Particular Audience
We leverage big data and machine learning to know what customers want, often before they do, helping retailers sell more online.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor investor investor | €0.0 | round |
| N/A | €0.0 | round | |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
| investor investor | €0.0 | round | |
* | N/A | N/A | Debt |
| Total Funding | 000k | ||
| USD | 2019 | 2020 | 2021 | 2022 |
|---|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 | 0000 |
| % growth | - | 185 % | 91 % | 154 % |
| EBITDA | 0000 | 0000 | 0000 | 0000 |
| Profit | 0000 | 0000 | 0000 | 0000 |
| EV | 0000 | 0000 | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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Particular Audience operates in the rapidly growing Retail AI market, which is expanding four times faster than eCommerce. The company provides an AI-powered contextual commerce platform that enhances retail media and product personalization for retailers and brands. By acting as an AI layer on top of existing commerce platforms, Particular Audience enables retailers to achieve incremental and high-margin revenue with minimal effort. The platform offers premium exposure to in-market customers for brands, balancing business goals with a flawless customer experience. The company's technology processes over 100 million items, interpreting compatibility and similarity through behavioral comparison, attribute affinity, and visual appearance. This results in superhuman merchandising and product list personalization tailored to each customer's needs. Particular Audience serves retailers and brands looking to optimize their eCommerce operations and improve customer engagement. The business model revolves around providing scalable AI solutions that drive revenue growth and enhance customer experiences. The company makes money through subscription fees and performance-based revenue models.
Keywords: AI-powered, contextual commerce, retail media, product personalization, eCommerce, incremental revenue, premium exposure, behavioral comparison, attribute affinity, visual appearance.