Bridgestone Cockpit store — Japan
Five privately owned petrol cars — a Nissan Cube, a Mazda Demio, a Suzuki Jimny, a Toyota Estima and a VW Polo — were treated at a Bridgestone Cockpit store and recorded with a median improvement of +14.1%, ranging from +3.8% to +21.4%. No test method is recorded for any of them, and three of the five baselines are round whole numbers. This is the weakest dataset we publish, and we publish it labelled that way.
Five unrelated private cars, one workshop, no recorded method: a useful reminder that "five vehicles" and "five vehicles in a controlled trial" are not the same claim.
| Location | Bridgestone Cockpit store 1 (ブリジストン Cockpit 1号店), Japan |
|---|---|
| Vehicles | 5 privately owned petrol cars, five different models |
| Relationship | Customer vehicles of a tyre retail store — not an operator fleet |
| Method | Not recorded in the dataset |
| Measured quantity | Fuel efficiency, km per litre |
| Result | Median +14.1%, range +3.8% to +21.4% |
| Evidence class | Lowest — retail records without a documented method |
Every measurement, not just the best one
| Vehicle | Before | After | Change |
|---|---|---|---|
| Nissan Cube | 10.90 | 12.40 | +13.8% |
| Mazda Demio | 7.00 | 8.50 | +21.4% |
| Suzuki Jimny JB23W/2008 | 7.00 | 8.00 | +14.3% |
| Toyota Estima 2400cc/2001 | 5.04 | 5.23 | +3.8% |
| VW Polo | 8.00 | 9.13 | +14.1% |
| Median across all 5 measurements | +14.1% |
Method before result
We cannot tell you how these five cars were measured, because the dataset does not record it. The entries carry a before figure, an after figure and nothing else — no method label, no period, no distance.
Three of the five baselines are exactly 7.00, 7.00 and 8.00 km/L. Round whole numbers in a measured column usually mean an estimate, a manufacturer figure or a driver’s recollection rather than a reading, and where the baseline is estimated the percentage that follows from it is estimated too.
They are also five unrelated private cars from five manufacturers, driven by five different people for whatever purposes they happened to have. There is no shared route, duty cycle, load or driver behaviour to hold anything constant.
Every percentage on this page was recalculated by us from the recorded before-and-after figures rather than taken from the summary column of the source; all of them reproduce the recorded value. That is a check on transcription, not on the measurement itself — it confirms the arithmetic is right, not that the reading was.
The limits of this trial
We publish these next to the result rather than in a footnote. If a limitation would change how you read the number, you should read it at the same time as the number.
Known limitations
- No test method is recorded. Without knowing whether this was a year-on-year comparison, a before-and-after reading or a single tankful, the figures cannot be weighted against the other datasets on this site.
- Three of the five baselines are round whole numbers, which is a common signature of an estimated rather than measured starting value.
- Private cars driven by their owners are the least controlled setting available: no fixed routes, no logged loads, and a driver who knows a product has been applied to their own car.
- Five different models in five different duty patterns cannot be averaged into anything meaningful. The median is reported for completeness, not as a result.
- This is a dataset entry, not a trial report. What we hold is the before-and-after fuel-efficiency figure per vehicle as recorded in the master test dataset — not the operator’s raw fuel logs, not the odometer readings behind them, and not a written test protocol.
- There is no control group. No comparable untreated vehicle was tracked over the same period, so seasonal, route and traffic effects cannot be separated from the treatment.
- The measurement dates and the length of each measurement period are not recorded in these entries. We therefore cannot say how far each vehicle ran between the two readings, or which months the comparison covers.
- The figures were recorded by the operator or by the local distributor, not by an independent party, and we cannot re-derive them from primary records.
Reading this evidence in context
We publish this group for one reason: it is in the dataset, and leaving out the weakest entries while keeping the strongest is exactly the selection that makes fuel-saving claims untrustworthy.
It should carry no weight in a purchasing decision. If you are comparing suppliers, compare their controlled trials — the Sanden Kotsu control-group data and the blinded Waste Services trial are the datasets on this site worth arguing about.
It does have one honest use: it shows what our evidence looks like at the bottom of the range, so you can judge the rest of it against a known floor.
Questions operators ask about this trial
Why publish data you say is weak?
What would make this group usable?
Was this a Bridgestone trial?
Provenance
- Source
- Eco-Spray / NanoEFX master test dataset, compiled 22 March 2020 — operator-named section
- Recalculation
- All percentages recomputed from the recorded before-and-after figures
- Raw records
- Held by the operator or the local distributor — not in our possession
- Location entry
- ブリジストン Cockpit 1号店 — Bridgestone Cockpit store 1
- Method as recorded
- None — the method field is empty for all five entries
- Name release
- Operator naming approved by ECO EFX Solutions, 15 August 2026
- Last checked
- 15 August 2026
The only baseline that matters is yours
Every trial on this site was run on someone else’s vehicles, duty cycle and baseline. A NanoEFX pilot measures yours — and we will help you design it with a control group so the result stands up.