# Shopify Store Leads - Emails, Size & Activity (`gganbukim/shopify-store-leads`) Actor Turn a domain list into qualified Shopify leads. Returns contact email, phone and socials, plus what decides whether a store is worth approaching: catalogue size, price band, discount depth, stock health, and how recently it launched anything. One row per store; filtered stores are free. - **URL**: https://apify.com/gganbukim/shopify-store-leads.md - **Developed by:** [DONGMIN KIM](https://apify.com/gganbukim) (community) - **Categories:** Lead generation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 qualified leads 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/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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 Leads — Contact Details Plus the Numbers That Qualify a Store ![Shopify Store Leads — Contact Details Plus the Numbers That Qualify a Store](https://raw.githubusercontent.com/gganbukim1/apify-actor-images/master/cards/shopify-store-leads.png) Paste a list of domains. Get back **one row per store**: who to email, and whether the store is worth emailing. Most contact scrapers stop at the address. The problem with a list of ten thousand addresses is that most of them belong to shops with eleven products, no sale in two years, and nothing to spend. This one reads the storefront the same way a buyer would — how big is the catalogue, what does it charge, how hard is it discounting, how much is out of stock, and **when did it last launch anything** — and ships those as fields you can filter on before you write a single email. Works on any Shopify store. No API key, no login, no store password. ### What it does well - **Contact details** — email, phone and Instagram/Facebook/TikTok/X/YouTube/Pinterest/LinkedIn accounts, from the home, contact and about pages. - **Qualification, not just contacts** — catalogue size, median price, discount depth, out-of-stock rate, and new products in the last 30 and 90 days. - **Two plain-language bands** — `sizeBand` and `activityBand`, so a ten-thousand-row list sorts itself without you writing rules. - **Filters run before billing** — require an email, a minimum catalogue, or a launch in the last N days, and **the stores you drop cost nothing**. - **Confirms Shopify first** — a mixed prospect list does not waste requests on WordPress sites. ### Input ```jsonc { "storeUrls": ["allbirds.com", "gymshark.com", "prospect-three.com"], "requireEmail": true, "minProducts": 25, "activeWithinDays": 90 } ``` #### Every option The same wording you see in the Apify console, with the JSON key for API and MCP callers. | Option | What it does | Default | |---|---|---| | **Store domains** — `storeUrls` *(required)* | Bare domains or any URL on the store. Paste a whole prospect list; each domain becomes one row. | — | | **Find contact details** — `includeContacts` | Read the store's home, contact and about pages for emails, phone numbers and social accounts. Stops as soon as it has both an email and a social account. | `true` | | **Max products scanned per store** — `maxProductsScanned` | How much of the catalogue to read before judging size and activity. None of it is written as rows — this is a request budget, not a row budget. | `500` | | **Only keep stores with an email** — `requireEmail` | Drop stores where no contact email could be found. Dropped stores are not billed. | `false` | | **Minimum products** — `minProducts` | Drop stores smaller than this. 0 disables. | `0` | | **Launched something within (days)** — `activeWithinDays` | Drop stores whose newest product is older than this. 0 disables. | `0` | | **Skip non-Shopify domains** — `skipNonShopify` | Check each domain is Shopify before qualifying it. | `true` | | **Concurrency** — `concurrency` | Stores processed in parallel. | `3` | | **Proxy** — `proxyConfiguration` | Leave the default. The actor starts on cheap datacenter proxies and escalates only for stores that throttle. | `{"useApifyProxy":true}` | ### Output One row per qualified store. ```json { "storeDomain": "allbirds.com", "url": "https://allbirds.com", "isShopify": true, "themeName": "DNAM Theme", "currency": "USD", "productCount": 291, "sizeBand": "medium", "activityBand": "active", "vendorCount": 1, "productTypeCount": 3, "minPrice": 3, "maxPrice": 160, "medianPrice": 68, "onSaleCount": 155, "onSalePercent": 53, "averageDiscountPercent": 50, "outOfStockCount": 43, "outOfStockPercent": 15, "newProductsLast30Days": 12, "newProductsLast90Days": 34, "daysSinceNewestProduct": 3.2, "catalogueAgeDays": 1840, "email": "help@allbirds.com", "emails": ["help@allbirds.com", "press@allbirds.com"], "phone": "+18885634387", "instagram": "allbirds", "facebook": "weareallbirds", "tiktok": "allbirds", "contactPageUrl": "https://allbirds.com/pages/contact", "scrapedAt": "2026-08-20T09:14:02.113Z" } ``` #### Every