# Shopify Store Discovery - Apps, Revenue Estimate, Tech Stack (`seibs.co/shopify-store-discovery`) Actor Find Shopify stores by domain list with full intel: 30+ app detection (Klaviyo/Recharge/Yotpo/Gorgias/etc), product count, revenue estimate range, theme, social links. Server-side filter by required/excluded apps + revenue range. For D2C SaaS sales teams. - **URL**: https://apify.com/seibs.co/shopify-store-discovery.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** E-commerce, Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $8.00 / 1,000 store records 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 ## Shopify Store Discovery Find Shopify stores by domain and enrich each with app-stack detection (30+ apps), product / revenue stats, theme, social links, and contact info. ### What does Shopify Store Discovery do? It verifies Shopify via the public `/products.json` endpoint (with Liquid HTML fallback), detects 30+ installed apps from script-tag footprints, and pulls product catalog stats, theme, social links, contact info, and a heuristic monthly revenue estimate. Server-side filters by required apps (AND), excluded apps (NOT), product count band, revenue band, country, and category keyword - filtered-out stores are not charged. ### Features - Shopify verification - `GET /products.json?limit=1` first, Liquid template HTML fallback. - 38+ app detection from script footprints, each tagged with confidence (low / medium / high). - Server-side filters - required_apps (AND), excluded_apps (NOT), product band, revenue band, country, keyword. - Heuristic monthly revenue estimate (`deep_analyze` mode) with Shopify Plus, subscription, B2B/wholesale, and enterprise-stack refinements; returns a `revenue_estimate_confidence` (low / medium / high) so buyers know how much to trust it. - Shopify Plus + B2B/wholesale classification surfaced as their own boolean fields. - Per-store progress logging - one info line per store with size, apps, revenue, and email so long runs are auditable. - Contact enrichment (opt-in default true) - scrapes `/contact` `/pages/contact` `/about` and surfaces `best_contact_email` (founder/sales/owner ranked above generic info/support), all `contact_emails` with role classification, and `contact_phones`. Only charged when something is extracted. - Founder + brand-story intel (opt-in) - `founder_names`, `founding_year`, and `brand_story_keywords` (vegan, sustainable, made in USA, woman-owned, B-corp, etc) for sales personalization. - Last-product-published timestamp + `days_since_last_publish` so you can split fresh brands from abandoned ones. - Visible review count + average rating when a review app (Yotpo / Loox / Judge.me / Okendo / Stamped / Reviews.io) is detected. - Theme name + version detection. - Social link parsing (IG, FB, TikTok, X, YouTube, Pinterest, LinkedIn). - App-list unwind view - one row per (store, app) for downstream slicing. ### Use cases D2C SaaS sales teams selling INTO the Shopify ecosystem - concrete buyers: - Klaviyo competitors (Omnisend, Sendlane, Drip) - filter `excluded_apps: ["klaviyo"]` for non-Klaviyo Shopify stores. - Recharge competitors (Bold, Loop, Awtomic, Stay AI) - `has_subscriptions: true` AND no Recharge. - Yotpo / Stamped / Judge.me competitors (Okendo, Loox, Reviews.io). - Gorgias competitors (Zendesk, Re:amaze, Help Scout). - Postscript / Attentive competitors - segment by SMS app presence. - Triple Whale / Northbeam / Polar Analytics - find stores with 5+ apps and $100K+ revenue. - Shogun / PageFly / Replo / GemPages teams - find competitors' installed base. - Headless agencies (Hydrogen / Storefront API) - find Plus-tier Shopify stores still on Liquid. ### FAQ **Q: Is this legal?** A: Yes - we hit Shopify's public `/products.json` endpoint, the public Liquid HTML, and public `/contact` / `/about` / `/pages/contact` pages. All publicly accessible to any browser. Use the data per Shopify's Terms of Service and applicable law. **Q: Why might a run fail?