Inventory accuracy 65% → 98%. BOPIS-ready. Loss prevention with proof.
TRACIO delivers item-level RFID programmes from DC through to flagship stores. Passive RFID at every meaningful read point — receiving, stockroom, sales floor, fitting room, exit. The accuracy gain unlocks omnichannel.
Retail: the use case, and the numbers it moves.
The right radio for each job — chosen, never sold — mapped to your use case. That is what makes the ROI fast.
1 · Tag
Item-level Passive RFID travels from the DC to the shop floor.
2 · Count
Handheld and overhead reads keep stock accuracy live, not monthly.
3 · Convert
Accurate stock powers BOPIS, replenishment and fewer out-of-stocks.
Passive RFID → items · BLE → shopper & staff flow
What we keep seeing in Retail programmes.
Inventory accuracy in the mid-60s
Most retailers run inventory accuracy at 60–70% at any given moment. Every omnichannel fulfilment decision is made on numbers that aren't real.
BOPIS fails because of the gap
'Buy online, pick up in store' looks great on the brochure. The reality: the store doesn't have it, the customer cancels, churn goes up.
Loss prevention is reactive
EAS catches the obvious. Sweep theft, employee shrink, and supply-chain shrink are still mostly invisible.
The use cases that consistently pay back.
Item-level Passive RFID
Every garment, every SKU, every read point. From DC outbound to the in-store fitting-room sensor.
Stockroom workflow
Cycle counting with handheld and overhead RFID. Stock-outs in minutes, not at next monthly count.
BOPIS readiness
Real-time on-floor inventory feeds the omnichannel availability promise. Customers see what's actually there.
Smart fitting room
RFID-equipped fitting rooms suggest complementary items, alert staff to assist, log try-on data for merchandising.
Electronic Article Surveillance
Passive RFID-aware EAS portals that distinguish purchased vs unpurchased — fewer false alarms, more catches.
Supply-chain shrink
Tracing where inventory disappears between DC and shelf. The 'unexplained' becomes accountable.
Hardware & software ecosystem
Impinj · Zebra · Avery Dennison · Smartrac · Nedap · Sensormatic · Checkpoint
Where we plug in
Manhattan Active Omni · Salesforce Commerce · Oracle Retail · SAP Retail · Aptos · Cegid
Inventory accuracy went from 65% to 98% with item-level RFID, and that single number unlocked reliable click-and-collect across the network within nine months. It worked because TRACIO kept us vendor-neutral and rolled out store-cluster by cluster, so we proved the gain before scaling the spend.Omnichannel & Supply Chain Director · European luxury fashion brand · EMEAAnonymised at the client’s request. Reference available on request.
What we design and document to
GS1 EPC Gen2v2 · ISO/IEC 18000-63 · GS1 GTIN · EDI 856 · Passive RFID Alliance
Retail — where the payback shows up.
Source-to-shelf serialisation
Items tagged at source give end-to-end visibility from DC to fitting room, lifting inventory accuracy from ~65% to 98%+.
Self-checkout & loss prevention
Exit reads and POS reconciliation cut shrink and reduce friction at self-checkout, turning an untraceable loss number into a fixable one.
Endless aisle & omnichannel
Accurate, location-aware stock lets associates sell what is in the back or another store, enabling BOPIS and lifting conversion.
Relevant case studies
Common use cases — what we keep seeing.
Item-level inventory accuracy
Problem: Apparel and footwear inventory accuracy averages 65-75% with manual counts — driving stock-outs, false out-of-stocks, and customer loss.
Tech mix: Passive RFID inlay on every item, handheld cycle-counters, fixed readers at receiving and dispatch.
Outcome: Inventory accuracy from 65% to 98%+, sell-through rate up 5-15%, BOPIS reliability dramatically improved.
Ship-from-store fulfilment
Problem: Omnichannel retail uses stores as mini-DCs — but ship-from-store only works when stock accuracy is real-time.
Tech mix: Passive RFID item-level + smart-receiving, integration with order management and fulfillment platform.
