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Card class: HeroCategory: Marketplace

At a glance

Rejected / Off-Shelf Listings counts every JD.com listing that the platform has rejected at review or pulled off-shelf (xia jia) so it can no longer be bought. On JD’s POP marketplace, listings come off-shelf for concrete, fixable reasons: a missing or expired brand authorisation in a controlled category, mandatory category attributes left blank, product images that fail JD’s image specification, or a compliance flag (3C certification, food/health licence, restricted keywords). Every off-shelf listing is lost shelf space and lost revenue until it is fixed and resubmitted, so this is a real-time firefighting card, not a trend card.
What it countsThe number of JD listings currently in a rejected or off-shelf state, across both JD Logistics (warehoused) and POP self-fulfilled listings. A listing in draft or pending first review is not counted; only listings JD has actively rejected or removed from sale are.
Sample typeBackend API data from JD.com listing status, refreshed on the standard data refresh.
Why it mattersAn off-shelf listing earns nothing and, if it sat live before removal, may signal a compliance or brand-authorisation gap that puts sibling listings at risk too. Repeated rejections in a controlled category usually point to one missing authorisation document rather than many separate faults.
Reading the valueAny value above zero is actionable. Read alongside the rejection reason in JD Seller Centre to batch fixes - one expired authorisation can off-shelf a whole brand’s catalogue at once.
Currencycount
Time windowRT
Alert trigger>0
Sentiment keyjd_rejected_listings
Rolesowner, operations

Calculation

Calculated automatically from your JD.com data. The card sums all listings whose JD status is rejected (review failed) or off-shelf (removed from sale by JD or auto-removed for a compliance/attribute breach). Listings you have voluntarily set inactive are excluded; this card isolates involuntary removals. See the worked example below for a typical reading.

Worked example

A representative reading of Rejected / Off-Shelf Listings for a mid-size POP seller on JD.com. The card shows 14 listings off-shelf as of 23 Jun 26, up from 3 the day before. Drilling in, 11 of the 14 share a single rejection reason: the brand authorisation letter (pin pai shou quan) for one cosmetics brand expired on 21 Jun 26, and JD auto-removed every SKU under that brand. The remaining 3 are image-spec failures (white-background main image missing). The fix is not 14 separate jobs - it is one renewed authorisation upload that restores 11 listings, plus 3 quick image swaps. Use Vortex Mind to group the off-shelf set by rejection reason and brand, and ask Ask Viq “which off-shelf listings share the same cause?” to triage before touching JD Seller Centre.

Sibling cards merchants should reference together

CardWhy merchants reach for it
jd_off_shelved_24hThe fresh removals in the last 24h - the leading edge of this count.
jdc_brand_auth_coverageMissing brand authorisation is the top off-shelf cause in controlled categories.
jdc_brand_auth_expiringPre-empts the renewals that prevent the next mass off-shelf event.
jdc_attr_completenessBlank mandatory attributes are a frequent rejection reason at review.
jdc_listing_qualityLow quality scores correlate with image and content rejections.
jdc_revenue_at_riskQuantifies the revenue exposed by the current off-shelf set.

Reconciling against the vendor’s own dashboard

Where to look in JD.com’s own dashboard: In JD Seller Centre (Shang Jia Hou Tai), open Product Management and filter by status “off-shelf” (xia jia) and “rejected” (shen he wei tong guo). The rejection reason and the offending field are shown per listing. Confirm you are viewing the same shop ID and that no category filter is narrowing the list before comparing to the Vortex IQ count. Why the Vortex IQ value may legitimately differ:
ReasonDirectionWhat to do
State definition. Vortex IQ counts both rejected-at-review and off-shelf-after-live; a JD view filtered to only one state shows fewer.Vortex IQ higherCombine both JD status filters.
Refresh lag. A just-fixed listing JD has re-approved may still show on the card until the next refresh.Vortex IQ higherForce a manual refresh after bulk fixes.
Voluntary vs involuntary. Listings you set inactive yourself are excluded here but may appear under “off-shelf” in JD’s combined view.Vortex IQ lowerMatch the involuntary-only filter.
Cross-connector reconciliation: pair with brand-authorisation and attribute-completeness cards to confirm the root cause before resubmitting. For divergence investigations, use Vortex Mind.

Known limitations / merchant FAQs

Q: How often does Rejected / Off-Shelf Listings update? This is a real-time (RT) card and refreshes on the standard data refresh (typically every 30-60 minutes). After a bulk fix in JD Seller Centre, force a manual refresh to clear restored listings immediately. Q: Why does my JD.com dashboard show a different number? The usual cause is the JD status filter: this card combines rejected-at-review and off-shelf-after-live, whereas a single JD filter shows only one. Refresh lag after a fix and exclusion of voluntarily inactive listings also account for small gaps. Q: A whole brand went off-shelf at once. Is that one problem or many? Almost always one. JD removes every SKU under a brand when its authorisation expires or is revoked. Group the off-shelf set by brand and rejection reason first; one renewed document often restores dozens of listings. Q: Can I customise the alert threshold? Yes. The default fires above zero because any involuntary removal is revenue lost, but the threshold is configurable per profile in the Sensitivity tab if you want to suppress single-listing noise.

Tracked live in Vortex IQ Nerve Centre

Rejected / Off-Shelf Listings is one of hundreds of KPI pulses Vortex IQ tracks across JD.com and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.