Early Birds
Early Birds and Attraqt enable international brands, manufacturers and retailers to optimize their e-commerce site performance by delivering exceptional shopping experiences to their customers.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor investor investor | €0.0 | round |
| investor investor | €0.0 | round | |
| investor investor | €0.0 | round | |
$17.8m Valuation: $18.0m 4.1x EV/Revenue 31.6x EV/EBITDA | Acquisition | ||
| Total Funding | 000k | ||
| EUR | 2018 | 2019 | 2020 |
|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 |
| % growth | - | 88 % | 34 % |
| EBITDA | 0000 | 0000 | 0000 |
| % EBITDA margin | (6 %) | 13 % | 18 % |
| Profit | 0000 | 0000 | 0000 |
| % profit margin | (27 %) | 8 % | 5 % |
| EV | 0000 | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 | 0000 |
Source: Company filings or news article
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Early Birds, founded in 2012 by Laetitia Comès, Nicolas Mathon, and Luc Falempin, developed an AI-driven personalization platform for e-commerce. The company originated from the founders' shared experience at a digital services firm, where they identified a market need for more sophisticated and open recommendation tools, moving beyond the 'black box' solutions prevalent at the time. Their vision was to empower brands with transparent, customizable algorithms to enhance the online customer journey. This approach attracted significant clients such as Cdiscount, La Redoute, and Fnac Darty.
In 2019, the UK-based company Attraqt Group PLC acquired Early Birds for a total consideration of €15 million, a strategic move to integrate Early Birds' advanced AI capabilities with Attraqt's data-led search and merchandising tools. Following the acquisition, the combined entity now operates under the name Attraqt. The company serves international brands, manufacturers, and retailers by enabling them to orchestrate individualized shopping experiences. The core offering is a platform that allows business, data, and technical teams to leverage AI models in real time, build bespoke personalization strategies, and create differentiated customer journeys at scale. This helps clients improve key performance indicators like conversion rates and average order value by delivering relevant product recommendations and content.
The platform's business model is centered on providing this powerful e-commerce personalization and search technology to large retail enterprises. It allows clients to unify various data sources and deploy machine learning algorithms to tailor the online shopping experience from discovery to purchase. This integration of search, merchandising, and AI-driven personalization provides a comprehensive solution for retailers aiming to meet evolving consumer expectations and achieve their commercial objectives. Keywords: e-commerce personalization, AI recommendation engine, customer journey optimization, retail technology, merchandising software, SaaS, predictive analytics, user experience, online retail, conversion rate optimization