field You are billed per lead delivered, so here is everything a row can contain. A field is absent when the store does not publish it. **Who to contact** | Field | What it is | |---|---| | `email` | The best single address found. Addresses on the store's own domain rank above a free-mail one, and role addresses (`info@`, `hello@`, `sales@`) above personal ones. `no-reply@` is ranked last, never first. | | `emails` | Every address found, in that same order. | | `emailSource` | `mailto` when the first address came from a link somebody published to be written to, `text` when it only matched in the page. A `text` address is worth a second look. | | `phone` / `phones` | Numbers from `tel:` links, digits only. Anything under seven digits is treated as an extension, not a number. | | `instagram`, `facebook`, `tiktok`, `twitter`, `youtube`, `pinterest`, `linkedin` | The store's handle on each network, when it links one. Share buttons and network furniture are excluded. | | `contactPageUrl` | Which page the details came from, when it was not the homepage. | **Whether to contact them** | Field | What it is | |---|---| | `sizeBand` | `empty` · `micro` (<25) · `small` (<150) · `medium` (<750) · `large`. The one field to sort a big list by. On a capped scan this is the **floor** — a scan that stopped at 250 proves at least `medium` and cannot rule out `large`. | | `activityBand` | `active` (launched within 30 days) · `slowing` (90) · `dormant` (a year) · `stale` · `unknown`. **The strongest single signal that a shop is still trading.** | | `productCount` | Products seen. | | `productCountCapped` | `true` when the catalogue was larger than **Max products scanned** — so `productCount` is a floor, not a count. | | `launchCountsAreFloors` | `true` in the same case. `/products.json` returns newest first, so a capped scan sees a recent slice: the launch counts below are minimums. `catalogueAgeDays` is then withheld entirely rather than guessed, because the oldest product in a recent slice is not the oldest product in the shop. | | `daysSinceNewestProduct` | Days since the newest product **record was created**. | | `daysSinceLastPublished` | Days since anything was last **made visible** on the storefront. A bulk republish moves this and not the one above. | | `daysSinceAnyActivity` | The more recent of those two — the last sign somebody was at the wheel. This is what `activityBand` reads. All three are safe on a capped scan: the true values can only be smaller. | | `newProductsLast30Days` / `newProductsLast90Days` | Launch cadence, which is what separates a growing shop from a parked one. Counted from when a product was **created**, not when it was published — see the note below. | | `catalogueAgeDays` | Age of the oldest product — roughly how long the shop has been trading. Absent when the scan was capped. | | `vendorCount` / `productTypeCount` | Whether it is a single brand or a marketplace-style reseller. | | `minPrice` / `maxPrice` / `medianPrice` | Price band in the store's own currency. Median, not average, because one $4,000 outlier should not move it. | | `currency` | The store's active currency. | | `onSaleCount` / `onSalePercent` | How much of the catalogue is marked down. | | `averageDiscountPercent` | How deep those markdowns go. Heavy, permanent discounting is a margin signal. | | `outOfStockCount` / `outOfStockPercent` | Stock health. A high rate can mean demand, or it can mean a supply problem — read it with `activityBand`. | **Housekeeping** | Field | What it is | |---|---| | `storeDomain` / `url` | The store, for joining back to your list. | | `isShopify` | Always `true` unless you turned off **Skip non-Shopify domains**. | | `themeName` | The Shopify theme, when the storefront exposes it. | | `scrapedAt` | When this run read the store. | #### Why there are three date fields instead of one Shopify puts two timestamps on a product, and **neither one means "launched"**. They fail in opposite directions, so this Actor reports both and derives the band from the pair. Measured on real stores while building this: - **`published_at` is a visibility stamp a bulk republish resets.** gymshark.com: 500 products created between 2021 and 2026, every one published inside the same three weeks. allbirds.com: the gap between creation and publication has a median of **617 days**, with the whole catalogue published within days of each other. Read alone, one admin action looks like explosive growth. - **`created_at` misses shops that refresh instead of adding.