# Etsy Sales Intelligence (`marielise.dev/etsy-sales-intelligence`) Actor Estimate hidden Etsy lifetime sales and revenue from any listing, shop, or keyword. Reverse-engineers per-listing units sold using public signals, AI translation, and adaptive confidence bands. $0.05 per listing analysed. The Etsy seller intelligence estimator. - **URL**: https://apify.com/marielise.dev/etsy-sales-intelligence.md - **Developed by:** [Marielise](https://apify.com/marielise.dev) (community) - **Categories:** E-commerce, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 listing scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Etsy Sales Intelligence **The Etsy seller intelligence estimator. Etsy hides per-listing sales counts; this actor reverse-engineers them from public signals โ€” and bills you $0.05 per listing analysed. No setup. No external accounts. No infrastructure.** > ๐Ÿ’ธ **$0.05 per listing. All inclusive.** Bright Data anti-bot bypass, Claude Haiku translation, multilingual extraction, proxies, retries, compute โ€” every cost is baked in. You pay only when a listing record is successfully delivered to your dataset. > **Pricing fine print.** The headline rate is **$0.05 per listing** (event `listing-scraped`). Apify auto-adds two tiny platform events: **$0.00005 once per run start** (first 5 seconds of compute waived) and **$0.00001 per dataset record**. These add **~$0.00006 extra per listing** โ€” a 0.1% uplift, effectively rounding error. The tables below use the headline $0.05. ### Worked example A listing has **5 reviews**. The shop reports **1,200 sales / 257 reviews** (a 21% review rate). Estimated lifetime units sold = `5 / 0.21 โ‰ˆ 23`. At $24.50 USD that is roughly **$564 lifetime revenue** with a low/high band of **$282 โ€“ $846**. Every record carries a `confidenceNote` explaining the math, plus pre-formatted display strings (`estimatedRevenueDisplay: "$564"`) for spreadsheets and reports. ### Built for - **Etsy sellers** benchmarking competitors before a price/photo refresh - **Niche researchers** hunting hidden winners ahead of the crowd - **Print-on-demand operators** sizing demand before paying for a sample run - **Dropshippers** validating product ideas with real revenue numbers - **E-commerce analysts** feeding raw JSON into BI tools, LLMs, or dashboards Subscription tools (eRank, EtsyHunt, Sale Samurai) charge $20โ€“$30 per month for the same reverse-engineered estimate locked behind a UI. This actor returns raw structured data into your Apify dataset on demand โ€” pay only for what you scrape. ### Just run it 1. Open the actor in Apify Console 2. Choose a mode: - **`listing`** โ€” paste one or more Etsy listing URLs to analyse specific products - **`shop`** โ€” paste an Etsy shop URL to audit all listings in that shop - **`search`** โ€” type a keyword to research a niche (top results) 3. Set `maxResults` (default 50) 4. Click **Run** That's it. No API keys, no Bright Data signup, no Anthropic key. The actor handles every layer of infrastructure for you. ### Pricing | Run size | You pay | Time at default concurrency=5 | |---|---|---| | 1 listing | $0.05 | ~30 s | | 10 listings | $0.50 | ~1 min | | 50 listings | $2.50 | ~5 min | | 100 listings | $5.00 | ~10 min | | 500 listings | $25.00 | ~50 min | | 1,000 listings | $50.00 | ~1.7 h | | 5,000 listings | $250.00 | ~8 h | **Linear per-listing โ€” no subscription, no setup fee, no minimum.