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retail-assortment-gap-analysis

核心功能:通过Crawlora API获取Shopify、Target、IKEA等平台商品目录,对比自有与竞品品类,精准识别品类、品牌、价格带等维度缺口,区分样本缺失与明确缺失。典型场景:零售商家优化品类布局、竞品调研。输入需指定店铺、品类、市场等参数,输出含覆盖台账、对比矩阵、优先级缺口清单及佐证信息。

crawlora-org
crawlora-org
热度 42.60
最近更新 2026-09-21 09:51:23
分类:数据依赖:代码执行 / 第三方 API / 读写文件应用场景:市场分析 / 数据处理 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add retail-assortment-gap-analysis
Metadata
name
retail-assortment-gap-analysis
description
Compare competing retail assortments through Crawlora catalogs. Use to find observed gaps in categories, brands, product attributes, variants, and price bands, with explicit catalog coverage and product-matching evidence.

Retail assortment gap analysis

Compare defined category samples or complete collections and identify evidence-backed assortment gaps. Keep a product absent from the collected sample distinct from one confirmed absent from a fully enumerated catalog.

Setup and API contract

Set CRAWLORA_API_KEY to your key from crawlora.net. Run the bundled scripts/crawlora.sh from this skill directory or by absolute path. It sends x-api-key to https://api.crawlora.net/api/v1; keep the key in the environment. Read reference/endpoints.md for the selected endpoints, required parameters, limits, and response behavior. Check the application code as well as HTTP status; successful payloads are inside data. Stop on 401/403, back off on 429, and retry a transient 5xx once. A failed or partial fetch is not an empty market or catalog. Bound requests to the user's scope and credit budget. For repeated collection, save the query, source IDs, pagination progress, and retrieval timestamps with the results so interrupted work can resume; do not create monitors implicitly.

Define and collect the comparison

  1. Agree on stores, target market, category boundaries, price-band edges, and counting unit: parent products or sellable variants. Fix store, country, language, currency, and retrieval window before collecting data. Use the user's own assortment when supplied, alongside public competitor records.
  2. For Shopify, resolve a storefront with /shopify/store, discover handles via /shopify/collections, and enumerate /shopify/collections/{handle}/products. /shopify/products provides the broader storefront catalog. Keep url fixed across pages and detail calls. Use returned product handles for detail. Classic transport does not support server-side sort/facets; do not pass sortBy unless transport_mode is ssr_embedded and the reference permits it.
  3. For Target, discover /target/categories, browse /target/category-products, and retain returned dynamic filter option IDs. Preserve the same store_id when supplied by the user for browsing and /target/product?tcin=... detail. This skill has no Target store-discovery tool: report the default store context if a verified ID is unavailable, rather than inventing a local store match.
  4. For IKEA, /ikea/search finds seed products; fetch detail to take category keys from its category paths for /ikea/category pagination and item numbers for detail. Keep country and language fixed. Keyword search is a candidate sample, not an exhaustive assortment even when its returned page is full.
  5. Record pages/offsets, filters, declared totals, unique IDs, and stopping reason. Follow each endpoint's pagination limits; Shopify supports up to 250 per page, Target category browsing caps at page 50, IKEA category uses offset/size. A request budget or endpoint cap means partial coverage. Deduplicate overlapping collections and stop if pages repeat rather than assuming new coverage.
scripts/crawlora.sh /ikea/search q=desk country=us language=en size=10
scripts/crawlora.sh /target/categories
# For a user-selected Shopify store, use its URL unchanged through discovery:
# scripts/crawlora.sh /shopify/collections url="$STOREFRONT_URL" limit=50 page=1

Normalize and identify gaps

  • Build a shared category/attribute mapping while preserving each store's original taxonomy. Store-specific category IDs and labels are not cross-store keys.
  • Match identical products using a returned GTIN or verified brand/model/variant combination. Treat retailer-local IDs as local. A similar title is only a candidate match; private-label alternatives belong in an attribute comparison.
  • Count parent products once for breadth; count sizes/colors only in the variant view. A sold-out variant is an availability gap, not a missing catalog product.
  • Use consistent currency, tax context, pack quantity, dimensions, and sale versus regular price basis. Do not compare a multipack with a single item by sticker price alone. Avoid counting a product's minimum variant price as every variant's price. Keep missing brand, attributes, or prices in an unknown bucket.
  • Calculate category/brand/price-band shares with explicit denominators and unknown counts. For incomplete coverage, label differences as observed sample gaps. A niche carried by a competitor is not proof of sales, demand, or profitability.

Deliverable

Return a coverage ledger, comparable assortment matrix, and prioritized gap list. For each proposed gap show category/attribute, stores observed, product and variant counts, price basis, example source URLs/IDs, collection time, confidence, and what would validate demand. Explain whether evidence supports absence, out-of-stock, unknown coverage, or a taxonomy mismatch. Do not turn a snapshot into a trend; changes require comparable saved snapshots and the same collection scope.