Particular Audience Particular Audience
Talk to us

The retail decisioning layer

One system decides what each shopper sees. Most retailers run four or five separate tools.

Search in one tool, recommendations in another, pricing in a third, ads bolted on top — nobody owns the order products appear in, and the margin leaks between them. Particular Audience replaces that patchwork with a single decision: a Unified Decision Engine that scores relevance, inventory, margin and sponsored demand in one pass, on every surface, including the AI assistants now doing the shopping.

Bundles Case Studies — Basket Growth Evidence

Measured bundle outcomes across furniture, fashion, electronics, gifting and hobby retail, with controlled uplift, attribution and rollout metrics kept distinct.

The basket is the product.

How retailers turn product relationships into larger, more useful baskets—with AI-generated sets, governed offers and placements from product page to cart.

A bundle is not a carousel. It is a live decision about which products belong together, where the set should appear and whether an offer improves the basket without wasting margin.

How it works

  • Generate: Learn useful product relationships from catalog attributes and purchase behavior.
  • Govern: Pin hero combinations, exclude unsafe pairings and respect stock, range and margin rules.
  • Place: Carry the next-best set across product pages, add-to-cart, mini-cart and cart.
  • Measure: Separate controlled uplift, post-click comparison, attribution and rollout growth.

Specific bundle implementations

Named retailers, distinct basket mechanics and the measurement lens used for each result.

Measured results

  • Mixed-basket merchandising at PVH — PVH Group (Tommy Hilfiger). Controlled uplift: +403% Mixed-basket lift. +403% increase in mixed baskets (shoes + accessories).
  • Cross-selling higher-margin accessories at digiDirect — digiDirect. Compared with sitewide: +32.2% Units per transaction; +14.9% Average order value. +32.2% lift in units per transaction and +14.9% lift in average order value from more relevant related-product recommendations.
  • Discovery for a high-consideration bathroom retailer — The Blue Space. Compared with sitewide: +27.5% Post-click AOV vs sitewide; +17.6% Post-click units per transaction vs sitewide; 11.2% Click through rate; 21.2% Click conversion rate. Custom-filtered AI bundles delivered +27.5% post-click AOV and +17.6% units per transaction versus sitewide.
  • From automatic sets to governed promotional bundles — Large US furniture retailer. Rollout trend: 1.49% → 4.7% Bundle-attributed revenue over five months; +36% AOV vs sitewide in later PDP/cart read; +44.3% Units per transaction vs sitewide in later PDP/cart read; $1,432 Bundle value per user in later read. Two separately measured phases: bundle-attributed revenue grew from 1.49% to 4.7% over five months; a later PDP and cart read showed +36% AOV and +44.3% units per transaction versus sitewide.
  • Often Bought Together across a broad retail catalog — Target Australia. Controlled uplift: 384× ROI on incremental uplift; +17.4% Units per transaction; 15.3% Click through rate; 16.1% Click conversion rate. AI bundles delivered 384× ROI and a +17.4% increase in units per transaction in post-impression A/B measurement.
  • In-page and add-to-cart bundles for hobby ecosystems — Hornby. Attributed performance: 12.5% Site revenue attributed to bundles; +20.6% Post-click average order value; 17.5% In-page bundle conversion; 3.4% Add-to-cart pop-up conversion. Bundles accounted for 12.5% of site revenue, with 17.5% conversion on in-page bundles and +20.6% post-click AOV.
  • Search and recommendations at Whittard — Whittard of Chelsea. Rollout trend: 2.2% → 4.58% Bundle-attributed site revenue over five months; +108% Increase in attribution; 8.7% Click through rate; 19.9% Click conversion rate. Bundle-attributed site revenue rose from 2.2% to 4.58% over five months, with 8.7% CTR and 19.9% click conversion.
  • UX-led personalization at Hotel Chocolat — Hotel Chocolat. Controlled uplift: +57.5% Units per transaction; +12.1% Average order value; 6.1% Click through rate; 17.5% Click conversion rate. +57.5% lift in units per transaction and +12.1% lift in average order value from tested bundle placements.
  • Bundles and recommendations at Petbarn — Petbarn. Observed outcome: Lift Cross-sell revenue. Cross-sell modules drove repeat-visit revenue across pet categories.
  • Cross-product discovery for a UK electricals retailer — Hughes. Observed outcome: Lift Long-tail engagement. Recommendations and bundles deepened category browsing on long-tail SKUs.
  • Limited drops, fanatical fans, bigger baskets — DTC boho fashion label (anonymized). Controlled uplift: +5.7% Average order value uplift; +12.3% Units per transaction uplift; 16.7% Click through rate. Multi-modal recommendations merged similar-item discovery with cross-sell and style buys on a direct-to-consumer own-brand range.
  • Doubling the head of the range without buying more stock — Multi-brand fashion retailer (anonymized). Controlled uplift: +21.1% More SKUs in head of range; +14.7% Average order value; +11.9% Revenue per visitor. Computer vision solved the cold-start problem on new arrivals, spreading demand across the catalog instead of concentrating it in a handful of SKUs.

Explore Bundles · Measurement standard