** Your `maxResults` input directly caps your spend. #### What's NOT charged - Failed scrapes (target page 404, target down) โ†’ free - Listings filtered out by your `minReviews` / `minEstimatedRevenue` thresholds โ†’ free - Listings cancelled by `maxResults` cap โ†’ free - Empty preview runs โ†’ free You pay only for records successfully pushed to your dataset. ### Output One record per analysed listing pushed to your dataset, plus a `RUN_SUMMARY.json` aggregate written to the run's key-value store. #### Units (read this once) - All `price*` and `*Revenue*USD` numbers are **whole US dollars, NOT cents**, rounded to 2 decimals. `estimatedRevenueUSD: 84656` means **$84,656.00**. - Every numeric field has a pre-formatted `*Display` sibling for table UIs and reports (`estimatedRevenueDisplay: "$84,656"`). - `shopReviewRate` is a `0..1` ratio. `shopReviewRatePct` is the same value as integer percentage `0..100`. - Counts are integers. Timestamps are ISO 8601 UTC. #### Per-listing fields | Field | Type | Unit | Description | |---|---|---|---| | `listingId` | string | โ€” | Etsy numeric listing ID | | `listingUrl` | string | URL | Canonical listing URL | | `title` | string | โ€” | Listing title (auto-translated to English when Etsy serves a non-English variant) | | `price` | number\|null | original currency | Whole units, e.g. `24.50` | | `priceDisplay` | string\|null | โ€” | `"โ‚ฌ24.50"` | | `priceUSD` | number\|null | USD whole dollars | Live FX-converted, 2 dp | | `priceUSDDisplay` | string\|null | โ€” | `"$24.50"` | | `currency` | string\|null | ISO 4217 | Original currency code | | `category` | string\|null | โ€” | Listing category breadcrumb | | `tags` | string[] | โ€” | Listing tags. **Best-effort: often empty on English-locale renders** (Etsy lazy-loads them via XHR). See Limitations. | | `images` | string[] | URLs | Listing image URLs | | `listingReviews` | integer | count | Reviews on this specific listing | | `viewsLast24h` | integer\|null | count | When Etsy exposes a counter | | `inCarts` | integer\|null | count | When Etsy shows the cart-count badge | | `badges` | string[] | โ€” | `["Bestseller", "Star Seller", "Quick Replies"]` etc | | `reviewDates` | string[] | ISO datetime | Recent listing review timestamps | | `trending` | boolean | โ€” | True when 6+ of the last 10 reviews fall within 90 days | | `dormant` | boolean | โ€” | True when no review in the last 180 days | | `shopName` | string | โ€” | Etsy shop slug | | `shopUrl` | string | URL | Etsy shop URL | | `shopTotalSales` | integer\|null | count | Lifetime sales reported by the shop page | | `shopTotalReviews` | integer\|null | count | Aggregated shop reviews | | `shopReviewRate` | number\|null | ratio 0..1 | `shopTotalReviews / shopTotalSales`, clamped 0.05โ€“0.50 | | `shopReviewRatePct` | integer\|null | percent 0..100 | Same value ร— 100 for table views | | `effectiveReviewRate` | number | ratio 0..1 | Shop rate after niche blend AND price-tier adjustment โ€” the value actually used in estimation | | `effectiveReviewRatePct` | integer | percent 0..100 | Same ร— 100 | | `nicheBlendApplied` | boolean | โ€” | True when the shop rate was blended with the niche median (run had 3+ distinct shops AND shop totals were measured) | | `observedReviewRate` | number\|null | ratio 0..1 | Bayesian observed shop rate from 4+ `trackOverTime` snapshots. Null until accumulated. | | `observedReviewRatePct` | integer\|null | percent 0..100 | Same ร— 100 | | `observedRateSampleCount` | integer | count | How many snapshots produced the observed rate | | `plausibility` | enum\|null | `"plausible"` / `"suspicious"` / `null` | AI sanity-check flag; null when disabled or check failed | | `plausibilityReason` | string\|null | โ€” | Short explanation when `plausibility = "suspicious"` | | `salesPerYearShop` | integer\|null | count/yr | Shop average annual sales (lifetime รท age) | | `salesPerYearShopDisplay` | string\|null | โ€” | `"427 / yr"` | | `listingAgeYears` | number\|null | years | Listing age inferred from oldest review date | | `listingSalesPerYearEstimate` | integer\|null | count/yr | Per-listing velocity = `estimatedUnitsSold / listingAgeYears` | | `listingSalesPerYearDisplay` | string\|null | โ€” | `"35 / yr"` | | `shopAge` | string\|null | โ€” | `"6 years"` | | `shopLocation` | string\|null | โ€” | Free-form location of the shop, e.g. `"Miami, Florida"` | | `shipsFromCountry` | string\|null | ISO-3166-1 alpha-2 | Country the listing ships from, e.g. `"US"` | | `shipsFromRegion` | string\|null | โ€” | Region/state, e.g. `"FL"` | | **`estimatedUnitsSold`** | integer | count | **Central lifetime estimate** | | `estimatedUnitsSoldDisplay` | string | โ€” | `"1,480"` | | `estimatedSalesLow` / `estimatedSalesHigh` | integer | count | Adaptive ยฑ25โ€“50% band (see "How the estimate works") | | `estimatedSalesRangeDisplay` | string | โ€” | `"740 โ€“ 2,220"` | | **`estimatedRevenueUSD`** | number | USD whole dollars | **Central ร— `priceUSD`** | | `estimatedRevenueDisplay` | string | โ€” | `"$84,656"` | | `estimatedRevenueLowUSD` / `estimatedRevenueHighUSD` | number | USD whole dollars | Same adaptive band, applied to revenue | | `estimatedRevenueRangeDisplay` | string | โ€” | `"$42,328 โ€“ $126,984"` | | `confidence` | enum | `"high"` / `"medium"` / `"low"` | Sortable confidence tier mirroring the band | | `confidenceNote` | string | โ€” | Plain-English explanation including price-tier adjustment, trending uplift, and band tier | | `competingListings` | integer\|null | count | Search-mode only | | `scrapedAt` | string | ISO datetime | Record timestamp | | `delta` | object\|null | โ€” | Populated only when `trackOverTime` is on and a previous snapshot exists | #### Run aggregate (KV `RUN_SUMMARY.json`) A single object summarising the run, written every time: ```json { "mode": "search", "scrapedAt": "2026-04-30T08:00:00.000Z", "totalCandidates": 50, "successfullyScraped": 48, "pushedToDataset": 42, "skippedFilters": 6, "failedScrapes": 2, "totalEstimatedRevenueUSD": 1284500, "totalEstimatedRevenueDisplay": "$1,284,500", "totalEstimatedUnitsSold": 36420, "totalEstimatedUnitsSoldDisplay": "36,420", "averagePriceUSD": 28.40, "averagePriceDisplay": "$28", "trendingCount": 14, "dormantCount": 7, "topByRevenue": [ { "listingId": "1570282475", "title": "Custom Hand-Painted Pet Portrait Leather Keyring", "shopName": "BeanieBaeArt", "estimatedRevenueUSD": 84656, "estimatedRevenueDisplay": "$84,656", "listingUrl": "https://www.etsy.com/listing/1570282475/..." } ], "topByUnits": [ { "listingId": "1234567890", "title": "Sticker Pack โ€” 10 Pieces", "shopName": "StickerWorld", "estimatedUnitsSold": 12500, "estimatedUnitsSoldDisplay": "12,500", "listingUrl": "https://www.etsy.com/listing/1234567890/..." } ], "shipsFromBreakdown": [ { "country": "US", "listings": 28, "share": 0.667, "sharePct": 67, "sharePctDisplay": "67%", "totalEstimatedRevenueUSD": 856200, "totalEstimatedRevenueDisplay": "$856,200" }, { "country": "GB", "listings": 9, "share": 0.214, "sharePct": 21, "sharePctDisplay": "21%", "totalEstimatedRevenueUSD": 312800, "totalEstimatedRevenueDisplay": "$312,800" }, { "country": "CA", "listings": 5, "share": 0.119, "sharePct": 12, "sharePctDisplay": "12%", "totalEstimatedRevenueUSD": 115500, "totalEstimatedRevenueDisplay": "$115,500" } ] } ```` > **Caveat on `shipsFromBreakdown`.** This is a **seller-side** distribution: which countries the listings ship from. It is **not** a buyer-country / sales-destination split. Etsy does not expose buyer-country sales mix on public pages; only the shop owner can see that via Etsy Stats. The breakdown is still useful for niche research (e.g. *"is this niche dominated by US sellers or international?"*) โ€” just don't market it as buyer demographics. ### Input examples #### One specific listing ```json { "mode": "listing", "listingUrls": [ { "url": "https://www.etsy.com/listing/1234567890/example-product" } ], "maxResults": 1 } ``` Cost: **$0.05**. #### Audit a competitor's full shop ```json { "mode": "shop", "shopUrl": "https://www.etsy.com/shop/CompetitorShopName", "maxResults": 50, "minReviews": 1 } ``` Cost: up to **$2.50** (50 ร— $0.05). #### Niche research ```json { "mode": "search", "searchQuery": "minimalist wall art", "minReviews": 5, "minEstimatedRevenue": 500, "maxResults": 100 } ``` Cost: up to **$5.00**. Filters drop low-signal listings before they reach the dataset, so actual charge is usually lower. #### Track a shop weekly ```json { "mode": "shop", "shopUrl": "https://www.etsy.com/shop/MyShopToTrack", "trackOverTime": true, "maxResults": 50 } ``` Run on a weekly schedule. Each record gains a `delta` block: `reviewsDelta`, `estimatedSalesDelta`, `salesPerDay`, `daysSinceLast`. First run establishes the baseline; subsequent runs compute growth. ### How the estimate works 1. Fetch the listing page โ†’ extract `listingReviews`, badges, recent review timestamps, ships-from country. 