** allbirds.com has not created a new product record in **196 days** and is obviously still trading — it updates existing records with new colourways. Read alone, a healthy shop looks abandoned. So `newProductsLast30Days` counts **creations**, because a republish is not a launch. And `activityBand` reads `daysSinceAnyActivity` — the more recent of the two — because either one means somebody is still administering the store. A shop where both are stale is the one that is actually gone. The catalogue Actor exposes both dates raw, and the new-arrivals monitor keys on `published_at`, because "newly visible to customers" is genuinely the right question there. ### Who this is for - **Agencies and freelancers** selling design, CRO, email or ads to Shopify merchants — `sizeBand` and `activityBand` tell you who can afford you and who is still trading. - **Suppliers and 3PLs** looking for shops of the right size in the right price band. - **App and SaaS founders** on Shopify, building a launch list that is not mostly dead stores. - **Anyone who bought a list** and needs to know how much of it is real before working it. ### What it does not do It finds addresses a store **publishes**. It does not guess `firstname.lastname@` patterns, buy from a contact database, or verify that an address accepts mail. Everything in a row came off the storefront on the day of the run. ### Common uses - **Qualify a bought list** — run 10,000 domains, keep the ones with an email and a launch in the last 90 days, discard the rest for free. - **Territory sizing** — median price and catalogue size across a segment, before pitching it. - **Trigger-based outreach** — schedule it and approach stores whose `activityBand` just moved to `active`. - **Competitive mapping** — the same numbers for every shop in your category, in one table. ### Pricing Pay per **lead delivered** — $5.00 per 1,000. Stores removed by your filters, stores that are not Shopify, and stores that fail **cost nothing**, which is what makes it safe to point at a list you have not cleaned. Starting a run costs $0.00001 — the platform's $0.00001 minimum, charged once per GB of memory, and these Actors run on 512 MB. Scanning is the expensive part and you are not charged for it: a store read across nine requests that then fails your email filter costs you nothing at all. ### Other Actors in this family Same engines, same billing, no account or API key on any of them. **YouTube & video** - [YouTube Scraper — No API Key, Any URL or Search](https://apify.com/gganbukim/youtube-scraper) — Any YouTube URL or search term in, videos out — with subtitles, comments and sponsor deals as add-ons. - [Download YouTube Subtitles in Bulk — SRT, VTT & Text](https://apify.com/gganbukim/youtube-transcript-scraper) — Bulk subtitles from videos, channels or playlists — text, SRT, VTT or RAG chunks. - [Export YouTube Comments to CSV — Replies and Likes](https://apify.com/gganbukim/youtube-comments-scraper) — Every comment and reply thread, with likes, authors and creator flags. - [List Every Video on a YouTube Channel — Export to CSV](https://apify.com/gganbukim/youtube-channel-scraper) — A channel's whole back catalogue plus a subscriber and RSS summary row. - [Find YouTube Sponsors — Brand Deals, Codes & Links](https://apify.com/gganbukim/youtube-sponsorship-finder) — Which brands pay which creators, with the campaign link, the code and the timestamp. - [YouTube Search API — Bulk Results, No Quota](https://apify.com/gganbukim/youtube-search-scraper) — Many search terms at once, every result as a row, filtered before you are billed. - [Track Deleted YouTube Videos & Title Changes](https://apify.com/gganbukim/youtube-channel-monitor) — What a channel quietly changed: deleted videos, rewritten titles, view velocity. - [YouTube Creator Email Finder & Sponsor Lookup](https://apify.com/gganbukim/youtube-creator-leads) — A channel list into leads: the published email, audience bands, and who already sponsors them. - [Export a YouTube Playlist to CSV — Every Video](https://apify.com/gganbukim/youtube-playlist-scraper) — Any playlist as a table, with each video position in it. **Search demand** - [AnswerThePublic Alternative — Autocomplete Keyword API](https://apify.com/gganbukim/long-tail-keyword-scraper) — One seed into hundreds of real keywords from Google, YouTube and Amazon autocomplete. - [Google Trends API — Today's Trending Searches, No Key](https://apify.com/gganbukim/google-trends-scraper) — Today's trending searches by country, with traffic bands and the news behind them. **E-commerce** - [Export Any Shopify Store's Products to CSV or JSON](https://apify.com/gganbukim/shopify-product-scraper) — Any Shopify catalogue: variants, SKUs, live prices, stock, images, collections. - [New Shopify Product Alerts — Competitor Drop Tracker](https://apify.com/gganbukim/shopify-new-arrivals-monitor) — Only