Plain answers, how-to steps and definitions for retail and ecommerce teams, each linked to the Particular Audience products and case studies behind it.

Use cases by retail vertical

• Retail media for grocery retailers: How grocery retailers run sponsored products and supplier-funded offers inside search and listings without hurting basket building.
• Site search for fashion ecommerce: Why fashion search needs vector understanding and visual similarity, and how to turn sold-out and no-result pages into the next click.
• Product recommendations for health and beauty retailers: How beauty and pharmacy retailers personalise recommendations around routines, replenishment and complementary products.
• Product bundles for furniture and homeware retailers: How furniture and homeware retailers use AI-selected bundles to raise basket value across rooms and collections.
• Retail media for sporting goods retailers: How sporting goods retailers launch onsite retail media with brand partners and prove brand growth beyond the clicked product.
• Improve retail media relevance without replacing your ad server: Assess a retail media relevance layer around your current ad server. Define data inputs, decision ownership, fallback behaviour and a measurable pilot.
• Sell sponsored products on your own Shopify store: Plan supplier-funded sponsored products on your Shopify store. Assess eligible inventory, placements, campaign operations, disclosure and reporting.

Buyer questions

• What is a retail media network?: A retail media network lets brands advertise on a retailer's own site and channels using the retailer's shopper data. How it works and what it needs.
• What is the difference between onsite and offsite retail media?: Onsite retail media runs on the retailer's own site; offsite uses retailer data to reach shoppers elsewhere. How each works and when to use it.
• How do sponsored products work on a retailer's site?: Sponsored products are brand-funded listings in search and category results. How bidding, relevance ranking and measurement work.
• Vector search vs keyword search: what's the difference for ecommerce?: Keyword search matches words; vector search matches meaning. Why that matters for long, descriptive and conversational shopper queries.
• How should a retailer choose a retail media platform?: The questions to ask when choosing a retail media platform: relevance, formats, brand buying tools, measurement, billing and ownership.
• How many sponsored products should search results show?: Find the right sponsored-product density with a controlled test. Measure media income, commerce contribution, relevance and displacement on the same scorecard.
• Similar products vs frequently bought together: which belongs where?: Choose recommendation logic for comparison, accessories, baskets and repeat purchase. See where similar products and frequently bought together each belong.
• One app for Shopify search, recommendations and bundles: what can you consolidate?: Review your Shopify app stack by task, not app count. Compare search, recommendations and bundles while preserving specialist checkout and cart needs.

