# Particular Audience > Retail discovery, retail media and agentic commerce infrastructure for retailers. Search, recommendations, personalization, pricing intelligence and sponsored placements ranked together on relevance and yield. Particular Audience gives retailers one ranking layer across on-site search, recommendations, merchandising and retail media. DiscoveryOS is the hub where trade, retail media, merchandising and ecommerce teams control the on-site experience and run ad operations. RevenueOS is the CRM, sales and FinOps terminal for retail media revenue teams. An MCP endpoint at /.well-known/mcp.json lets AI agents query capabilities, case studies and RFP requirements directly. ## Platform - [Platform Overview](/platform): One relevance stack behind search, personalization, merchandising and retail media. See the four pillars, how the modules combine, and the results in production. - [Module Explorer — 15 AI Capabilities for RMNs](/platform/modules): Explore 15 modular retail media capabilities: sponsored search, display ads, product recommendations, data intelligence, and conversion optimization for retail media networks. - [Surfaces — Every Touchpoint in the Shopping Journey](/platform/surfaces): Search, listing, product detail, add to cart, checkout, landing pages and email. One ranking intelligence layer applied to every surface. - [DiscoveryOS — On-Site Experience & Retail Media Operations](/discovery-os): The hub for trade, retail media, merchandising and ecommerce teams to control the on-site experience — search, recommendations, merchandising and retail media ad ops. - [RevenueOS — CRM & FinOps for Retail Media Sales](/revenue-os): The CRM, sales and FinOps terminal for retail media sales teams: brand accounts, pipeline, rate cards, packages, bookings, yield, billing, reconciliation and receivables. - [Unified Ranking — Organic + Sponsored in One Engine](/unified-ranking): See how Particular Audience unifies organic and sponsored ranking, and why organic itself is a multi-objective problem spanning private label, overstocks, trade agreements and more. ## Retail media - [Sponsored Search — Signal-Led AI vs Keyword Targeting](/sponsored-search): Why Particular Audience's sponsored search beats keyword-targeted auctions. Transformer vector retrieval, gradient boosting and unified ranking — quantified with Bosch, PetAds and Face the Future case studies. - [Retail Media Yield Engine — Benchmark & Grow Your RMN](/yield-optimizer): Model CTR uplift, query coverage, and inventory expansion to forecast retail media network growth. Benchmark your RMN against industry scenarios with compounding revenue levers. - [Unified Demand Aggregation — Particular Audience](/demand-engine): Connect to every major demand source through a single integration. PA runs a unified auction with relevance gating for maximum yield. - [Automated Ad Set Builder](/ad-set-builder): The first one-click campaign builder for retail media. Launch AI-powered Sponsored Product and Sponsored Search ad sets across CPC, CPM and CPA in a single action. ## Discovery and personalization - [Pricing Intelligence — Data, Elasticity and Automated Policy](/pricing-intelligence): Competitor price data from Similar Inc, elasticity modeling and automated onsite price match. Turn price feeds into ranked decisions, then act on them. ## Agentic commerce and MCP - [Agentic Commerce — Particular Audience](/agentic-commerce): AI agents show 2-4 products, not 200. Connecting your catalog isn't enough — you need transformer vector search for relevance, governance, and retail media in the AI agent channel. ## Case studies - [Case Studies](/case-studies): Explore retail media, discovery, search, and price-match case studies from Particular Audience — filterable by product area and case type. - [Retail Media: Challenger vs Incumbent](/case-studies/retail-media): Interactive case study comparing Sponsored Product and Sponsored Search performance across 8 brands on a Particular Audience Retail Media Network. - [Grocery search relevance — +65% catalog coverage](/case-studies/grocery-search-relevance): How a top-10 North American grocer replaced keyword search with transformer vector search: +65% recall@120, +19% nDCG@120, 40% fewer severe misses, graded across 705 terms and ~169k product judgements. ## Resources - [RFP & RFI Builders — Particular