Enterprise product discovery for large multi-brand and multi-category retailers
Large retail catalogues create a discovery problem that navigation alone cannot solve. Shoppers arrive with an intent - a silhouette, occasion, colour, price point, product type or complete look - while the assortment is organised across brands, categories, variants and markets. RecoMelon connects that intent to relevant products across the eligible catalogue, helping retailers expose more of the range without manually merchandising every relationship.
Search that understands what shoppers mean. Conversational and contextual search interprets style, colour, attributes and intent. Dynamic merchandising balances commercial and catalogue priorities, while inline Shop Similar and integrated LiveGrid™ UGC keep shoppers discovering without returning to a static results grid.
Shop Similar, directly from the product image. When a product is "almost right", Reveal™ offers visually aligned alternatives from within the primary product image, above the fold. Shoppers stay on the PDP and keep their intent while finding an alternative without the attribute stopping the purchase.
Turn “almost right” into another relevant option. Shop Similar keeps high-intent shoppers exploring with visually matched alternatives based on the product they are already considering - helping them refine their choice without starting their search again.
Turn one product into a complete look. Complementary recommendations create multiple looks around a chosen product, with configurable discounts and multi-buy offers to increase AOV. Bundle Rescue swaps unavailable or unsuitable items for visually similar alternatives without breaking the set. Integrated LiveGrid™ content helps shoppers visualise the combination.
Abandoned Cart Email Rescue. Sending shoppers back to rejected products repeats the problem. SecondLook™ restores the abandoned basket and offers visually matched alternatives for each item - helping shoppers find a better fit while preserving basket intent and cross-sell opportunities.
The discovery problem
A shopper looking for a black evening dress, a school-ready outfit, a minimalist trainer or a complete holiday look does not necessarily care how the catalogue is divided internally. The relevant products may sit across different brands, collections, departments and merchandising structures.
At scale, those internal boundaries can become discovery boundaries. Shoppers repeatedly encounter the products that are easiest to search, already popular or manually promoted while relevant new and long-tail inventory remains harder to reach.
RecoMelon creates a product-intelligence layer across the eligible assortment so the next product can follow the shopper’s intent rather than simply the catalogue hierarchy.
Across the assortment
A large retailer should not have to manually define every useful relationship between products. RecoMelon uses product imagery, catalogue context and the shopper’s current journey to connect relevant choices across the eligible assortment.
VisualDNA™ establishes visual relationships, IntentWeave™ adds usable product intelligence, and RecoMelon surfaces those relationships through search, collections, PDP alternatives and complementary looks. Merchandising teams retain control over the brands, categories, markets and products allowed to participate.
When a product is almost right, preserve the characteristics creating desire while changing the likely dealbreaker - such as colour, silhouette, detail, price point or product type.
Expose relevant alternatives without requiring identical product naming or a manually maintained cross-brand relationship map.
Bring new arrivals and lower-history products into relevant journeys before popularity data has had time to accumulate.
Use complementary product relationships to connect apparel, footwear, accessories and other eligible categories around the item already creating intent.
Use authoritative catalogue data for price, variants, stock and market eligibility while merchandising controls determine what can be promoted, excluded or prioritised.
Category-specific discovery
A multi-category retailer should not force dresses, trainers, beauty, childrenswear and accessories through the same recommendation logic. The product relationships that matter change with the category and the shopping mission.
Continue silhouette, colour, occasion and style intent across eligible brands, then move naturally from alternatives into a complete look.
Balance visual similarity with authoritative size, variant and availability data so an attractive alternative is also a purchasable one.
Keep age, size, category and availability constraints authoritative while using visual and catalogue relationships to widen relevant choice across large seasonal ranges.
Use visible shade, format and presentation to support discovery while merchant-supplied product data and compliance rules remain authoritative for suitability and claims.
Define inclusion, exclusion and commercial priorities by brand, category, market, campaign or assortment so automation expands discovery without flattening the retailer’s buying strategy.
The result is shared intelligence without a one-size-fits-all shopper experience.
Inventory-aware outfitting and cross-sell
For a multi-brand retailer, complementary discovery is not simply another recommendation carousel. It is the opportunity to turn the product creating intent into a coordinated basket across categories and brands.