2. Fetch the shop page (cached once per run per shop) โ†’ extract `shopTotalSales`, `shopTotalReviews`, `shopAge`, `shopLocation`. 3. `shopReviewRate = shopTotalReviews / shopTotalSales`, clamped to `[0.05, 0.50]` to suppress wild estimates from tiny samples. Falls back to `0.20` (Etsy-wide observed midpoint) when shop totals are unavailable. 4. **Price-tier adjustment.** Cheap items get fewer reviews per sale than expensive ones, even within the same shop. The shop rate is multiplied by a price-tier coefficient: | Listing price (USD) | Coefficient | Why | |---|---|---| | < $20 | ร— 0.70 | Impulse buyers leave fewer reviews | | $20 โ€“ $100 | ร— 1.00 | Baseline | | $100 โ€“ $300 | ร— 1.20 | More engaged buyers | | > $300 | ร— 1.40 | High-ticket reviewers most diligent | Result is `effectiveReviewRate`, also clamped to `[0.05, 0.50]`. 5. `estimatedUnitsSold = round(listingReviews / effectiveReviewRate)`. 6. `estimatedRevenueUSD = estimatedUnitsSold ร— priceUSD`. 7. **Adaptive confidence band:** - **ยฑ25 %** when shop totals are real (measured) AND listing has 50+ reviews โ†’ `confidence: "high"` - **ยฑ35 %** when shop totals are real but listing has 10โ€“49 reviews โ†’ `confidence: "medium"` - **ยฑ50 %** when shop totals are assumed (20 % default) OR listing has < 10 reviews โ†’ `confidence: "low"` The `confidence` field is sortable for filtering; `confidenceNote` explains the math in plain English. 8. **Trending uplift.** When the listing's review velocity flags it as `trending = true` (6+ of the last 10 reviews within 90 days), the band is shifted asymmetrically: the low edge tightens by ร— 0.95 and the high edge widens by ร— 1.15. Reflects the empirical observation that trending listings tend to over-perform their historical-average estimate. 9. **Velocity signals.** Two derived fields turn lifetime numbers into per-year flows: - `salesPerYearShop = shopTotalSales / parseShopAgeYears` โ€” average annual shop pace. - `listingSalesPerYearEstimate = estimatedUnitsSold / listingAgeYears`, where `listingAgeYears` is derived from the **oldest review date** in JSON-LD. Tells you whether a high-revenue listing is an active winner or a legacy product winding down. 10. **Niche calibration (two-pass estimation).** When a run touches 3+ distinct shops, the actor switches to a two-pass estimator: - **Pass 1** scrapes every listing + shop in parallel and stashes the raw data โ€” no estimates yet. - Between passes, it computes `nicheReviewRate` = median shop review rate across distinct shops in the run. - **Pass 2** estimates each listing with the shop rate **blended** toward the niche: `blendedShopRate = 0.7 ร— shopRate + 0.3 ร— nicheRate`. Outlier shops (e.g. one at 8 % in a niche where median is 22 %) are pulled toward the niche norm, reducing per-listing estimation error. - The blend is only applied when shop totals are **measured** (not assumed). Per-listing records flag `nicheBlendApplied: true` and the `confidenceNote` describes the blend. - With fewer than 3 distinct shops (typical for `listing` mode with one URL), the blend is skipped โ€” rate stays as-is. 11. **Bayesian observed rate** (only with `trackOverTime: true`, kicks in after 4+ weekly snapshots per shop). Each run appends a per-shop snapshot of `(shopTotalSales, shopTotalReviews)` to KV. Once 4+ snapshots exist, the actor computes `observedRate = (lastReviews โˆ’ firstReviews) / (lastSales โˆ’ firstSales)` โ€” i.e. the *actual* review rate during the tracked period, not the lifetime average. This observed rate is then blended with the lifetime rate as `posteriorShopRate = 0.6 ร— observed + 0.4 ร— lifetime` and used as the shop's effective rate for the rest of the pipeline. Most accurate signal we have. Per-record fields `observedReviewRate`, `observedReviewRatePct`, and `observedRateSampleCount` expose what fired. 