Audience Resources](/resources): Free interactive RFP / RFI builders for Personalization, Search & Merchandising, Price Beat and Retail Media. Pick the requirements, export to Excel or PDF. - [Whitepapers — Retail Media AI, MCP & Adaptive Search](/whitepapers): Download Particular Audience whitepapers on Retail Media AI Architecture, the Model Context Protocol (MCP) for retail, and Adaptive Transformer Search. Technical briefs for retail and RMN leaders. - [Retail Media Revenue Calculator — Forecast 30+ Ad Products](/retail-media-calculator): Free retail media revenue calculator. Model 30+ ad products across 14 retail verticals with 5-year forecasting, marketplace mix, and private label adjustments. Build your RMN business case. - [Blog — Retail Media, Search & Personalization](/blog): News, research and product thinking from Particular Audience on retail media, search, personalization and price intelligence. - [Learn — How Retail Media, Search & Personalization Work](/learn): Explainers and playbooks on adaptive transformer search, personalization, bundling, unified ranking and retail media strategy. ## Company and technical - [Developers & Architecture — API-First, Headless, Composable](/developers): How Particular Audience plugs into a composable stack: API-first and headless delivery, SDK and tag options, catalog and event ingestion, ranked-ID responses, multi-region SaaS and a public MCP discovery card. - [Security & Data Handling — Particular Audience](/security): Encryption, least-privilege access, US, EU and AU data regions, penetration testing and incident response — plus the shopper data we deliberately never collect. - [How Pricing Works — Particular Audience](/pricing): Modular, usage-metered pricing: what each capability is measured by, what is always included, what sits outside the subscription, and how a quote is built. ## Optional - [Face the Future — Relevance vs Bid retail media case study](/case-studies/face-the-future): When Face the Future swapped relevance for bid-led auction logic, ad scale rose 9× but CTR collapsed -87.3% and sitewide conversion fell. The relevance-first proof point. - [Bosch — Gradient boosting in retail media search](/case-studies/bosch-tcl-gradient-boosting): How gradient boosting lifted Bosch on an electronics retailer (+36% SoV, +121% SoC, +11.8% SoS, click position 11.4 → 9.6) without breaking organic relevance or forcing fixed ad slots. - [Personalization RFP Builder — Particular Audience](/resources/rfp/personalization): Build a defensible personalization RFP in minutes. 75+ pre-built requirements across algorithms, widgets, auction mechanics and reporting. Export to Excel or PDF. - [Search & Merchandising RFP Builder — Particular Audience](/resources/rfp/search): Specify your next search RFP against transformer foundations, vector recall, merchandising controls and agentic future-proofing. Export-ready Excel and PDF. - [Price Beat RFP Builder — Particular Audience](/resources/rfp/price-beat): Compare price-intelligence vendors on scraping resilience, matching accuracy, and member / delivery / coupon nuances. Interactive RFP builder with exports. - [Retail Media RFP Builder — Particular Audience](/resources/rfp/retail-media): 234 retail media capabilities mapped to contribution margin. The most exhaustive RFP builder for retail media networks. Excel and PDF export. - [Trending — Retail Media & AI Commerce News](/trending): What's moving in retail media, AI shopping and ecommerce right now, and what it means for retailers and brands. - [Community — People, Clients & Events](/community): The people, clients, events and conversations around Particular Audience and the wider ecommerce community. - [Press — Particular Audience In The News](/press): Announcements, funding news, awards and media coverage of Particular Audience. - [Solutions by Vertical & Outcome](/solutions): Retail media, search and personalization solutions mapped to your category and to the metrics you're accountable for — conversion, AOV, money velocity and stockout recovery. - [Compare Particular Audience vs Alternatives](/compare): Like-for-like comparisons of Particular Audience against Constructor, Moloco, Osmos and Pentaleap for retail media, onsite search and personalization. - [Company — About Particular Audience](/company): The team, story, community, press and open