what a store launched since the last run. Scanning is free. - [Website Tech Stack & Email Finder for B2B Lists](https://apify.com/gganbukim/website-leads-scraper) — Any domain list into leads: contact email, what the site runs on, and the marketing tags it carries. **Hiring** - [Greenhouse, Lever & Ashby Job Scraper — No API Key](https://apify.com/gganbukim/ats-job-scraper) — Paste a company domain, get its open roles from Greenhouse, Ashby, Lever or SmartRecruiters. - [Ghost Job Detector — Track Reposts, Closures & Edits](https://apify.com/gganbukim/job-lifecycle-monitor) — What changed on a careers page: opened, closed, quietly reposted, or a ghost job. ### Run it from code Nothing here needs a login to the source, only your Apify token. **HTTP** — start a run and wait for the rows: ```bash curl -X POST "https://api.apify.com/v2/acts/gganbukim~shopify-store-leads/run-sync-get-dataset-items?token=$APIFY_TOKEN" \ -H "content-type: application/json" \ -d @input.json ``` **JavaScript** ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('gganbukim/shopify-store-leads').call(input); const { items } = await client.dataset(run.defaultDatasetId).listItems(); ``` **Python** ```python from apify_client import ApifyClient client = ApifyClient(os.environ["APIFY_TOKEN"]) run = client.actor("gganbukim/shopify-store-leads").call(run_input=input) items = client.dataset(run["defaultDatasetId"]).list_items().items ``` **Scheduled or event-driven** — attach a [schedule](https://docs.apify.com/platform/schedules) to run it on a cron, or a [webhook](https://docs.apify.com/platform/integrations/webhooks) to push each finished run into your own endpoint. It also connects through Apify's [Zapier, Make, n8n and LangChain integrations](https://docs.apify.com/platform/integrations), and is reachable from an [MCP server](https://docs.apify.com/platform/integrations/mcp) if you are driving it from an agent. **Standby / API mode** — the run above is synchronous: one call in, rows out, no polling. That is the shape to use if you are calling this per request rather than in a batch. ### Errors, limits and what you are charged for - **You pay for delivered rows only.** A row your filters removed, a page that failed, a retry — none of it is billed. Starting a run costs $0.00001: the platform minimum, charged once per gigabyte, and this Actor runs on 512 MB. - **A run that delivers nothing still costs the start fee and nothing else.** If the input resolved to zero items, the run fails loudly with the reason rather than finishing green on an empty dataset. - **Blocking is handled by changing address, not by waiting.** The Actor starts on cheap datacenter proxies and moves up only after a tier has actually been refused several times in a row, then drops back down once the cheap tier answers cleanly again. You are not paying for residential bandwidth that was never needed. - **Rate limits belong to the source, not to this Actor.** Very large inputs are worked through in batches; the run reports how many items succeeded, were filtered, and failed, so a partial result is never presented as a complete one. - **Dataset retention follows your Apify plan.** Export what you need, or push it out with a webhook, if you want it past that window. ### Is this legal? This Actor reads pages and public endpoints that anyone can open in a browser without an account. It does not log in, does not defeat a paywall, and does not touch anything behind authentication. Scraping public data is broadly lawful in the US and the EU, and courts have repeatedly said so — but "public" is not the same as "unrestricted", and what you may then *do* with the data is a separate question from whether you may collect it. Personal data pulls in the GDPR and similar regimes whatever the source, so if your rows contain people, you need a lawful basis for keeping them. Apify publishes a fuller treatment in [Is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/) and an [ethical scraping guide](https://docs.apify.com/academy/web-scraping-for-beginners/crawling/scraping-ethics). None of this is legal advice; if the use is commercial and the data is personal, ask someone qualified. ### Something wrong, or missing? Open an issue on the [Actor's Issues tab](https://apify.com/gganbukim/shopify-store-leads/issues) — it goes straight to the developer and is the fastest route. Include the run ID; it carries the input and the log, which is usually enough to reproduce the problem without another round trip. Sources change without warning, and a field that quietly goes null is worth reporting even if the run succeeded. A broken parser looks exactly like a quiet day in the data until someone says so. ### FAQ **Is it legal to collect business contact details this way?