12. **AI plausibility check** (default on; toggle via `plausibilityCheck: false` to skip). After estimation, each record is sanity-checked by Claude Haiku 4.5 against red flags like *estimatedUnitsSold > shopTotalSales*, *revenue > $5M*, *price โ‰ค 0*, etc. Output fields `plausibility` (`"plausible"` / `"suspicious"` / `null`) and `plausibilityReason` flag outliers for human review without blocking them from the dataset. 13. `trending = true` when 6+ of the last 10 reviews fall within 90 days. 14. `dormant = true` when no review timestamps fall within the last 180 days. ### What we deliberately did NOT build (and why) Two improvements were considered for v2 but skipped on engineering principle, not laziness: - **Calibration corpus.** Validating the algorithm's coefficients against a curated set of Etsy shops with publicly disclosed lifetime sales would let us tune coefficients with statistical confidence. **Skipped** because the realistic public corpus is ~10โ€“15 shops (interviews, podcasts, indie-maker tweets) โ€” too small for confident tuning, and self-reported numbers are noisy. The right way to do this is to collect anonymised real customer run outputs over months, backtest against any sellers who later publicly disclose, and refine quarterly. Pre-launch this is impossible. - **Category-specific default rates.** Same data problem: without ground truth or large samples, hard-coding per-category rates would just be more wrong-confidence numbers stacked on existing ones. Price-tier adjustment (already implemented) captures most of what category would, more reliably. If you're a researcher with verified shop sales data and would like to help calibrate, the source is open on Apify โ€” open an issue. ### Limitations - **Estimates, not facts.** Etsy never reveals true per-listing sales. Treat output as directional intelligence with a stated `confidenceNote`. - **Mixed-price shops skew per-listing estimates.** A shop selling one $5 sticker and one $500 sculpture distorts both estimates toward the average review rate. The clamp `[0.05, 0.50]` cushions this but does not eliminate it. - **Currency rates** refresh once per run and are persisted to KV `CURRENCY_RATES.json` for transparency. - **`tags` is best-effort and frequently empty.** Etsy serves tag data inline only on some locale variants. On the English (US) variant tags are lazy-loaded via XHR after page render, and the underlying scrape captures pre-hydration HTML โ€” so the tags array is empty in that case. The translator never invents tags from the title or description; what you see is what Etsy actually shipped in the initial HTML. Estimates do not depend on tags. - **`listingFavourites` is no longer exposed by Etsy** publicly (deprecated by Etsy ~2024). The field has been removed from the actor. - **Buyer-country distribution is not available.** `shipsFromBreakdown` reports where listings *ship from*, not where buyers are. Etsy only exposes buyer-country sales mix to the shop owner via Etsy Stats. ### FAQ #### How accurate is the estimate? The band is adaptive: ยฑ25% when both shop totals are measured and the listing has 50+ reviews (high confidence), ยฑ35% when the listing has 10โ€“49 reviews (medium), and ยฑ50% when shop totals are assumed or the listing has fewer than 10 reviews (low). Real-world tests show the central estimate falls within the reported band ~80% of the time across shops with measured totals. For tiny shops or zero-review listings accuracy collapses; `confidenceNote` always reports the tier (`high` / `medium` / `low`) so you can filter accordingly. #### Why doesn't Etsy show sales counts directly? Etsy removed per-listing sales counts to discourage clones. Public reviews, shop totals, and badges remain โ€” exactly the signals this actor consumes. #### Do I need a Bright Data account or Anthropic key? **No.