** A: (1) Cloudflare challenge - we use `curl_cffi` with Chrome 131 impersonation which handles most, but RESIDENTIAL proxies improve consistency. (2) Domain is not Shopify - row comes back `is_shopify: false` with the detection reason and is not charged. (3) `/products.json` is rate-limited at the store level - we self-throttle, but very high concurrency on a single brand's domain group can still trigger it. **Q: How fresh is the data?** A: Live at crawl time. Product counts, prices, theme, apps, contact info, social links, and `days_since_last_publish` are read directly from the store at run time - no internal cache. **Q: Can I schedule this daily or weekly?** A: Yes - weekly is typical for D2C-into-Shopify SaaS prospecting (find fresh installs of competitor apps, drop the new ones into outbound). Daily for very narrow watchlists. Use Apify Schedules. **Q: How do I push results into a CRM?** A: The output maps cleanly to standard lead schemas - `best_contact_email`, `contact_phones`, social links, store name, and the `apps_installed` array all forward to HubSpot, Salesforce, Pipedrive, Apollo, or Klaviyo via Zapier/Make/n8n. Webhook the full record on each run-complete for real-time CRM enrichment. **Q: How accurate is the revenue estimate?** A: It is a heuristic from `product_count x avg_price x estimated_orders/day multipliers` (with Shopify Plus, subscription, B2B/wholesale, and enterprise-stack refinements). Expect approximately +/-50% error on absolute MRR. The wedge is relative ranking - "under $10K/mo vs over $500K/mo" - not precision. Use it as a filter floor (`min_estimated_monthly_revenue_usd: 50000` to skip tiny stores), not ground truth for a financial model. `revenue_estimate_confidence` (low / medium / high) tells you how much to trust each estimate. **Q: How does PPE pricing actually work here?** A: Filtered-out and non-Shopify rows are NEVER charged. You only pay for stores that match your input criteria. Contact enrichment only bills when data is actually extracted. See the Pricing section for per-event rates. ### Related Actors - [`b2b-sales-triggers`](../b2b-sales-triggers/) - score intent (hiring, funding, exec changes) on top of Shopify-store fit. Run this actor to find non-Klaviyo $50K+ MRR stores, then pipe the domain list into the triggers actor. - [`google-maps-reviews-pro`](../google-maps-reviews-pro/) - layer review sentiment / topic analysis on Shopify brands with physical retail or showrooms. - [`reddit-topic-watcher`](../reddit-topic-watcher/) - watch for `alternative_seek` and `complaint` posts mentioning Shopify apps your prospects are using (conquest signals). ### Integrations - Zapier - push to HubSpot/Salesforce/Pipedrive/Apollo/Klaviyo - Make.com - workflow automation - n8n - self-hosted automation - Apify webhooks - POST to your endpoint - API + dataset export (JSON/CSV/Excel/XML) - MCP / AI agents - call from Claude/GPT/LangChain ### App detection list (30+ apps) Email + SMS: Klaviyo, Postscript, Privy, Justuno, Sumo, Drip. Subscriptions: Recharge, Bold, Loop, Smile.io. Reviews + UGC: Yotpo, Stamped.io, Judge.me, Okendo, Loox, Reviews.io, Trustpilot, Bazaarvoice. Support + Chat: Gorgias, Tidio, Drift. Search + Personalization: Klevu, Searchanise, Algolia, Nosto, Dynamic Yield, LimeSpot, Wiser. Page Builders: Shogun, PageFly, Replo, GemPages, Zipify. Upsell + CRO: ReConvert, Rebuy, Fomo, Octane AI. Headless / Frontend: Hydrogen, Shogun Frontend. ### Modes - `discover_by_domain_list` - run the full intel pass on every input domain. - `detect_shopify_only` - lightweight is-Shopify boolean only (cheapest). - `deep_analyze` - `discover_by_domain_list` plus full `/products.json` walk and revenue estimate. ### Input See `.actor/INPUT_SCHEMA.json`. Sample - find non-Klaviyo Shopify stores doing 50-1000 products, $50K+ MRR: ```json { "mode": "deep_analyze", "domains": ["allbirds.com", "rothys.com", "warbyparker.com"], "excluded_apps": ["klaviyo"], "min_product_count": 50, "max_product_count": 1000, "min_estimated_monthly_revenue_usd": 50000, "concurrency": 4, "use_apify_proxy": true, "apify_proxy_groups": ["RESIDENTIAL"] } ```` ### Output **Sample output:** [`.actor/sample-output.json`](./.actor/sample-output.json) — copy-paste-ready preview of real-looking records. First record inline: ```json { "domain": "luminouswick.co", "store_url": "https://luminouswick.co", "is_shopify": true, "shopify_plan_hint": { "plan": "shopify", "source": "X-ShopId