Algolia’s Meteoric Rise: Charting the Path to a Multi-Billion Dollar Valuation

Want to see something worth $2.25 billion?

Seriously.

Algolia — a SaaS company — offers companies a better search bar. That’s it. 

And it’s worth billions.

They estimated their target addressable market at $14 billion in 2021 and predicted that they would grow to $86 billion in the next decade. And they’re on their way. 

Nicolas Dessaigne and Julien Lemoine co-founded Algolia in 2012, and they marketed the company as a cheap tool for new developers to add a search bar easily.

How did they make that shift into a valuation worth billions?

Let’s break it all down.

What Algolia Does

Algolia started as a search bar that developers could plug into their websites. Since then, they’ve developed two main products: 

• AI Search: A quality search bar built into a website that’s activated in minutes. There are all kinds of features that make it better than other search bars, but that’s the nuts and bolts.
• AI Recommendations: A product recommendation tool that automatically shows a carousel of recommended products or content.

Better Internal Search

AI Search combines semantic and keyword searches to offer a fantastic search bar for your website, providing better, more relevant results.

The difference between semantic and keyword searches is that semantic searches are more about search intent. If an item is labelled as a “canteen”, a “flask”, or a brand name, it might not appear in a keyword search for “water bottles”. However, semantic search presents relevant websites relating to the keyword, not just exact matches. Algolia’s search bar combines both search types to deliver the most relevant results.

The truth is most sites’ search bars would benefit greatly from Algolia’s offering. Because, for most sites, internal search is pretty poor. In fact, 69% of websites can’t autocorrect slight misspellings in search terms, and 71% can’t handle different product jargon like the water bottle vs. canteen example.

The result? Frustrated visitors who can’t find what they need and go elsewhere to find it. Companies that optimize their site searches can see an increase in conversion rates of up to 43%. The ones that make it hard for visitors to find what they’re looking for are leaving money on the table.

But Algolia has more to offer than a search algo. They use AI alongside semantic and keyword search to:

• Categorize the results users are interested in and provide more relevant results in future searches.
• Identify and boost trending content.
• Give personalized results based on users’ reactions to past searches.

To showcase the difference between sites using Algolia’s technology and those that don’t, I searched two sunglasses sellers for Carrera-brand sunglasses, using the term “shades”. I made sure that neither site sells Carrera products nor categorizes any sunglasses under that term.

Under Armour uses Algolia, and I had no trouble getting relevant search results.

Algolia still knew I wanted sunglasses, so they offered some styles similar to my search term. 

Then, I tried that exact search on a major sunglasses retailer that doesn’t use Algolia:

The results speak for themselves, I’m sure they have sunglasses similar to Carrera’s designs, but I’ll never know. 

The moral of the story? Algolia knows only too well the pain of ineffective search for the site visitor and for the site owner.

Recommendations for Those Who Don’t Search

Some might say using all of this advanced AI-powered technology only for searches would be a waste.

But Algolia already knows this. That’s why they created AI Recommendations.

Where Algolia’s search product can customize search results to match trends, personal preferences, and related products, the recommendations engine can do the same even if you don’t search.

If you’ve seen a carousel labelled something like “people also bought” or “you might also like,” you’ve benefited from an algorithm like Algolia’s. These e-commerce recommendations provide lists of items customers might like based on the buying patterns of similar site visitors. Here’s an example from one of Algolia’s customers, Gymshark: 

Carousels like these mean that even if someone goes straight to your site and finds what they want, you can still tempt them with other nifty products (AKA cross-selling).

Pages per visit — how many pages on the website they clicked on before they left — is a good indication of how well this works. So, we compared Gymshark to four other major gym wear retailers.

The other retailers have more brand recognition, more monthly visits, and almost certainly more revenue than Gymshark. But Gymshark’s site visitors visited an average of 8.86 pages per visit, the highest among the group, and 11% higher than the second best. 

Gymshark also saw a lower bounce rate than the other retailers, clocking in at 39.12% compared the 44.31% average. That means people visiting Gymshark’s site are looking at several pages, most likely recommended by Algolia’s recommendations engine. 

The returns from this kind of design can be significant. One experienced analyst from Forrester believes on-site recommendations from sites like Amazon bring in conversion rates as high as 60%. In Gymshark’s case, they saw a 150% increase in order rate and a 32% increase in “add to cart” when they used Algolia for their Black Friday sale.

Algolia has built a powerful product that helps websites deliver highly relevant results to their visitors. The strength of that algorithm has been a massive part of their success, but their products weren’t always the API-based, AI-powered engines the are today. 

So how’d they get to where they are?

Algolia’s Rapid Rise

Algolia initially struggled to find their identity. But after their founders grappled with tough Y Combinator interviews, they pivoted their product. Instead of a cheap, single-purchase, and single-purpose software development kit (SDK), Algolia became powered by an application programming interface (API).

That meant Algolia could build a much more powerful search algorithm while making it scalable for their customers. It also made it easier for their new customers to implement. The API is platform- and language-agnostic, meaning you can use it no matter how you’ve built your website.

That new focus on developing an API let them expand rapidly. They returned to Y Combinator and secured $120,000 in pre-seed funding in March 2014. That turned into seed funding, totalling $2.8 million by the end of the year. But that was just the beginning.

Growing Their Partnerships

As Algolia kept growing, their valuation skyrocketed. While we don’t have data on their early valuation, you can see the wild ride since their Series B funding.