** Everything is included in the $0.05 per-listing price. The publisher absorbs all infrastructure (anti-bot bypass, translation, proxies, compute). You just run. #### Why "$0.05" and not a tiny number with a subscription? The actor uses Apify's Pay-Per-Event model โ€” you pay only when a complete listing record lands in your dataset. No subscription, no setup fee, no compute charges. A failed scrape, a filtered-out listing, or a run that hits its `maxResults` cap costs you nothing. Compared with subscription tools like eRank ($10/mo) or EtsyHunt ($20/mo), this actor breaks even at ~200-400 listings per month โ€” and gives you raw structured data instead of a locked-in dashboard. #### Can I run this against thousands of listings? Yes. A 5,000-listing run costs **$75** flat. Increase the `concurrency` input (default 5, max 20) to speed up โ€” each step adds parallel scraping requests. Split into batches if a single Apify run exceeds memory or time limits. #### Does the actor scrape in parallel? Yes. Listings are processed in batches of `concurrency` (default 5) using `Promise.allSettled`, with shared shop-fetch deduping (concurrent listings from the same shop reuse a single in-flight shop request). At default concurrency a 50-listing run finishes in roughly 4โ€“6 minutes versus ~25 minutes sequentially. #### Can the actor tell me which countries are buying most? **No** โ€” Etsy does not expose buyer-country sales splits on public pages. Only the shop owner sees that via Etsy Stats. The `shipsFromBreakdown` aggregate in `RUN_SUMMARY.json` is a **seller-side** distribution (where the listings ship from), not a buyer-country mix. #### Why is `tags` sometimes empty? Etsy A/B tests its render path. On the English (US) variant tags are lazy-loaded via XHR after the page loads; the scrape captures the pre-hydration HTML and tags are missing. On other locale variants Etsy inlines tags. The actor does not invent tags from the title โ€” what you see is what Etsy shipped in the HTML. Estimates do not depend on tags. #### How do I track changes over time? Set `trackOverTime: true` and re-run with the same input on a schedule. Each record gains a `delta` block once a previous snapshot exists. #### What if a scrape fails? Failed scrapes are NOT charged. You only pay for records successfully delivered to your dataset. #### Can I export to Google Sheets / Airtable / a webhook? Yes โ€” every Apify dataset can be exported via the Console UI or piped through Apify Integrations to Google Sheets, Airtable, Slack, Make, Zapier, or a custom webhook. See [Apify Integrations docs](https://docs.apify.com/platform/integrations). ### How this is built The actor stack โ€” fully managed, you don't pay or configure any of it: - **Bright Data Web Unlocker** for Akamai/Cloudflare/PerimeterX bypass on Etsy listing and shop pages. - **Claude Haiku 4.5** for translating cosmetic fields (title, category, tags, badges) when Etsy serves a non-English variant. Numeric fields are never sent to the LLM. - **Multilingual regex** in the shop scraper extracts numeric stats (sales, reviews, shop age) using patterns covering English, Spanish, French, German, Italian, Portuguese, and Dutch โ€” so estimates work regardless of routing locale. - **JSON-LD parsing** for `Product`, `BreadcrumbList`, and `Organization` schemas โ€” locale-independent and survives Etsy's frequent DOM redesigns. - **Live currency rates** fetched once per run from `open.er-api.com` (free, no key needed). - **Shop-level cache** prevents fetching the same shop twice per run, and concurrent listings from the same shop reuse a single in-flight request. If you're a developer who wants to fork this actor and run your own infrastructure, the source is on Apify and accepts