header pattern" }, "store_name": "Luminous Wick \u2014 Hand-Poured Soy Candles", "homepage_title": "Luminous Wick | Small-Batch Soy Candles & Refills", "homepage_description": "Hand-poured in Brooklyn. Coconut-soy wax, cotton wicks, fragrance-loaded. Shop scents, refill kits, and gift sets.", "currency": "USD", "primary_country": "US", "total_product_count": 84, "total_collections_count": 12, "avg_product_price": 38.4, "min_product_price": 14.0, "max_product_price": 168.0, "top_categories": [ "Candles", "Refill Kits", "Gift Sets", "Wax Melts", "Accessories" ], "recent_product_count_30d": 7, "has_subscriptions": true, "has_rewards_program": true, "has_quiz": true, "has_post_purchase_upsell": true, "apps_installed": [ { "app_id": "klaviyo", "footprint_match": "static.klaviyo.com", "confidence": "high" }, { "app_id": "recharge", "footprint_match": "rechargepayments.com/shopify", "confidence": "high" }, { "app_id": "smile_io", "footprint_match": "cdn.smile.io", "confidence": "high" }, { "app_id": "octane_ai", "footprint_match": "cdn.octaneai.com/quiz-widget", "confidence": "high" }, { "app_id": "judgeme", "footprint_match": "judge.me/widget", "confidence": "high" }, { "app_id": "yotpo", "footprint_match": "staticw2.yotpo.com", "confidence": "medium" }, { "app_id": "rebuy", "footprint_match": "rebuyengine.com", "confidence": "high" }, { "app_id": "gorgias", "footprint_match": "config.gorgias.chat", "confidence": "high" }, { "app_id": "tapcart", "footprint_match": "open.tapcart.com", "confidence": "medium" } ], "apps_count": 9, "estimated_monthly_revenue_usd": { "low": 180000, "high": 320000, "midpoint": 250000 }, "revenue_estimate_method": "product_count * avg_price * estimated_orders/day band", "social_links": { "instagram": "https://www.instagram.com/luminouswickco", "facebook": "https://www.facebook.com/luminouswickco", "tiktok": "https://www.tiktok.com/@luminouswick", "twitter": null, "youtube": null, "pinterest": "https://www.pinterest.com/luminouswickco", "linkedin": null }, "contact_email": "hello@luminouswick.co", "contact_phone": "(718) 555-0184", "theme_name": "Impulse", "theme_version": "7.4.2", "language": "en", "scraped_at": "2026-05-13T16:02:14Z", "mode": "domain_scan", "available": true, "reason": null } ``` Sample record: ```json { "domain": "example.com", "store_url": "https://example.com", "is_shopify": true, "shopify_plan_hint": {"plan": "shopify", "source": "headers"}, "store_name": "Example Co", "currency": "USD", "primary_country": "US", "total_product_count": 187, "avg_product_price": 64.50, "apps_installed": [ {"app_id": "klaviyo", "footprint_match": "static.klaviyo.com", "confidence": "high"}, {"app_id": "recharge", "footprint_match": "rechargepayments.com", "confidence": "high"} ], "apps_count": 6, "estimated_monthly_revenue_usd": {"low": 60000, "midpoint": 120000, "high": 240000}, "theme_name": "Dawn", "available": true, "scraped_at": "2026-05-14T12:00:00Z" } ``` Non-Shopify rows include `is_shopify: false` and the detection reason; filtered-out rows are not emitted. ### Pricing Pay-per-event: | Event | When | Price | |---|---|---| | `store_record` | Verified Shopify store with metadata | $0.008 | | `app_enrichment` | 3+ apps detected | $0.005 | | `contact_enrichment` | At least one email or phone extracted from /contact /about | $0.005 | | `deep_analysis` | Surcharge in `deep_analyze` mode | $0.010 | Worst case (deep\_analyze, 5+ apps, contact extracted): $0.028 per store. Cheapest (detect\_shopify\_only, <3 apps, no contact): $0.008. Contact enrichment is only billed when data is actually returned, so misses cost nothing. ### FAQ **Q: Why is `shopify_plan_hint` often null?** A: Shopify hides plan info. We can sometimes spot `shopify-plus` references in HTML or `Powered-By` headers; otherwise plan is null. **Q: How accurate is the revenue estimate?** A: A rough heuristic - expect +/- 50% error on absolute MRR. The wedge is relative ranking ("under $10K/mo or over $500K/mo"), not precision. Treat it as a defensible signal, not a financial figure. **Q: Do I need a residential proxy?