended on a popular tech news discussion platform. A quick test environment was set up out of the box, and the team found that Meilisearch was a good fit as the test continued. The CTO and engineers presented the working prototype to the management, and it was decided to implement Meilisearch before the holiday season, which typically starts at the end of the year. The timing was crucial, as the end-of-year seasonal influx in sales brings a lot of increased consumer activity and a significant portion of profits for a bookseller as a result of it.

The initial demo included connecting Meilisearch to a book catalog and was quick and easy. Then followed the process of balancing and ranking the data that should inform the quality of a result internally, weighing different factors such as how recently the book was sold or how long ago it was published. The team acknowledged that the transition to Meilisearch would have been seamless if a clean data catalog had existed beforehand.

The process of changing the ranking rules to keep the book search relevant for shoppers is very streamlined. Suppose they want to rank a book's description higher or lower in the ranking rules. All they need to do is move it up or down, reindexing the entire catalog and making any change easy. Having global ranking rules that apply to the entire database proved healthy for a small team that needs to understand how one change can impact search across the repository.

After a few weeks of tuning the rules, we've introduced almost no changes. It's been just about perfect.

- Mason Stewart, CTO at

To add to the vision of the future with Meilisearch, the team mentioned that having a multi-index search would be the next most important thing to improve the search experience of the website visitors. Say, a website visitor searches for a specific keyword in a search bar. Multi-index search allows the engine to perform concurrent searches across multiple sources. To that extent, Meilisearch is happy to announce the release of the federated search in v1.1 as an additional step in boosting user experience and increasing relevancy for clients.


With an initial Meilisearch deployment, the team could compare the search performance to the metrics they were getting with a previous Elasticsearch configuration.

By bringing Meilisearch to the table, the team introduced a straightforward configuration process, removing the need to increase the team’s bandwidth or expertise. With Elasticsearch, 14% of searches resulted in a purchase. With Meilisearch, that number jumped to 20%,  increasing overall conversion by 43%.