Their initial seed funding quickly exploded to over $18 million the following year. From there, Algolia took on new funding every two years, growing their valuation each time until the most recent round in 2021 culminated at $2.25 billion. That’s almost quadruple growth between 2019 and 2021.

But it’s not about the money. 

Well, it kind of is, but it’s not all about the money. 

As they’ve grown, they’ve done an excellent job selecting investors who bring them true value. For example, one of their Series C investors was Salesforce — one of the largest SaaS companies in the world, with a market cap of $278.65 billion.

More than that, Salesforce powers over 150,000 companies with their customer relationship management (CRM) software. They’re the perfect advisors for an e-commerce-focused SaaS company looking to expand.

Another great partner for Algolia was Twilio. Twilio makes API-based customer experience products like Algolia does, and they’ve also succeeded by making their products developer-centric.

By partnering with the right companies as they grew, Algolia positioned themselves to use their funding wisely for maximum growth.

Investing in AI

In the last three years, Algolia has made two major purchases to propel their growth: Search.io and MorphL.

MorphL, specializing in AI-powered predictive experiences and personalization, enabled Algolia to launch “Predict”, a product that later became part of their AI Search offering. This integration brought advanced machine learning and personalization to Algolia’s platform. 

Meanwhile, Search.io, known for its innovative vector search technology, allowed Algolia to provide more nuanced and contextually aware search results. 

Why They Succeeded

Algolia succeeded because they capitalized

on trends in their industry, took part in a rapidly growing market, and targeted customers of all sizes with a real solution. How do I know? Well, they presented that in their pitch deck for the most recent funding round.

The slide above sums things up.

• They see their serviceable addressable market (SAM) growing to $30 billion by 2026.
• The total e-commerce market doubled in revenue between 2019 and 2021 (when this slide was created), and Algolia was powering e-commerce sites at that time. 
• They positioned themselves at the center of important market trends, such as headless e-commerce search, a market projected to grow 22.5% annually through 2030. 

Let’s dig a little deeper into that last point. 

Algolia’s frontend search bar, powered not only by the site’s code but by an API, helps customers benefit from Algolia’s algorithm while allowing them the flexibility to design their UX as they wish. The headless trend (where frontend is separate from backend) has exploded recently, led by companies like Shopify, whose valuation has grown by 500% since 2019. By positioning themselves within trends, Algolia could ride that wave.

Finally, Algolia grew because they approached their sales from two separate directions: self-service for smaller customers and direct sales for enterprise-level customers. In general, self-service sales work great when you’re targeting smaller businesses and don’t want to devote resources to negotiating with each one. On the other hand, direct sales require salespeople and are more costly, so they are often reserved for enterprise deals that can make your revenue explode.

With a growing market, a wave of trends behind them, and a flexible sales strategy, Algolia saw 300% growth in just a couple of years. 

It certainly doesn’t hurt when the rest of your industry is growing, too!

The Future of Algolia

So, where do you go when you’ve already hit hypergrowth? Well, we can’t leak audio from Algolia’s most recent board meeting. But, based on market trends and their journey, Algolia still has excellent growth opportunities.

Expanding Voice and Image Search

Algolia’s incorporation of voice and image search options will help them continue to capture e-commerce trends. With half of US consumers using voice search daily, this feature is vital for e-commerce sites to capture and engage with a growing segment of users who prefer voice interaction.

Similarly, Algolia’s visual search taps into the rapidly expanding visual search market, already valued at over $9 billion. This feature allows customers to search using images, catering to the growing preference for visual information processing and enhancing UX on e-commerce platforms.

Whether you’re a marketer, developer, or UX designer, be ready for the next kind of search. You want to be able to quickly adapt your site to voice search, image search, or something else we haven’t even heard of yet. So, keep your ear to the ground for what’s coming next.

But just listening for existing trends won’t be enough. 

Growing Developer Support

Algolia has benefited from a strong developer community that loves their platform. Their services are easy to use and integrate with many other tools. Plus, they’ve marketed directly to developers in the past. 

Moving forward, Algolia is expanding on documentation, making the product even more accessible. Documentation represents an investment, since technical writing is expensive, but it makes developers’ lives significantly easier.

Algolia also signalled a bigger investment in their customers when they launched their developer conference in 2022. They invited their CEO and CPO to the opening and included 37 other speakers from Algolia to present on everything from AI fine-tuning to new product releases.

These moves directly support the developers who work with Algolia daily. They’re a great marketing strategy because if developers prefer Algolia, the websites they build, optimize, and maintain will use Algolia’s products. Algolia’s documentation library and its conference are investments in an audience that will strongly influence the buying decisions that matter most to Algolia.

The secret here is that Algolia targets a critical audience who can advise the CTO in their buying decisions. 

What to Learn from Algolia

Algolia, now valued at over $2 billion, transformed from a basic search bar tool to a comprehensive SaaS offering, driving immense growth. Key to this success was pivoting to an API-driven approach which enhanced scalability and ease of integration. 

Strategic acquisitions in AI, like MorphL and Search.io, bolstered their capabilities in predictive and nuanced search. Partnering with significant investors like Salesforce and Twilio, Algolia capitalized on market trends and developed a robust sales strategy, leading to a rapid increase in valuation. It’s a thrilling story and a fantastic lesson in how to capitalize on your strengths.