** A: Recommended. Many Shopify stores are behind Cloudflare; we use `curl_cffi` with Chrome 131 impersonation, which gets through plain CF challenges, but RESIDENTIAL proxies improve consistency. **Q: How do server-side filters affect billing?** A: Filtered-out and non-Shopify rows are NEVER charged. You only pay for stores that match your input criteria. ### Support Open an issue on the actor's GitHub or contact via Apify Store. Include the run ID and input config. ### Changelog See [CHANGELOG.md](./CHANGELOG.md). # Actor input Schema ## `mode` (type: `string`): discover\_by\_domain\_list = check each provided domain. detect\_shopify\_only = cheapest path, just verify Shopify and return basic metadata. deep\_analyze = full /products.json walk + revenue estimate + collections + apps (most expensive, most thorough). ## `domains` (type: `array`): List of root domains or URLs to check (e.g. 'allbirds.com', 'https://www.warbyparker.com', 'fashionnova.com'). Strip 'www.' / scheme / paths — the actor will normalize. ## `discovery_seed_urls` (type: `array`): URLs to crawl for outbound links — e.g. 'powered by Shopify' directory pages, niche listicles, awards lists. Outbound links become candidate domains. ## `required_apps` (type: `array`): Only emit stores that have ALL of these apps detected. Leave empty to skip. Allowed values: klaviyo, recharge, yotpo, gorgias, postscript, loop, smile\_io, bold, stamped, judge\_me, okendo, octane\_ai, tidio, drift, klevu, searchanise, algolia, shogun, pagefly, replo, loox, reviews\_io, fomo, privy, justuno, nosto, rebuy, limespot, wiser, reconvert, zipify, gempages. ## `excluded_apps` (type: `array`): Drop stores that have ANY of these apps installed. Useful to find non-customers (e.g. exclude 'klaviyo' to surface non-Klaviyo Shopify stores). Allowed values: same enum as required\_apps. ## `min_product_count` (type: `integer`): Drop stores with fewer than N products. Set to 0 to disable. ## `max_product_count` (type: `integer`): Drop stores with more than N products. Set to 0 to disable. ## `min_estimated_monthly_revenue_usd` (type: `integer`): Drop stores whose estimated monthly revenue midpoint is below this. Rough heuristic - see README. Set to 0 to disable. ## `max_estimated_monthly_revenue_usd` (type: `integer`): Drop stores whose estimated monthly revenue midpoint is above this. Set to 0 to disable. ## `country_codes` (type: `array`): Restrict to stores whose detected primary country (from currency / shipping signals) is in this list. Empty = no filter. Example: \['US', 'CA', 'GB']. ## `category_keywords` (type: `array`): Keyword filter on store homepage title + description. Case-insensitive substring match. Example: \['beauty', 'skincare', 'fashion']. ## `concurrency` (type: `integer`): Parallel domain fetches. Shopify rate-limits aggressively; 6 is the recommended sweet spot. ## `use_apify_proxy` (type: `boolean`): Route requests through Apify Proxy. RESIDENTIAL is strongly recommended - many Shopify stores sit behind Cloudflare. ## `apify_proxy_groups` (type: `array`): Apify Proxy groups. RESIDENTIAL is the most reliable for Shopify. ## `apify_proxy_country` (type: `string`): Two-letter country code for proxy egress. 'US' is a safe default since most Shopify stores ship to US. ## `max_results` (type: `integer`): Cap on emitted records. Default 200. Increase for larger discovery runs. ## `include_contact_enrichment` (type: `boolean`): Scrape /contact /pages/contact /about for email addresses (founder@, support@, hello@, sales@) and phone numbers. Adds the highest-impact field for D2C SaaS sales outreach. Charged $0.005 per store ONLY when at least one email or phone is actually extracted. ## `include_founder_intel` (type: `boolean`): Scrape /about /pages/our-story for founder names, founding year, and brand-story keywords (vegan, sustainable, made in USA, woman-owned, etc). Useful for sales-outreach personalization. Slower because of extra page fetches; opt-in. ## Actor input object example ```json { "mode": "discover_by_domain_list", "domains": [ "allbirds.com", "warbyparker.com", "fashionnova.com", "gymshark.com", "bombas.com" ], "min_product_count": 0, "max_product_count": 0, "min_estimated_monthly_revenue_usd": 0, "max_estimated_monthly_revenue_usd": 0, "concurrency": 