> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Catalogue Drift vs Amazon, Shopline > SKUs that diverge between Shopline and Amazon. Brand-trust killer + de-listing risk under MAP policies. How to read it, why it matters, and how to act on it. **Metrics type:** [Cross-Platform Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Ecommerce Platform](/nerve-centre/connectors#connectors-by-type) > SKUs that diverge between Shopline and Amazon. Brand-trust killer + de-listing risk under MAP policies. ## At a glance > Count of SKUs listed on both Shopline and Amazon where price differs by >20% OR title differs (Levenshtein >5) OR primary image hash differs. The brand-consistency canary, divergence here triggers MAP-policy violations and Amazon Buy Box suspensions. Unlike OnBuy's price-only drift, this card also catches title and image divergence common in APAC fashion catalogues. | | | | --------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `COUNT(SKUs WHERE listed on both AND (ABS(price_a - price_b) / price_a > 0.20 OR title_levenshtein(a, b) > 5 OR image_hash(a) != image_hash(b)))`. Three drift dimensions; any one triggers the count. | | **Source data** | Shopline `GET /v1/products` (variant price, title, primary image URL) joined to Amazon SP-API `GET /listings/items` for the merchant's region. | | **Match key precedence** | (1) GTIN / EAN / UPC / JAN where available, (2) seller-SKU, (3) manual ASIN cross-reference. | | **Drift dimensions** | (a) Price gap >20%, (b) title Levenshtein distance >5 (catches paraphrased titles, missing keywords, language mismatch in HK/TW catalogues that run Trad-Chinese on Shopline and English on Amazon), (c) primary image perceptual-hash mismatch (catches different product photography between channels). | | **Currency** | Both sides converted to common reporting currency for the price-gap check. FX from daily-close rates. | | **Refunds / cancellations** | Not relevant; this is a catalogue-state card, not order-driven. | | **Time window** | `RT` (re-evaluated every 6 hours; webhook-driven on inventory and price updates). | | **Alert trigger** | `>5 SKUs drifted (>20% price OR title mismatch)`. | | **Sentiment** | None directly; the count is the signal. | | **Roles** | owner, marketing, operations. | | **Only when** | `has_amazon_sibling = true`. | ## Calculation Calculated automatically from your Shopline data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading. ## Worked example **An APAC fashion brand running Hong Kong Shopline + Amazon JP, snapshot taken 27 Apr 26.** The brand has 142 SKUs listed on both. The drift comparison flags 11: | SKU | Drift type | Detail | | --------------------------- | ------------- | ------------------------------------------------------------------------------------------------------------------- | | FB-201 (linen blouse, oat) | Price | Shopline HK$ 380, Amazon JP equiv HK$ 510 (+34%) | | FB-203 (linen blouse, sage) | Price | Shopline HK$ 380, Amazon JP equiv HK$ 495 (+30%) | | FB-104 (cotton tunic) | Title | Shopline 棉質長衫, Amazon JP "Cotton Long Tunic - Off White, Linen-blend" (Levenshtein > 30) | | FB-105 (cotton dress) | Title | Same SKU, totally different language and keyword set | | FB-118 (denim jacket) | Image | Shopline shows lifestyle shot (model wearing); Amazon shows flat-lay product shot | | FB-205 (silk scarf) | Price | Shopline HK$ 240, Amazon JP equiv HK$ 195 (-19%, just under threshold... actually -25% with FX adjustment, drifted) | | FB-308 (leather belt) | Price + Image | Both dimensions | | (... 4 more rows ...) | | | ```text theme={null} SKUs listed on both 142 Drifted (any dimension) 11 Of which price drift 7 Of which title drift 2 (mostly language mismatch) Of which image drift 2 ``` **What it means.** 11 drifted SKUs is above the alert threshold (>5). The pattern reveals two distinct issues: 1. **Price drift** (7 SKUs). Most are Amazon JP higher than HK Shopline by 20 to 35%, justifiable as the JP market tolerates higher fashion prices and FX volatility absorbs some difference, but the gap is too wide to ignore. Risk: cross-border resellers buying from HK Shopline and reselling on Amazon JP at lower prices than the merchant's own listing, which Amazon will eventually flag. 2. **Title and image drift** (4 SKUs). Language mismatch is the easy fix (translate Shopline titles to consistent JP keywords); image mismatch needs a brand-consistency review (do we want lifestyle on Shopline and flat-lay on Amazon, or harmonise?). **The action.** (1) Reprice the 7 drifted SKUs by either lifting Shopline or lowering Amazon to bring gaps inside 20%. (2) Translate the 4 title-mismatched SKUs to consistent JP keywords. (3) Schedule a brand-consistency review for image strategy across channels. The drift count should drop from 11 to under 5 within 14 days. ## Sibling cards merchants should reference together | Card | Why it matters next to drift count | What the combination tells you | | -------------------------------------------------------------------------------------------------- | ------------------------------------- | ---------------------------------------------------------------------------------------------------- | | [Marketplace Revenue Share (Amazon)](/nerve-centre/kpi-cards/shopline/marketplace-revenue-share) | Channel weight. | Higher Amazon share + higher drift = bigger MAP-risk surface area. | | [Active Ads on OOS SKUs](/nerve-centre/kpi-cards/shopline/active-ads-on-out-of-stock-skus) | Ad-OOS twin. | Both cards detect cross-platform inefficiency; one on price/title, the other on stock vs ads. | | [Top Products by Revenue](/nerve-centre/kpi-cards/shopline/top-products-by-revenue) | Drift on hero SKUs is most expensive. | If drifted SKUs include top-10 by revenue, the dollar impact of fixing is highest. | | [Missing Descriptions](/nerve-centre/kpi-cards/shopline/products-missing-description) | Catalogue-quality cousin. | A merchant with poor catalogue hygiene on Shopline tends to have title drift vs Amazon too. | | [Refund Rate](/nerve-centre/kpi-cards/shopline/refund-rate) | Image-drift