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On October 21st, 2020, just as my MorphL co-founder Alexandra and I were getting ready to sign a term sheet from an investor, I was looking at our product registrations in HubSpot, and noticed that both the CTO and the VP of Engineering of Algolia signed up for our product on the same day. This, of course, raised a few questions in my head, so I opted for a direct approach: I emailed to welcome them to the product personally, and offered a demo. In our first conversation, Julien and Sylvain were both candid about their interest in joining forces, and we wasted no time in exploring product, value, and market fit.
The rest is history — or at least what we hope will become history. MorphL joined Algolia in January 2021 — here is the story of how and why we got here, and our plans for the future.
MorphL is the third company my co-founder Alexandra Anghel and I started together. We share an entrepreneurial spirit that had us founding a web dev agency in college. While we successfully grew it into a 15-people company, we also both yearned for creating a product. In 2010, our first startup was selected by a tech accelerator in Copenhagen, and while it wasn’t a full-blown success, it provided many gotchas and lessons that led us to founding MorphL in 2017. In September 2018, we got a free grant from the European Data Incubator and started developing MorphL SaaS, pivoting from media publishing to ecommerce, and being selected to the 2019 Techstars Montréal AI Accelerator..
Then came 2020. While the global pandemic slowed down early fundraising efforts, the fall provided ample opportunity for getting investors for MorphL. So when we started talking to Algolia, we found ourselves at quite the crossroads.
Here we are in October 2020. On the one hand, easy to continue on our anticipated path of getting investment — the path we had worked so hard on. On the other, here was this successful large startup whose approach to AI jibed with ours so much it was almost uncanny. Here is what ultimately tipped the scale:
In many ways, I feel like we were riding a bike on this uphill dirt road when a high-speed train went by and briefly slowed down to offer to pick us up. With all the considerations above, and where our hearts and instincts were telling us, how could we say no?
In the ecommerce and media space, user behaviour is king. Just like Google is creating the knowledge graph of the world, and like social networks are building the social graph of the world, we’d like to build the user behaviour graph of the world – and one that fits with the world’s shift to the privacy-first mode.
Our plan is making AI transparent, accessible and easy to use, helping developers and even marketers or product managers create AI-powered applications or websites that predict user behaviours. We like to call this intent-based, privacy-first search and discovery experiences.
Let me offer an example. Today, an ecommerce website will retarget with ads any user that touches their site, even if that user had no intent to purchase, and may have instead just wanted to browse and check out the brand. This is nothing short of digital spamming — annoying to users, and at best useless and at its worst harmful to the company brand. That’s the state of things today. One of the things we offer is a shopping-stage prediction model based, giving companies the ability to be very targeted with who they communicate to — to stop spamming everyone, and only work with users who showed an interest in buying.
Today’s user segmentation in marketing, for example, is often based on demographics, psychographics and such, which raises two issues. First, there is a pandemonium of data that is impossible to sift through manually. Google Analytics alone offers 500 parameters to describe user behaviour, making it nearly impossible and incredibly time consuming to truly understand users. Secondly, technology is still very poor at picking up sophisticated signals from user behaviours on websites and in apps. In both instances, AI offers great advances that will enable people in charge of digital properties to get very sophisticated in understanding their user behavior from the first visit.
As we are starting the integration of our products, I am again struck by similarities in our approaches to everything from the philosophy of product building to the company culture. In the next months and years, my goal is not just to integrate seamlessly but to make an impact. Algolia makes it easy to connect with colleagues around the globe, not just with tools and technology but with everyone’s trust, humility and passion — and the visible desire to improve every bit and piece of the company and the product. This is an exciting playground for my team, and I can’t wait to see what we’ll do together.
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