Outcome: Ship-from-store cancellation rate reduced 50%+, customer fulfillment SLAs met, store labour utilisation improved.
Loss prevention and shrink reduction
Problem: Retail shrink runs 1.4-2.5% of revenue; theft, internal loss, and admin errors all contribute.
Tech mix: Passive RFID at receiving, on the floor, at point-of-sale, and at exit — discrepancies become visible.
Outcome: Shrink reduced 15-30%, internal-theft cases pursued with evidence, admin-error losses eliminated.
BOPIS (buy online, pick up in store) operations
Problem: BOPIS requires stock accuracy at every store, fast order assembly, and customer-pickup verification.
Tech mix: Passive RFID inventory + handhelds for order picking, customer-pickup verification via app and store-RFID confirmation.
Outcome: BOPIS fulfillment SLA met >95%, cancellation rate reduced, customer satisfaction up.
Visual merchandising compliance
Problem: Field merchandising compliance is hard to verify — store-team activities, product placement, and POS displays often diverge from plan.
Tech mix: BLE beacons on POS displays, store-employee app with location-aware checklists, photo-evidence of compliance.
Outcome: Merchandising compliance verified per store, brand-experience consistency improved, field-execution time reduced.
Smart fitting-room recommendations
Problem: Fitting rooms are conversion hotspots — knowing what a customer brought in enables recommendations and replenishment.
Tech mix: Passive RFID at fitting-room entry, fitting-room screen with recommendations, store-associate app for replenishment.
Outcome: Conversion rate up 5-15%, average-basket-size up 10-20%, customer-experience improved measurably.
Returns processing automation
Problem: Returns are a labour cost; verifying that the right item is returned and putting it back into available inventory is slow manually.
Tech mix: Passive RFID at returns counter, integration with order-management, automated putaway sorting.
Outcome: Returns processing time reduced 60-80%, return-fraud reduced, inventory-availability after return improved.
Smart shelves and out-of-stock alerts
Problem: Empty shelves cost retailers 3-5% of revenue; ID'ing missing SKUs requires staff to walk the floor.
Tech mix: Passive RFID smart-shelf readers (or weight + visual), real-time stockout alerts, integration with replenishment systems.
Outcome: Out-of-stock duration reduced 50%+, sales lost to stockouts reduced, replenishment efficiency improved.
Distribution-centre throughput
Problem: Retail DCs move millions of units per week; bottlenecks at receiving, picking, sortation and dispatch are the main throughput limits.
Tech mix: Passive RFID portals at receiving and dispatch, AMR for picking, fixed-reader sortation, WMS orchestration.
Outcome: DC throughput up 20-40%, labour cost per unit reduced 15-25%, peak-season capacity sustainable.
Personalised customer experience in-store
Problem: Customers expect digital-level personalisation in physical stores; without analytics on in-store behaviour, opportunities are missed.
Tech mix: BLE beacons + opt-in app for personalisation, AoA for fine-grained store analytics, integration with CRM and loyalty.
Outcome: Loyalty-customer dwell-time up, conversion rate up 5-10%, customer-lifetime-value measurably improved.
Related reading.
Frequently asked questions
How does RFID lift retail inventory accuracy?
Item-level RFID keeps stock records continuously accurate - typically from the ~65% of manual processes to 98%+ - which is the foundation for omnichannel and loss prevention.
Does it enable BOPIS and omnichannel?
Yes - accurate, real-time stock is what makes buy-online-pickup-in-store, ship-from-store and endless-aisle reliable rather than a source of cancellations.
How does it help loss prevention?
RFID gives provable, item-level visibility of what left the shelf and the store, turning shrink from an estimate into evidence you can act on.
How disruptive is rollout?
Tagging, often at source, and reader install are phased; a department or store can prove accuracy and uplift before chain-wide rollout.
How does it integrate with our systems?
Stock and event data feed your retail or inventory and e-commerce platforms via API so online and store reflect the same truth.