Ecommerce Price List Analyzer

Analyze user-provided product or offer price records into grouped price intelligence. The Actor does not autonomously discover websites, scrape stores, use proxies, require logins, or call paid external APIs.

What It Does

This Actor turns current ecommerce price-list, offer, or competitor records into one deterministic analysis row per comparable product. It is meant for records you already collected or exported, not for autonomous website discovery.

Who It Is For

Pricing teams, ecommerce operators, resellers, catalog managers, and analysts who need to compare active listed prices across merchants, regions, channels, or internal catalogs.

Input

Provide records with product or item names, prices, optional currency, and optional source fields. Use groupKey, priceField, and dedupeKey to adapt the analysis to your own data.

Output

Each dataset row is one analyzed group with offer count, min/median/mean/max price, spread percentage, outlier count, deterministic score, recommended action, score explanation, and source record indexes.

How It Works

The Actor validates records, normalizes product names and numeric prices, removes duplicates using group, currency, price, and source key, and groups remaining rows by the configured item field. For each group it calculates min, median, mean, max, spread percentage, and IQR-based outlier count. The 0..100 score is explainable: more valid offers add coverage confidence, wider price spread raises review priority, and detected outliers reduce confidence. Recommended action is prioritize_review at 80+, review at 65+, and monitor below 65.

Example

{
  "records": [
    {"product": "Widget A", "price": "$10.00", "currency": "USD", "url": "https://a.example/w-a"},
    {"product": "Widget A", "price": 12, "currency": "USD", "url": "https://b.example/w-a"},
    {"product": "Widget B", "price": 20, "currency": "USD", "url": "https://a.example/w-b"}
  ],
  "groupKey": "product",
  "priceField": "price",
  "dedupeKey": "url"
}

Example output row:

{
  "groupKey": "widget a",
  "itemName": "widget a",
  "currency": "usd",
  "offerCount": 2,
  "minPrice": 10,
  "medianPrice": 11,
  "meanPrice": 11,
  "maxPrice": 12,
  "spreadPct": 18.1818,
  "outlierCount": 0,
  "score": 70,
  "recommendedAction": "review",
  "ScoreExplanation": ["offer_count:2", "spread_pct:18.18", "outliers:0", "coverage:+10", "spread:+10"],
  "sourceRecordIndexes": [0, 1]
}

Pricing

PAY_PER_EVENT event analysis_record_emitted is charged once per emitted grouped analysis row. Invalid records, duplicates, skipped rows, and charge-limited records are not billable.

Limitations

Currency symbols and codes are normalized for grouping only; this Actor does not perform FX conversion.

It does not distinguish completed sales from active listings, does not fetch live competitor pages, and does not infer demand. It analyzes only the records supplied in the input.

Integration

Run it directly with JSON input, from an Apify task, or downstream from another Actor that produces a dataset of price records. Results are written to the default dataset and the run summary is written to the OUTPUT key-value store record.

Differentiation

Use Ecommerce Price List Analyzer when you have active ecommerce offer or catalog records and need grouped price spread, outliers, and review priorities. Use Marketplace Sold Comps Analyzer when your records are completed marketplace sales with sale dates and conditions.