custom `brightDataApiKey` and `anthropicApiKey` overrides via the input form (advanced). ### Support Questions, feature requests, or issues: open a ticket in the actor's Issues tab on Apify, or message the publisher directly. # Actor input Schema ## `mode` (type: `string`): How to source listings. listing = specific URLs. shop = every listing in a shop. search = top results for a keyword query. ## `listingUrls` (type: `array`): Required when mode is `listing`. Paste one or more Etsy listing URLs (e.g., https://www.etsy.com/listing/123456789/...). ## `shopUrl` (type: `string`): Required when mode is `shop`. Paste an Etsy shop URL (e.g., https://www.etsy.com/shop/ShopName). ## `searchQuery` (type: `string`): Required when mode is `search`. Keywords describing what to research (e.g., 'minimalist wall art', 'handmade leather wallet'). ## `minReviews` (type: `integer`): Skip listings with fewer reviews than this. Reviews drive estimation accuracy. Skipped listings are NOT charged. ## `minEstimatedRevenue` (type: `integer`): Skip listings with estimated revenue below this threshold (USD). Skipped listings are NOT charged. ## `maxResults` (type: `integer`): Hard cap on the number of listings to deliver. Your bill is at most `maxResults ร— $0.05`. Default 50 โ†’ $2.50 max. ## `trackOverTime` (type: `boolean`): If enabled, the actor stores per-listing snapshots in its key-value store. Subsequent runs against the same listings return a `delta` block with review growth, sales growth, and sales-per-day. Use with Apify Schedules to automate weekly tracking. ## `concurrency` (type: `integer`): How many listings to process in parallel. Default 5. Higher = faster, but each step adds parallel scraping requests. Max 20. ## `plausibilityCheck` (type: `boolean`): By default, deterministic math checks flag obvious impossibilities (e.g. listingReviews > shopTotalReviews, priceUSD โ‰ค 0, parsing-error titles). Enable this to ALSO run a Claude Haiku sanity check that catches softer outliers. Off by default because the LLM occasionally flags legitimate edge cases (e.g. shops where one hit listing carries all reviews). ## `debugDumpHtml` (type: `boolean`): Saves each scraped listing's raw HTML and shop HTML to the run's key-value store under LISTING\_HTML\_ and SHOP\_HTML\_. Use only if a field comes back unexpectedly null and you want to share the source HTML when filing an issue. Keep off for production. ## Actor input object example ```json { "mode": "listing", "listingUrls": [ { "url": "https://www.etsy.com/listing/1234567890/example-product" } ], "shopUrl": "https://www.etsy.com/shop/ExampleShop", "searchQuery": "minimalist wall art", "maxResults": 50, "trackOverTime": false, "concurrency": 5, "plausibilityCheck": false, "debugDumpHtml": false } ``` # Actor output Schema ## `listings` (type: `string`): Per-listing estimated units sold, revenue bands, badges, and confidence notes ## `keyValueStore` (type: `string`): Run metadata, currency rates cache, and trackOverTime snapshots # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "listingUrls": [ { "url": "https://www.etsy.com/listing/1234567890/example-product" } ], "shopUrl": "https://www.etsy.com/shop/ExampleShop", "searchQuery": "minimalist wall art" }; // Run the Actor and wait for it to finish const run = await client.actor("marielise.dev/etsy-sales-intelligence").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "listingUrls": [{ "url": "https://www.etsy.com/listing/1234567890/example-product" }], "shopUrl": "https://www.etsy.com/shop/ExampleShop", "searchQuery": "minimalist wall art", } # Run the Actor and wait for it to finish run = client.actor("marielise.dev/etsy-sales-intelligence").