Keep the product the shopper is considering fixed, then introduce distinct companions from eligible product roles - for example footwear, accessories, outerwear or jewellery - rather than returning more versions of the same item.
Use current product and variant data to keep recommendations aligned with market, price and stock. If a companion becomes unavailable, Bundle Rescue can offer another eligible visual alternative rather than allowing the look to become a dead end.
Control eligible products, category roles, look groupings and offer presentation so complementary discovery supports the retailer’s assortment strategy rather than overriding it.
Intent-led personalisation
Large retailers already have behavioural data. The problem is that historical behaviour naturally favours products and brands that have already received exposure.
RecoMelon adds another signal: the product, query and visual direction the shopper is expressing in the current session. That makes it possible to refine discovery around live intent while keeping the retailer’s commercial rules authoritative.
Carry the shopper’s query, selected product, colour, category, occasion or refinement into the next search result, alternative or complete-look recommendation.
Let shoppers compare alternatives, change variants and swap complementary products rather than forcing them through a fixed recommendation path.
Apply brand, category, stock, market and campaign rules to determine what is eligible for each discovery experience.
Configure labels, layouts, controls and calls to action so the intelligence can sit naturally inside the retailer’s existing design system.
Behaviour tells you what has worked before. Live intent helps you respond to what this shopper is trying to do now.
Enterprise measurement
For a large retailer, more recommendation clicks are not enough. The useful question is whether discovery exposes relevant products from more of the eligible assortment and turns that additional choice into commercial progression.
Measure how much of the eligible assortment enters meaningful shopper journeys, including new arrivals and lower-exposure products.
Track whether shoppers move into relevant products, brands and departments they were unlikely to encounter through the original path.
Compare progression to purchase, conversion and basket value against an agreed baseline or control.
Include the operational cost of maintaining rules, reviewing matches and managing exceptions. Better discovery should not require an ever-growing manual relationship map.
Use consistent attribution, account for promotions and stock changes, and expand only where the commercial and operational evidence supports it.
Compare the platforms when search, recommendations and merchandising need to work across a large or visually complex catalogue.
Bloomreach presents a broad discovery platform. RecoMelon concentrates on making product imagery and catalogue context operational inside Shopify journeys.
RecoMelon builds visual relationships between products and uses them across The Index™ search, Smart Collections, Reveal™ PDP discovery and Bundles™. This can be particularly useful where style, colour, silhouette, pattern or finish affect relevance.
No. Scope which platform owns each surface and run a controlled test. RecoMelon can begin with PDP alternatives, a selected collection or complementary-product discovery while the current search stack remains live. No native Bloomreach connector is assumed.
Review catalogue preparation, integration ownership, merchandising workload, time to value, regional requirements, explainability, reporting and the commercial result on a representative category.
Yes. RecoMelon can sit across a large retail assortment while respecting the commercial boundaries already used to operate it. Product imagery and catalogue context establish relationships independently of inconsistent brand naming or sparse behavioural history, while retailer rules determine which products, brands, categories, variants and markets are eligible for each discovery surface.
No. Start where the current experience leaves intent unresolved - cross-brand alternatives, new-product exposure, PDP continuation, collection discovery or complete-look recommendations. Existing search and navigation can remain in place while RecoMelon is evaluated on a defined category, market or surface.
Yes. Inclusion, exclusion and merchandising controls can define where cross-brand discovery is useful and where brand, category, campaign or commercial boundaries should remain intact. Catalogue data remains authoritative for price, variants, stock and market availability.
RecoMelon can establish product relationships from imagery and catalogue context before extensive click or purchase history exists. This gives new collections and lower-exposure products a route into relevant discovery without requiring them to become popular first.
Choose a high-choice category where shoppers regularly compare across brands or where a large proportion of the eligible assortment receives little exposure. Establish the baseline for catalogue reach, product exploration, conversion and order value, then expand only where the data supports it.
Bring your catalogue scale, category structure, markets and current search or merchandising stack. We’ll identify where shoppers are losing access to relevant products, what should remain in place and the lowest-risk surface to test first.
Review our catalogue