How-to guides

• How to reduce zero-result searches on your ecommerce site: Five steps to find, fix and prevent zero-result and near-zero-result searches, from query logs to meaning-based search.
• How to launch a retail media network: Steps to launch onsite retail media: size the opportunity, choose formats, set relevance rules, onboard brands and prove results.
• How to measure retail media incrementality: Use holdout groups to separate sales caused by retail media from sales that would have happened anyway, and report brand halo.
• How to monetise your ecommerce site search: Turn search results into retail media inventory with sponsored search ranked on relevance, plus search retargeting across the site.
• How to evaluate your ecommerce site search: Test site search relevance with a fixed query set, graded results and head-to-head comparisons, including LLM-as-a-judge grading.
• Increase sponsored-search fill rate on long-tail queries: Diagnose sponsored-search coverage by query, traffic and failure reason. Separate relevance gaps, advertiser demand, budgets and delivery before increasing fill.
• Audit ecommerce search merchandising rules: Find conflicting search boosts, outdated pins and global rules. Use a practical audit to protect shopper intent while keeping merchandising decisions measurable.
• Build or buy ecommerce search? A three-year cost model: Compare the full cost of building or buying ecommerce search: engineering, infrastructure, data, merchandising, measurement and migration over three years.
• Ecommerce search migration checklist: test, switch and roll back: Plan an ecommerce search migration with catalogue and event parity, query evaluation, a controlled release and explicit rollback criteria for your team.
• Store-specific grocery search: stock, assortment and availability: Design grocery search around store assortment, local offers and stock freshness. Explore a worked data model, changed-store behaviour and availability checks.
• How to measure supplier-funded promotion incrementality: Separate the effect of an offer from paid visibility. Plan holdouts, calculate incremental orders and reconcile supplier funding, fees and contribution.
• Why retail media campaigns underspend: a diagnostic checklist: Find why retail media campaigns underspend. Check status, eligible products, budgets, bids, pacing and delivery before changing campaign settings.
• Retail media billing and reconciliation checklist: Reconcile retail media bookings, delivery, billable amounts, invoices and cash. Use a worked example with clear owners for credits, makegoods and disputes.
• Sponsored recommendations on product pages: similar, complementary and bundle placements: Design sponsored product-page recommendations for alternatives, accessories and complements. Define eligibility, compatibility, billing and measurement.
• Store-level availability in retail media: avoid advertising unavailable products: Design sponsored-product eligibility around store, fulfilment and stock freshness. Define stale-data behaviour, campaign permissions and delivery checks.
• Exact SKU and part-number search alongside semantic search: Test exact SKUs, model numbers and descriptive product queries together. Use a labelled fixture to expose identifier collisions, false matches and weak retrieval.
• Product recommendations for new products with no sales history: Handle recommendation cold start for new products, shoppers and sites. Compare catalogue evidence, images, contextual signals and carefully measured fallbacks.
• Dietary and attribute search in grocery: enforcing shopper constraints: Design grocery search with verified dietary attributes, explicit exclusions and careful missing-data handling. Separate semantic relevance from eligibility.
• Compatible accessory recommendations for electronics retailers: Build accessory recommendations around verified product compatibility, clear evidence and useful basket context. Explore a data model and practical test fixtures.
• How to make Shopify metafields searchable: Map Shopify product and variant metafields, sync the right data and test search and facets with examples for materials, specifications and compatibility.
• Price matching vs dynamic pricing vs price affirmation: Compare public repricing, policy-approved price matching and evidence-based price affirmation. Choose the right action with a practical retail decision matrix.
• Sync retail media campaigns with live promotions: Design a promotion-feed contract for retail media with product scope, effective dates, funding controls, expiry behaviour and reconciliation keys.
• Programmatic ecommerce landing pages without duplicate or empty pages: Build useful ecommerce collection pages with clear demand, valid assortments, unique guidance, controlled facets, canonical rules and retirement decisions.
• How to A/B test ecommerce search and recommendations: Design credible tests for search and recommendations: randomisation, sample size, exposure, uncertainty and commercial guardrails, with clear decision rules.

Glossary

• ROAS (return on ad spend): ROAS is attributed revenue divided by ad spend. What it shows, what it misses and how it relates to incrementality.
• Incrementality: Incrementality is the extra sales caused by advertising, measured against a group that did not see it.
• Brand halo: Brand halo is the sales uplift across a brand's wider range caused by advertising one of its products.
• Holdout test: A holdout test withholds a campaign from a random group of shoppers to measure the campaign's true effect.
• Product bundles: Product bundles group complementary items so shoppers can buy them together, often on the product page.

Templates and checklists

• Retail media rate-card template: CPC, CPM, CPA and tenancy: Build a retailer rate card with placement units, pricing, availability, fees and makegoods. Compare CPC, CPM, CPA and tenancy using clear worked examples.
• Price-match automation policy template for retailers: Define eligible competitors, comparable prices, margin floors and escalation rules with a worked price-match policy template for retail teams and developers.
• Product-data requirements for AI ecommerce search: Prepare product data for AI search with a field checklist covering identity, variants, attributes, prices, stock, update behaviour and measurement joins.
• MCP product search for retailers: an implementation checklist: Scope retail MCP product search with identity, permissions, live-price boundaries, inventory freshness, tool contracts, failure handling and test cases.

Comparisons and decisions

• Retail media: build, buy or add an intelligence layer?: Compare building, buying and augmenting your retail media stack. Use a three-year cost model covering integration, operations, fees and decision ownership.
• An Algolia alternative for retailers evaluating search and retail media: Compare Particular Audience and Algolia on your catalogue, search needs, operating model and retail-media scope with a fair, documented evaluation plan.