Supplymo

Supplymo research edition

Original research from the supply side

1688 Shelf Index · Issue 1Published 2 September 2026
All research

A fixed-panel view of the supplier score fields buyers see on 1688

Issue 1 follows the same 120 product-detail records once per day. Across 26 completed days, the composite median was 4.5/5, while the logistics and after-sales fields produced very different below-3.5 shares. That gap tells buyers to open the component fields. It does not support a supplier verdict.

This is a fixed, non-random panel selected from the first page of 12 deliberately chosen English searches; it is not representative of all 1688 listings.

Liam Cai

Liam Cai · Founder, Supplymo

Published 2 September 2026 · Collected 2026-08-31 · Yiwu, China

Evidence figure · Fixed-panel monthly reading

Logistics-score observations below 3.5 across Issue 1

1291

of 3119

Below 3.5

At or above 3.5
1828

n = 3119 score observations. 2026-08-06 to 2026-08-31. One daily read-only detail call for each item in the fixed 120-item panel; numeric score rows only.

Collected

2026-08-31

Evidence

Version 1 · 26 daily aggregate rows from one fixed 120-item panel

Sample status

Non-random · method and row unit stated

Reuse

CC BY 4.0 · 10 stated limits

Study reading

One headline score does not describe every service component

The composite-service field had a median of 4.5/5 across 3,119 numeric observations. In the same panel, 1,291 logistics observations fell below 3.5. These fields should not be collapsed into one supplier verdict without knowing how the platform defines and weights them.

For a live order, ask for the package facts, dispatch terms and written supplier answer that matter to that shipment. A marketplace score is context; it is not the evidence file for your goods.

Study reading

The panel stays fixed so movement cannot be manufactured by reselection

The 120 internal offer IDs were selected once on 6 August 2026. The same set was queried on every day in this issue. New high-scoring listings were not swapped in, and low-scoring records were not removed from the denominator.

The trade-off is deliberate: a fixed panel can show how one defined shelf changes, but it cannot describe the entire marketplace. Future issues must keep that distinction visible.

Study reading

Availability has a narrower meaning than a listing being gone

No observation in this issue was explicitly marked offer_not_returned. If that status appears in a later issue, it will mean only that the read-only detail call did not return the offer on that run.

Collection errors are a separate state and never count as unavailable. This prevents a network or API failure from becoming a false delisting claim.

Research boundary

What this study cannot tell you

  • BoundaryThis is a fixed, non-random panel selected from the first page of 12 deliberately chosen English searches; it is not representative of all 1688 listings.
  • BoundaryThe 120 panel items were not de-duplicated by seller. They are not 120 distinct suppliers, factories, companies or ownership groups.
  • BoundaryThe 3,120 private observations repeatedly measure the same 120 panel items across 26 days; they are not that many unique products.
  • BoundaryScores are numeric fields returned by the platform. They are not independently audited service performance, warehouse evidence or buyer outcomes.
  • BoundaryThe 3.5 threshold is a descriptive comparison point chosen before calculation. It is not a supplier approval rule.
  • BoundaryAn explicit offer_not_returned response is not proof of permanent delisting, stockout, business closure or unavailability to every buyer.
  • BoundaryCollection errors are kept separate from explicit non-returns and never counted as unavailable.
  • BoundaryA returned product-detail row can still omit one or more score fields; score denominators therefore travel with every figure.
  • BoundaryNo order, checkout, payment, supplier contact, message, shipment or after-sales case was observed.
  • BoundaryNothing here says 1688, a platform operator or any seller has done anything wrong.

Questions readers ask

Read the finding without over-reading it

What is the one-line result from Issue 1?

In a fixed, non-random Supplymo panel of 120 1688 product-detail records observed once daily from 2026-08-06 to 2026-08-31, the composite-service median across 3,119 returned score observations was 4.5/5; 1,291 of 3,119 logistics-score observations and 500 of 3,119 after-sales-score observations were below 3.5, while 0 of 3,120 daily observations were explicitly marked offer_not_returned by the collection contract. The score denominators and all stated limits are published with the data.

Is this a random sample of 120 1688 suppliers?

No. The panel contains 120 product-detail records selected from the first page of 12 deliberately chosen English searches. It was not de-duplicated by seller and cannot represent all of 1688.

Why publish daily aggregate rows instead of offer-level records?

The daily aggregates are enough to reproduce every public figure while keeping offer IDs, seller identity, shop names, prices and product details out of the downloadable dataset.

Does a score below 3.5 mean the supplier failed?

No. 3.5 is a descriptive threshold chosen for this issue. The fields are platform-returned display values, not Supplymo inspections, audited fulfilment outcomes or supplier approval decisions.

Does offer_not_returned mean a product was permanently delisted?

No. It means the product-detail call explicitly did not return that offer on that run. It cannot prove a permanent delisting, stockout, business closure or unavailability to every buyer.

How often will the Shelf Index update?

The plan is one issue per completed measurement window on this fixed URL. Each issue keeps its dates and evidence boundary; the panel is not silently reselected to improve the numbers.

Can this index replace a Product Check?

No. A panel trend cannot answer whether one product, supplier, MOQ, package, document set or shipping route is safe to approve. Product Check reviews the exact buyer decision before payment.

Issue archive

The measurement window stays attached to every issue

Issue 1

2026-08-06 to 2026-08-31 · 26 daily aggregate rows · 3,120 private item observations

Research accountability

Author and figure check

Author: Liam Cai. Collected 2026-08-31; published 2026-09-02.

Every published figure was deterministically recomputed from the sanitized daily rows and checked against the private source-window hash. No independent human reviewer is claimed.

Check the exact product

A panel score cannot approve the product you are about to buy

Send the exact product link, quantity, destination and supplier clue for a written pre-payment review.

Check a product before payment