6, "use_apify_proxy": true, "apify_proxy_groups": [ "RESIDENTIAL" ], "apify_proxy_country": "US", "max_results": 200, "include_contact_enrichment": true, "include_founder_intel": false } ``` # Actor output Schema ## `datasetItems` (type: `string`): Narrow, token-efficient slice of every record. Consumer: LLM agents (Claude, GPT, LangChain tools), MCP hosts, dashboards. Store fields: domain, Shopify Plus flag, store name, product count, app count, monthly revenue estimate, contact email. ## `datasetItemsDetailed` (type: `string`): All fields for every record. Consumer: humans browsing the dataset in the Apify UI, RAG ingest pipelines, and full backups. Larger payload — not recommended as a direct LLM tool response. ## `datasetItemsUnwind` (type: `string`): Same records, but each element of the `apps` array is promoted to its own row. Consumer: Zapier / Make / n8n / Google Sheets users who want one row per item, and LLM agents that prefer flat rows over nested arrays. ## `datasetItemsMcp` (type: `string`): First 50 overview records as a clean JSON array. Wrap on the agent side in an MCP tool-call response envelope, e.g. `{ "ok": true, "data": , "meta": { "actor": "shopify-store-discovery", "count": , "view": "overview" } }`. Consumer: MCP servers, Claude Desktop, Cursor, OpenAI Assistants tool calls. ## `datasetItemsCsv` (type: `string`): Spreadsheet-friendly export of the overview view. Consumer: humans, sales-ops teams, Excel / Google Sheets users. # 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 = { "mode": "discover_by_domain_list", "domains": [ "allbirds.com", "warbyparker.com", "fashionnova.com", "gymshark.com", "bombas.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/shopify-store-discovery").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "mode": "discover_by_domain_list", "domains": [ "allbirds.com", "warbyparker.com", "fashionnova.com", "gymshark.com", "bombas.com", ], } # Run the Actor and wait for it to finish run = client.actor("seibs.co/shopify-store-discovery").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "discover_by_domain_list", "domains": [ "allbirds.com", "warbyparker.com", "fashionnova.com", "gymshark.com", "bombas.com" ] }' | apify call seibs.co/shopify-store-discovery --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/shopify-store-discovery", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Shopify Store Discovery - Apps, Revenue Estimate, Tech Stack", "description": "Find Shopify stores by domain list with full intel: 30+ app detection (Klaviyo/Recharge/Yotpo/Gorgias/etc), product count, revenue estimate range, theme, social links. Server-side filter by required/excluded apps + revenue range. For D2C SaaS sales teams.", "version": "0.3", "x-build-id": "ZXKf0GmaH7e4EAg9e" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~shopify-store-discovery/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-shopify-store-discovery", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seibs.co~shopify-store-discovery/runs": { "post": { "operationId": "runs-sync-seibs.co-shopify-store-discovery", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seibs.co~shopify-store-discovery/run-sync": { "post": { "operationId": "run-sync-seibs.co-shopify-store-discovery", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "discover_by_domain_list", "detect_shopify_only", "deep_analyze" ], "type": "string", "description": "discover_by_domain_list = check each provided domain. detect_shopify_only = cheapest path, just verify Shopify and return basic metadata. deep_analyze = full /products.json walk + revenue estimate + collections + apps (most expensive, most thorough).", "default": "discover_by_domain_list" }, "domains": { "title": "Domains to check", "type": "array", "description": "List of root domains or URLs to check (e.g. 'allbirds.com', 'https://www.warbyparker.com', 'fashionnova.com'). Strip 'www.' / scheme / paths — the actor will normalize.", "items": { "type": "string" } }, "discovery_seed_urls": { "title": "Discovery seed URLs (optional)", "type": "array", "description": "URLs to crawl for outbound links — e.g. 