downstream. | Image mismatch correlates with "looks different from photo" refunds; cross-reference. | | [Catalogue Drift vs Amazon UK (OnBuy)](/nerve-centre/kpi-cards/onbuy/catalogue-drift-vs-amazon-uk) | Cross-platform pattern. | Same archetype, different upstream. | | [SKU Coverage](/nerve-centre/kpi-cards/shopline/sku-coverage) | Match-key health. | If SKU coverage is low, match-precision is weaker, and drift count may be inflated by false matches. | | [Shopline Health Score](/nerve-centre/kpi-cards/shopline/shopline-health-score) | Composite. | Drift drags the health score because it represents structural risk, not transient operational noise. | ## Reconciling against the vendor's own dashboard **Where to look:** Neither Shopline nor Amazon offer a built-in cross-platform comparison; this is a Vortex IQ-only view. The closest manual workflow is: > **Shopline Admin -> Products -> Export** (CSV with prices, titles, image URLs) > **Amazon Seller Central -> Inventory -> All Inventory** (export with prices, titles) > **Compare in Excel using EAN/JAN as the join key.** Image drift is effectively impossible to spot manually at scale; the perceptual-hash check is the unique value of this card. **Why our number may legitimately differ from a manual comparison:** | Reason | Direction | Why | | ----------------------------- | ------------------ | ------------------------------------------------------------------------------------------------------------------ | | **Title comparison** | Ours stricter | We use Levenshtein distance >5, which catches paraphrasing; manual comparisons usually only flag exact mismatches. | | **Image hash** | Ours surfaces this | Vendor consoles do not expose image hashes; this dimension is impossible to manually replicate. | | **FX rate for price gap** | Either | We use daily-close FX; manual price comparisons may use month-end or "mental math" rates that differ. | | **Stability filter** | Ours lower | We require drift to hold for 7 consecutive days; flash-promo drift is excluded. | | **Variant rollup** | Marginal | Apparel parent-child variant trees do not always 1:1 between Shopline and Amazon. | | **Restricted brand listings** | Ours lower | Listings the merchant cannot freely reprice (brand-registry restricted) are excluded since action is impossible. | **Internal identity:** `shopline_xc_catalogue_drift = COUNT(SKUs WHERE listed on both AND ANY drift dimension exceeds threshold AND drift_days_consecutive >= 7)` The drill-down view shows per-SKU dimension breakdowns for action prioritisation. ***
Documentation cross-reference (for agencies running multiple platforms) * [`shopify.shopify_xc_catalogue_drift`](/nerve-centre/kpi-cards/shopify/catalogue-drift-vs-amazon) * [`bigcommerce.bigcommerce_xc_catalogue_drift`](/nerve-centre/bigcommerce/bigcommerce_xc_catalogue_drift) * [`onbuy.onbuy_xc_catalogue_drift`](/nerve-centre/kpi-cards/onbuy/catalogue-drift-vs-amazon-uk)
## Known limitations / merchant FAQs **Why is the price threshold 20% here but 15% on the OnBuy version?** Because Amazon JP / US fee structures and FX volatility absorb a wider naturally-occurring gap than UK marketplaces. 20% is the rule-of-thumb threshold where Amazon's Fair Pricing crawler reliably flags listings; below that is structural noise. **My title drift is mostly because the channels run different languages. Is that a problem?** Not necessarily a brand-trust problem; it is a discovery problem. If your Shopline runs Trad-Chinese and Amazon JP runs JP keywords, that is correct localisation. The card flags it as "drift" so you can decide; if intentional, mark the SKU as `vortexiq_localised_title` to exclude from the count. **Image drift seems too sensitive; can I tune it?** The perceptual-hash threshold is configurable per-merchant in the manifest. Default is the standard pHash distance threshold; tightening or loosening shifts the count. **My count includes a SKU I deliberately list at different price points by region. How do I exclude it?** Tag the SKU `vortexiq_intentional_price_drift` and provide an annotation. The card excludes it but logs the annotation for audit history. **How fast does drift get detected after I update one channel?** 6 hours typically (the price/title sync cadence); image drift is detected once per 24 hours. The 7-day stability filter then delays the count update by a week to avoid flagging transient promos. **Why does the card include both price and image drift in one count?** Because both create the same business risk (brand-trust erosion, MAP-policy violation, Amazon Buy Box suspension), and the action playbook overlaps (visit each drifted SKU, decide whether to harmonise or document the divergence). The drill-down view separates dimensions for prioritisation. **My drift count went from 11 to 14 overnight. What happened?** Three usual causes. (1) New SKU launched on one channel before the other (transient drift; will resolve when the second channel catches up). (2) Bulk price update on one side without the other (deliberate human action; the card is doing its job). (3) Image refresh on one side; if the merchant updated Amazon photography but not Shopline, the image-drift count rises until they harmonise. **What is "Levenshtein distance"?** The minimum number of single-character edits (insertions, deletions, substitutions) to convert one string to another. Distance >5 means the titles are meaningfully different, not just whitespace or punctuation variants. For Asian languages we use a character-level distance, not byte-level, so Trad-Chinese characters count as one unit each. **Does this card account for Shopline's pre-order tag?** Pre-order and "coming-soon" tagged SKUs are excluded since they are not actively buyable. The exclusion list is configurable per-store. *** ### Tracked live in Vortex IQ Nerve Centre *Catalogue Drift vs Amazon* is one of hundreds of KPI pulses Vortex IQ tracks across Shopline 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](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.