A distributor in one country reports that sales have dropped, while shops there are selling your products at prices below what you charge that distributor. The stock is genuine. It simply came from somewhere it should not have. Consumer scans of serialized packs can show where products actually end up, if the data is collected, linked and read with care.
What diversion is
Diversion, sometimes called grey-market or parallel trade, is when genuine products are sold outside the market, channel or terms they were intended for. Typical cases include:
- stock priced for one country resold in another;
- products intended for a professional or institutional channel appearing in consumer retail;
- promotional or donated stock sold commercially;
- one distributor selling into another distributor's territory.
Unlike counterfeiting, the product is real. That changes both the evidence and the response. For the counterfeit side of the same data, see how serialized QR codes support anti-counterfeit programmes.
The two ingredients
1. A serial on every unit
A consumer scan only tells you where one specific unit ended up if that unit has its own serial number. With product-level codes alone, every scan looks the same. Serialization is the starting point.
2. A link from serial to shipment
The scan location is meaningless unless you know where that unit was supposed to go. That knowledge comes from shipment records, and the practical way to get it is aggregation: recording which units were packed into which carton, and which cartons onto which pallet, often identified by an SSCC. When the pallet ships to a distributor, every unit on it inherits that destination.
Read what aggregation is in product traceability and how individual products become cartons and pallets for how this is captured on the line and in the warehouse.
Many companies record these steps as events. EPCIS is GS1's standard for sharing such event data between trading partners, with standard business steps such as packing, shipping and receiving. You do not need EPCIS to detect diversion, but you do need the shipment link in some form. What is EPCIS? explains the standard.
Turning scans into signals
Once each scan can be compared with an intended market, patterns emerge. Typical signals:
| Signal | What it might mean | Innocent explanations to rule out |
|---|---|---|
| Units shipped to Market A scanned in Market B | Cross-border diversion | Travellers, gifts, legitimate cross-border online sales, VPNs |
| A cluster of units from one distributor's shipments scanned in another's territory | Distributor selling outside its territory | Approved transfers between distributors |
| Institutional or professional stock scanned by consumers | Channel diversion | End users who legitimately bought through that channel |
| Units scanned before their shipment was due to arrive | Errors in shipment records, or stock taken early | Data entry mistakes, early deliveries |
| A shipment's units scanned in many unexpected places | Stock broken up and resold | Normal distribution in a region with wide reach |
The right-hand column is the important one. A single scan from an unexpected country is almost meaningless. A sustained pattern, many units from the same shipments appearing in the same unexpected place, is worth investigating.
Why scans are signals, not proof
- Location is approximate. Location inferred from a phone's network connection is a rough estimate and can be wrong. Precise device location is available only when the person grants permission.
- Scanners are not a random sample. People scan for rewards, information or reassurance, so scan rates differ by market, product and campaign.
- People and products move. Genuine buyers travel, move house and send gifts.
- Records can be wrong. A mis-scanned carton during aggregation sends a whole set of units to the wrong destination in your data.
A fair investigation workflow
Halden Skincare, a fictional brand, ships serialized moisturiser to distributors in two neighbouring countries at different prices. Its monitoring notices that units from three pallets shipped to the first country are being scanned steadily in the second.
- Detect. The pattern crosses a threshold Halden set in advance: a meaningful number of units from the same shipments, over several weeks, in one unexpected market.
- Enrich. The team looks up the pallets: which distributor received them, when, under which order.
- Check the data. They confirm the aggregation records for those pallets were complete and correct, and that no approved transfer explains the movement.
- Corroborate. A field visit or test purchase in the second country confirms the stock is on sale and reads the serials on the shelf.
- Act proportionately. Halden raises the findings with the distributor under the terms of their agreement, with legal advice where needed.
- Learn. The outcome, confirmed diversion or innocent explanation, is recorded and used to tune the thresholds.
This is the same discipline brand-protection teams use for counterfeit signals, described in the cornerstone guide to product verification vs authentication: data raises the question, people answer it.
Privacy and consent
Diversion monitoring relies on scan location, which can be personal data. Collect only what you need, prefer approximate location for routine monitoring, ask permission before requesting precise location, and explain in your privacy notice how scan data is used. Investigations should focus on products and trade partners, not on individual consumers.
See how aggregation and scan data support track and trace