How to prove the real return rate of reusable packaging

The return rate is the metric that decides everything in a reuse model. It determines how many cycles a package actually completes, hence how many times its manufacturing cost is amortized, hence whether the business model holds up. The problem is that this figure is almost always published today without any explanation of how it was measured. Here is what actually exists to measure and prove it.

Why this figure cannot be guessed

A return rate cannot be calculated in advance. It depends on the sector, the distribution channel, how easy returning is for the end customer, and the perceived value of the packaging. The gaps observed in the field are wide: a Deloitte barometer cites return rates of up to 99% in professional food service, driven by closed loops and deposit habits, while an in-store trial reports rates of 11.9 to 18.6% for integrated retail outlets and 8.4% for pharmacies. Between these two realities, there is no universal figure that can be carried over from one sector to another.

In e-commerce specifically, where the parcel is received at home and the customer has no contractual obligation to send the packaging back, measurement matters even more, because this is precisely where the system can lose the most units.

Measurement methods available today

Individual QR codes. This is the most widespread method in e-commerce packaging reuse. Each package carries a unique identifier that is scanned at key stages of the cycle: shipment, receipt, drop-off for return. RE-ZIP relies on this principle to track the return of each unit. Other systems on the market use the same mechanism: a QR code specific to each parcel, paired with an app that triggers tracking and organizes the return, for example through drop-off in a partner mailbox. The QR code is simple to deploy and has a low unit cost. Its limit is that it depends on a voluntary action by the customer at each stage: if the customer does not scan, the data does not exist.

RFID. RFID tags built into containers allow automatic reading, with no action from the customer, at every checkpoint equipped with a reader: warehouse, receiving dock, sorting center. This automation reduces dependence on end-user behavior, which makes it a relevant option for high-volume flows or for B2B loops where packaging circulates between equipped logistics sites. A market report mentions a fast-food case in which RFID tracking reportedly achieved inventory accuracy close to 99%. This figure comes from a market study, not a published independent audit, and should be read as an order of magnitude rather than a reference figure.

GS1 identifiers for reusable assets. GS1 has developed a dedicated standard, the GRAI (Global Returnable Asset Identifier), designed to uniquely identify reusable assets such as pallets, crates or drums. It can designate a type of packaging or each individual unit, which allows precise tracking and sorting. The GRAI is built from the GS1 company prefix, an asset number and a serial number, a framework already proven in logistics. Combined with a QR code or an RFID tag, it gives the identifier a standardized scope that is interoperable between partners, rather than a proprietary code that only its issuer understands. This is the thinking behind Le Pack't, launched by GS1 France: an alliance of nineteen initial players in commercial and industrial packaging reuse (eco-organizations and operators, including MOBIUSpack) set up to build this common traceability foundation together.

What published figures reveal, and their limits

The few return rate figures made public in the reuse sector should be read in context. RE-ZIP reports a return rate of 80%, corresponding to an average of 4.4 reuses per package, for a target life cycle of up to ten uses. This figure comes from a Danish industry source, not an independent third-party audit. Brasserie Météor, for its part, reports a consumer return rate of 97% for its reusable bottles, a result largely explained by a long-standing deposit tradition deeply rooted locally in Alsace, and therefore hard to transfer as is to an anonymous e-commerce parcel.

The lesson from these gaps: a return rate only makes sense when tied to its precise context (sector, channel, collection system) and to its measurement method. A figure published without these two elements cannot be verified, and should not be taken at face value, by a customer or by an extended producer responsibility (EPR) scheme.

Building credible proof

Whatever the technology, what makes a return rate credible is the rigor of the documentation behind the figure. The requirements set by Citeo (a French packaging eco-organization) for reuse declarations provide a good basis, even outside any direct regulatory obligation: collection method, collection date to the month, collection location identified by a name and ideally a SIRET number (French business registration number), identification of the consolidation point and of the collection service providers. The batch number and consignment note, optional in this framework, strengthen traceability when they are available.

Applying this level of documentation, even when not required to, turns a marketing figure into auditable data. It is the difference between saying “80% of our packaging comes back” and being able to show, unit by unit, where and when each return was recorded.

Pitfalls that undermine the figure's credibility

Three mistakes come up regularly. Reporting a return rate aggregated across very different channels (direct sales, marketplace, physical store) without separating them, which hides real differences. Publishing a theoretical return rate, based on the packaging's design, rather than one measured in the field. And failing to distinguish lost packaging from packaging that is simply on a long circulation cycle, which skews the rate calculation at any given moment.

A traceability system that identifies each unit individually, and relies on a standardized rather than proprietary identifier, solves all three problems at once.

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