Particular Audience

Most retailers have strong systems, but they make separate decisions. Search optimizes relevance, personalization optimizes engagement, and retail media optimizes yield. DiscoveryOS replaces that fragmentation with one decision at ranking time, using a shared objective. Every product, ad, and creative placement is ordered against a composite goal—net profit per session—balancing relevance, margin, conversion, and monetization in real time. This allows retailers to grow retail media revenue without degrading search quality, increase conversion without suppressing monetization, and align teams around outcomes instead of competing tools. DiscoveryOS powers enterprise-grade onsite search and personalization and is used by leading retailers as their primary discovery system. Retail media performs better inside DiscoveryOS because monetization decisions are made within the same ranking engine that already understands customer intent, engagement, and purchase likelihood. The platform can operate as the decision layer over existing systems, or optionally execute bidding, pacing, and serving across sponsored products, display, and video when consolidation reduces operational friction. Founded in 2017, Particular Audience is AI-native by design, using multimodal machine learning (behavior, language, and vision) to deliver hyper-personalized discovery that outperforms keyword-led approaches by multiples. Headquartered in London, Sydney, and Vancouver, Particular Audience supports global enterprise retailers and contributes to open standards such as the Model Context Protocol (MCP), enabling agentic commerce on retailer-controlled infrastructure. If a product is seen, searched, clicked, or bought—DiscoveryOS decides why.