roles behind the retail intelligence layer powering search, personalization and retail media. - [Our People — Particular Audience](/company/people): Meet the Particular Audience team. Q&As and profiles from product, engineering, account management and go-to-market. - [Merchandiser Control — Rules, Boosts and Guardrails](/platform/merchandising): How merchandisers keep commercial control of AI ranking: objective-led boosts, pins, relevance floors, ad density caps, range gaps, stockouts and the weekly workflow. - [Integration Process — Feed, Events, Surfaces, Go-Live](/integration-particular-audience): How a Particular Audience integration runs: catalog feed and behavioral events in, ranked decisions out, four delivery models, checkout tracking verification and what your team owns at each phase. ## Press coverage (full articles hosted on-site) - [Q&A: PA CEO on the evolution of retail media, search and personalization — Retail Week](/press/retail-week-ceo-qanda): James Taylor argues today's retail media architecture won't survive the next five years without advanced search and recommendation systems underneath it. - [“The greatest optionality investment as a retailer” — ExchangeWire](/press/exchangewire-optionality-cannes): Filmed at Cannes: how AI is changing retail media, and whether the industry is entering the era of agent-to-agent commerce. - [Retailers have two years to take charge of retail media's AI shift — AdTech Juice](/press/adtech-juice-ai-shift): Coverage of our guide on why retailers, not intermediaries, should own the AI layer that decides what shoppers see. - [Retail & commerce media: actionable advice for CMOs — Forbes](/press/forbes-actionable-advice-for-cmos): David Doty's Cannes-timed piece features our founder and CEO James Taylor on how CMOs should navigate a channel heading for $300bn — and why legacy procurement and measurement habits hold brands back. - [My Road to Retail Media: James Taylor, Founder and CEO — Retail Media Age](/press/retail-media-age-my-road-to-retail-media): The route from an idea about product discovery to a full retail media and discovery platform, in our founder's own words. - [The Missing Piece: James Taylor, Particular Audience — Retail Media Age](/press/retail-media-age-the-missing-piece): Why retail media only works when the ranking, relevance and monetization layers are solved together rather than bolted on. - [Named in The Leading 100 list, celebrated at the Nasdaq tower — The Leading 100](/press/the-leading-100-nasdaq): Recognized for AI-driven hyper-personalization across ecommerce and retail media, with the announcement carried on the Nasdaq tower in Times Square. - [Guest comment: how to succeed in the era of agentic commerce — InternetRetailing](/press/internetretailing-agentic-commerce-guest-comment): Advice for retailers looking to boost retail media monetization as AI assistants start doing the browsing. - [Particular Audience launches PA DiscoveryOS on Shopify — AdTech Juice](/press/adtech-juice-discoveryos-shopify): Enterprise AI search, retail media and agentic commerce brought to millions of Shopify merchants. - [Particular Audience just smashed open the black box of AI search — MarTech Series](/press/martech-series-search-model-ab-testing): Retailers can now A/B test the AI models that decide relevance and margin, building on Adaptive Transformer Search. - [Modular retail media solutions to cut costs and accelerate innovation for RMNs — Retail Technology Review](/press/retail-technology-review-modular-retail-media): Retail media networks can adopt individual modules rather than replatforming onto a single monolithic ad stack. - [First-ever automated Ad Set Builder for retail media — Martech Record](/press/martech-record-automated-ad-set-builder): One-click campaign creation of AI-powered sponsored product formats across every billing type and placement. - [A vertically integrated retail media platform comes to Europe — Martech Record](/press/martech-record-vertically-integrated-platform-europe): The AI-native retail media offering joins our recommendation and site search platforms in Europe, after growth in Australia and New Zealand. - [Named in Forrester Research's 2025 NRF Innovators Report — Business Wire](/press/forrester-2025-nrf-innovators): Particular Audience listed among the retail-focused technology companies to watch.