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "listingUrls": [ { "url": "https://www.etsy.com/listing/1234567890/example-product" } ], "shopUrl": "https://www.etsy.com/shop/ExampleShop", "searchQuery": "minimalist wall art" }' | apify call marielise.dev/etsy-sales-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=marielise.dev/etsy-sales-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Etsy Sales Intelligence", "description": "Estimate hidden Etsy lifetime sales and revenue from any listing, shop, or keyword. Reverse-engineers per-listing units sold using public signals, AI translation, and adaptive confidence bands. $0.05 per listing analysed. The Etsy seller intelligence estimator.", "version": "0.0", "x-build-id": "UX5zGzPwJnjbImT0w" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/marielise.dev~etsy-sales-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-marielise.dev-etsy-sales-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/marielise.dev~etsy-sales-intelligence/runs": { "post": { "operationId": "runs-sync-marielise.dev-etsy-sales-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/marielise.dev~etsy-sales-intelligence/run-sync": { "post": { "operationId": "run-sync-marielise.dev-etsy-sales-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "listing", "shop", "search" ], "type": "string", "description": "How to source listings. listing = specific URLs. shop = every listing in a shop. search = top results for a keyword query.", "default": "listing" }, "listingUrls": { "title": "Listing URLs", "type": "array", "description": "Required when mode is `listing`. Paste one or more Etsy listing URLs (e.g., https://www.etsy.com/listing/123456789/...).", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "shopUrl": { "title": "Shop URL", "type": "string", "description": "Required when mode is `shop`. Paste an Etsy shop URL (e.g., https://www.etsy.com/shop/ShopName)." }, "searchQuery": { "title": "Search Query", "type": "string", "description": "Required when mode is `search`. Keywords describing what to research (e.g., 'minimalist wall art', 'handmade leather wallet')." }, "minReviews": { "title": "Min Reviews", "minimum": 0, "type": "integer", "description": "Skip listings with fewer reviews than this. Reviews drive estimation accuracy. Skipped listings are NOT charged." }, "minEstimatedRevenue": { "title": "Min Estimated Revenue (USD)", "minimum": 0, "type": "integer", "description": "Skip listings with estimated revenue below this threshold (USD). Skipped listings are NOT charged." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Hard cap on the number of listings to deliver. Your bill is at most `maxResults ร— $0.05`. Default 50 โ†’ $2.50 max.", "default": 50 }, "trackOverTime": { "title": "Track Over Time", "type": "boolean", "description": "If enabled, the actor stores per-listing snapshots in its key-value store. Subsequent runs against the same listings return a `delta` block with review growth, sales growth, and sales-per-day. Use with Apify Schedules to automate weekly tracking.", "default": false }, "concurrency": { "title": "Concurrent listings", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many listings to process in parallel. Default 5. Higher = faster, but each step adds parallel scraping requests. Max 20.", "default": 5 }, "plausibilityCheck": { "title": "Extra AI plausibility check (off by default)", "type": "boolean", "description": "By default, deterministic math checks flag obvious impossibilities (e.g. listingReviews > shopTotalReviews, priceUSD โ‰ค 0, parsing-error titles). Enable this to ALSO run a Claude Haiku sanity check that catches softer outliers. Off by default because the LLM occasionally flags legitimate edge cases (e.g. shops where one hit listing carries all reviews).", "default": false }, "debugDumpHtml": { "title": "Debug: dump HTML to key-value store", "type": "boolean", "description": "Saves each scraped listing's raw HTML and shop HTML to the run's key-value store under LISTING_HTML_ and SHOP_HTML_. Use only if a field comes back unexpectedly null and you want to share the source HTML when filing an issue. Keep off for production.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```