** This reads pages the store publishes publicly, with no login and nothing bypassed — a shop that puts `hello@` in its footer is asking to be contacted there. Business contact details are treated differently from personal data in most regimes, but **how you use them is regulated**: GDPR, CAN-SPAM, PECR and their equivalents govern marketing email regardless of how the address was obtained. Each store's own terms are a separate contract question. Not legal advice. **Will I get blocked?** Rarely. This reads public storefront pages and the same `/products.json` endpoint Shopify serves on every shop, on cheap datacenter proxies, escalating only for the minority of stores behind a WAF. **How much does 1,000 leads cost?** $5.00, plus $0.00002 for the run. Filtered and failed stores are free, so a 10,000-domain list where 2,000 pass your filters costs $10. **Why one row per store instead of per contact?** Because the decision you are making is per store. A shop with four published addresses is not four leads. **Can I export the results to Excel or Google Sheets?** Yes. Every run's dataset downloads as CSV, Excel, JSON, XML or RSS from the Storage tab, or straight from the API if you want a live link a spreadsheet can pull. **Can I connect it to Zapier, Make or n8n?** Yes — Apify publishes integrations for all three, plus webhooks that fire when a run finishes. A common setup is a schedule here and a webhook into your CRM. **Do I need to write code?** No. Fill the form in the console and press Start. If you do want code, the Apify client libraries for Python and JavaScript call this the same way, and it is available over MCP so an AI agent can call it directly. **Can I run it on a schedule?** Yes, via Apify Schedules, webhooks, or the API. # Actor input Schema ## `storeUrls` (type: `array`): Bare domains or any URL on the store — gymshark.com, https://allbirds.com/collections/mens, shop.example.co.uk. Paste a whole prospect list; each domain becomes one row. ## `includeContacts` (type: `boolean`): Read the store's home, contact and about pages for emails, phone numbers and social accounts. Costs up to six cheap requests per store and stops as soon as it has both an email and a social account. ## `maxProductsScanned` (type: `integer`): How much of the catalogue to read before judging size and activity. Products arrive 250 per request, and none of them are written as rows — this is a request budget, not a row budget. 500 is enough to band almost any store. ## `requireEmail` (type: `boolean`): Drop stores where no contact email could be found. Dropped stores are not billed. ## `minProducts` (type: `integer`): Drop stores smaller than this. 0 disables. Useful for skipping abandoned or placeholder shops. ## `activeWithinDays` (type: `integer`): Drop stores whose newest product is older than this. 0 disables. This is the strongest single signal that a shop is still trading. ## `skipNonShopify` (type: `boolean`): Check each domain is Shopify before qualifying it. Costs one cheap request per store and avoids wasted work on a mixed list. ## `concurrency` (type: `integer`): Stores processed in parallel. ## `proxyConfiguration` (type: `object`): Leave the default. A minority of stores sit behind a WAF that throttles datacenter IPs; the actor starts cheap and escalates to residential only for the stores that need it. ## Actor input object example ```json { "storeUrls": [ "allbirds.com", "gymshark.com" ], "includeContacts": true, "maxProductsScanned": 500, "requireEmail": false, "minProducts": 0, "activeWithinDays": 0, "skipNonShopify": true, "concurrency": 3, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): One row per store that passed your filters: contact details plus the size, pricing and activity numbers that decide whether it is worth approaching. ## `runSummary` (type: `string`): Counts for this run: leads delivered, how many carried an email, stores filtered out, stores that were not Shopify, failures, and the proxy tier used. # 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 = { "storeUrls": [ "allbirds.com", "gymshark.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("gganbukim/shopify-store-leads").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 = { "storeUrls": [ "allbirds.com", "gymshark.com", ] } # Run the Actor and wait for it to finish run = client.actor("gganbukim/shopify-store-leads").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "storeUrls": [ "allbirds.com", "gymshark.com" ] }' | apify call gganbukim/shopify-store-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,gganbukim/shopify-store-leads" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/R0c9KEeBUeQlF3amE/builds/PytebzZwHZfW9cFX0/openapi.json