ReturnRouteRequest a demo
Use cases

Built for the teams that process returns

Illustrative scenarios for retailers and fulfilment operators. The organisations described are composites, not customers.

Consumer electronics retailer

Stop restocking faulty units

Challenge. Units returned as ‘changed mind’ were restocked without testing; a share came back again as defective.

  • Reason classification flags ‘works but…’ language as likely defects
  • Power-on and battery checks are mandatory for battery products
  • Repair is permitted only when its cost stays under a set share of MSRP

Fewer repeat returns, and lithium-battery items never leave quarantine without a recorded safety check.

Fashion & footwear

Grade at speed, resell more

Challenge. High volumes of tried-on items, with grading left to each inspector’s judgement.

  • Photo-assisted grading suggests A/B/C grades for the inspector to confirm
  • Open-box (B) items go to secondary resale automatically under your rules
  • Size and fit analytics feed back to merchandising

Consistent grading across shifts and sites, with sizing problems reported by SKU.

Home & furniture

Know when repair beats liquidation

Challenge. Bulky items are expensive to move, so damaged returns were liquidated by default.

  • Value analysis includes handling and outbound logistics by weight
  • Repair-bench capacity is visible in the warehouse task queue
  • Carrier damage patterns are surfaced for claims

Recovery decisions backed by a full cost model, plus evidence to support carrier claims.

3PL / fulfilment provider

Run each client on their own rules

Challenge. Every retailer client had different disposition rules, kept in spreadsheets.

  • Rules are configured per client and versioned in an audit log
  • Approval thresholds can be set by client and by value
  • Client-facing recovery value reports

Each client’s rules are applied consistently, with reporting that can be passed straight to clients.

Marketplace operations

Find the fulfilment problem behind returns

Challenge. ‘Damaged in transit’ returns were rising, with no visibility by carrier or packaging type.

  • Damage analytics by carrier, site and SKU
  • Inspection images and notes attached to every damage record in S3
  • Bottleneck tracking for each workflow stage

A clear view of which lanes and packaging types drive damage.

Small appliances brand

Close the loop with product teams

Challenge. Defect signals were buried in free-text return notes.

  • Defect clustering by SKU and failure phrase
  • AI summaries of recurring issues for quality teams
  • Routing to return-to-repair or certified recycling

Recurring faults surface weeks earlier and reach the people who can fix them.

Discuss your use case