'powered by Shopify' directory pages, niche listicles, awards lists. Outbound links become candidate domains.", "items": { "type": "string" } }, "required_apps": { "title": "Required apps (AND filter)", "uniqueItems": true, "type": "array", "description": "Only emit stores that have ALL of these apps detected. Leave empty to skip. Allowed values: klaviyo, recharge, yotpo, gorgias, postscript, loop, smile_io, bold, stamped, judge_me, okendo, octane_ai, tidio, drift, klevu, searchanise, algolia, shogun, pagefly, replo, loox, reviews_io, fomo, privy, justuno, nosto, rebuy, limespot, wiser, reconvert, zipify, gempages.", "items": { "type": "string" } }, "excluded_apps": { "title": "Excluded apps (NOT filter)", "uniqueItems": true, "type": "array", "description": "Drop stores that have ANY of these apps installed. Useful to find non-customers (e.g. exclude 'klaviyo' to surface non-Klaviyo Shopify stores). Allowed values: same enum as required_apps.", "items": { "type": "string" } }, "min_product_count": { "title": "Minimum product count", "minimum": 0, "type": "integer", "description": "Drop stores with fewer than N products. Set to 0 to disable.", "default": 0 }, "max_product_count": { "title": "Maximum product count", "minimum": 0, "type": "integer", "description": "Drop stores with more than N products. Set to 0 to disable.", "default": 0 }, "min_estimated_monthly_revenue_usd": { "title": "Minimum estimated monthly revenue (USD)", "minimum": 0, "type": "integer", "description": "Drop stores whose estimated monthly revenue midpoint is below this. Rough heuristic - see README. Set to 0 to disable.", "default": 0 }, "max_estimated_monthly_revenue_usd": { "title": "Maximum estimated monthly revenue (USD)", "minimum": 0, "type": "integer", "description": "Drop stores whose estimated monthly revenue midpoint is above this. Set to 0 to disable.", "default": 0 }, "country_codes": { "title": "Country codes (ISO 2-letter)", "type": "array", "description": "Restrict to stores whose detected primary country (from currency / shipping signals) is in this list. Empty = no filter. Example: ['US', 'CA', 'GB'].", "items": { "type": "string" } }, "category_keywords": { "title": "Category keywords", "type": "array", "description": "Keyword filter on store homepage title + description. Case-insensitive substring match. Example: ['beauty', 'skincare', 'fashion'].", "items": { "type": "string" } }, "concurrency": { "title": "Max concurrent fetches", "minimum": 1, "maximum": 8, "type": "integer", "description": "Parallel domain fetches. Shopify rate-limits aggressively; 6 is the recommended sweet spot.", "default": 6 }, "use_apify_proxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route requests through Apify Proxy. RESIDENTIAL is strongly recommended - many Shopify stores sit behind Cloudflare.", "default": true }, "apify_proxy_groups": { "title": "Proxy groups", "type": "array", "description": "Apify Proxy groups. RESIDENTIAL is the most reliable for Shopify.", "default": [ "RESIDENTIAL" ], "items": { "type": "string" } }, "apify_proxy_country": { "title": "Proxy country (optional)", "type": "string", "description": "Two-letter country code for proxy egress. 'US' is a safe default since most Shopify stores ship to US.", "default": "US" }, "max_results": { "title": "Max results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Cap on emitted records. Default 200. Increase for larger discovery runs.", "default": 200 }, "include_contact_enrichment": { "title": "Include contact enrichment (emails + phones)", "type": "boolean", "description": "Scrape /contact /pages/contact /about for email addresses (founder@, support@, hello@, sales@) and phone numbers. Adds the highest-impact field for D2C SaaS sales outreach. Charged $0.005 per store ONLY when at least one email or phone is actually extracted.", "default": true }, "include_founder_intel": { "title": "Include founder + brand-story intel (slower)", "type": "boolean", "description": "Scrape /about /pages/our-story for founder names, founding year, and brand-story keywords (vegan, sustainable, made in USA, woman-owned, etc). Useful for sales-outreach personalization. Slower because of extra page fetches; opt-in.", "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 } } } } } } } } } } ```