# Ecommerce Platform Market Share & Migration Scraper (`fanndev/ecommerce-platform-market-share-scraper`) Actor

Track ecommerce platform market share: live store counts for 110 platforms, quarterly growth back to 2019, stores by country, category, app, technology and theme, plus how many stores switch between platforms. Shopify, WooCommerce, BigCommerce, Wix and more.

- **URL**: https://apify.com/fanndev/ecommerce-platform-market-share-scraper.md
- **Developed by:** [Faisal Ahdan naufal](https://apify.com/fanndev) (community)
- **Categories:** E-commerce, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Ecommerce Platform Market Share & Migration Scraper

How many live stores does Shopify have this quarter? How fast is WooCommerce growing? How many stores left Wix for Shopify? This Actor turns the public platform reports at Store Leads into rows you can chart, compare and track - for **110 ecommerce platforms**, back to 2019.

### Why use this actor

- **110 platforms, one schema** - Shopify, WooCommerce, BigCommerce, Wix, Squarespace, Magento, Shopware, PrestaShop, Cafe24, Ecwid, Demandware and 99 more.
- **Seven years of quarterly history** in one run - the store-count series starts in 2019 Q1.
- **Migration flows both ways** - how many stores switched *to* a platform and *away from* it, broken down by the other platform.
- **Deep breakdowns** - stores by country, category, app, technology, theme, shipping carrier, top-level domain, employee count, product count, social media presence and published contact details.
- **Only public data.** The per-store database behind the publisher's paid account is not touched; what you get is exactly what the public reports publish, including their own "top stores" and "new stores" lists.
- **The in-progress quarter is flagged**, so a partial quarter never looks like a decline in your chart.

### How it works

1. Pick a mode and one or more platform slugs (`shopify`, `woocommerce`, ...), or set `allPlatforms` for the whole market.
2. The Actor reads each platform's published report page.
3. It parses the report's tables and embedded data into flat rows, parsing counts into real numbers and attaching machine codes (`US` next to `United States`) where the report publishes them.
4. Rows stream into your dataset for JSON, CSV or Excel export.

### Input

```json
{
    "mode": "platform",
    "platforms": ["shopify", "woocommerce", "bigcommerce"],
    "maxItems": 1000
}
```

| Field | Type | Description |
|---|---|---|
| `mode` | string | `platform`, `growth`, `breakdown`, `migration`, `stores` or `reference`. |
| `platform` / `platforms` | string / array | Platform slugs. A full report URL is accepted too. |
| `allPlatforms` | boolean | Process every published platform report (~110) instead of a list. |
| `dimension` / `dimensions` | string / array | Restrict `breakdown` to specific dimensions. |
| `maxItems` | integer | Row cap for the run. Default `1000`. |
| `maxConcurrency` | integer | Reports fetched in parallel. Default `4`. |
| `proxyConfiguration` | object | Optional; not needed. |

#### Example inputs

Rank the whole market by live stores:

```json
{ "mode": "platform", "allPlatforms": true, "maxItems": 200 }
```

Chart Shopify vs WooCommerce since 2019:

```json
{ "mode": "growth", "platforms": ["shopify", "woocommerce"] }
```

Which countries and apps dominate Shopify:

```json
{ "mode": "breakdown", "platform": "shopify", "dimensions": ["country", "app"] }
```

Who is winning migrations:

```json
{ "mode": "migration", "platforms": ["shopify", "wix", "squarespace"] }
```

### Output

#### `PLATFORM` (platform mode)

```json
{
    "_input": "shopify",
    "recordType": "PLATFORM",
    "platform": "shopify",
    "platformName": "Shopify",
    "reportUrl": "https://storeleads.app/reports/shopify",
    "reportTitle": "The State of Shopify in 2026",
    "reportUpdated": "2026-09-11",
    "liveStores": 3077514,
    "quarterOverQuarterGrowthPct": 7.3,
    "quarterOverQuarterQuarter": "2026 Q2",
    "yearOverYearGrowthPct": 11,
    "latestQuarter": "2026 Q3",
    "latestQuarterIsPartial": true,
    "latestQuarterStores": 3077515,
    "quartersOfHistory": 31,
    "sectionsFound": ["growth", "socialmedia", "contactinfo", "topcategories", "topcountries", "topapps", "employees", "products", "toptechnologies", "shipping", "themes", "tlds", "topstores", "newstores", "windomains", "lossdomains"]
}
```

| Field | Type | Description |
|---|---|---|
| `liveStores` | integer | Live stores on the platform right now. |
| `quarterOverQuarterGrowthPct` / `yearOverYearGrowthPct` | number | Growth rates as the report publishes them. |
| `latestQuarterIsPartial` | boolean | Whether the newest quarter is still running. |
| `quartersOfHistory` | integer | Length of the growth series for that platform. |
| `sectionsFound` | array | Which sections carried data - smaller platforms publish fewer. |

#### `GROWTH` (growth mode)

```json
{ "recordType": "GROWTH", "platform": "shopify", "quarter": "2019 Q1", "activeStores": 753977, "isPartialQuarter": false }
{ "recordType": "GROWTH", "platform": "shopify", "quarter": "2026 Q3", "activeStores": 3077515, "isPartialQuarter": true }
```

31 rows for Shopify, 27 for WooCommerce - one per quarter since the publisher started counting.

#### `BREAKDOWN` (breakdown mode)

```json
{ "recordType": "BREAKDOWN", "platform": "shopify", "dimension": "country", "label": "United States", "code": "US", "stores": 1169447 }
{ "recordType": "BREAKDOWN", "platform": "shopify", "dimension": "app", "label": "Judge.me Product Reviews App", "stores": 412553 }
```

Dimensions: `country`, `category`, `app`, `technology`, `theme`, `tld`, `shipping-carrier`, `employee-count`, `product-count`, `social-media`, `contact-info`.

#### `MIGRATION` (migration mode)

```json
{ "recordType": "MIGRATION", "platform": "shopify", "direction": "switched-in", "otherPlatform": "WooCommerce", "stores": 8728 }
{ "recordType": "MIGRATION", "platform": "shopify", "direction": "switched-out", "otherPlatform": "WooCommerce", "stores": 6006 }
```

Both directions against the same platform, so net flow is a subtraction.

#### `STORE` (stores mode)

```json
{
    "recordType": "STORE",
    "platform": "shopify",
    "listType": "top",
    "name": "Barnes & Noble®",
    "domain": "www.barnesandnoble.com",
    "url": "https://www.barnesandnoble.com",
    "rank": 74,
    "created": "2016/12/30"
}
```

`listType` is `top` (highest-ranked stores on the platform) or `new` (recently created).

#### `AVAILABLE_REPORT` (reference mode)

```json
{ "recordType": "AVAILABLE_REPORT", "platform": "bigcartel", "reportUrl": "https://storeleads.app/reports/bigcartel" }
```

Run this first to get all 110 slugs.

#### Error rows

```json
{
    "recordType": "ERROR",
    "_input": "definitely-not-a-platform",
    "_error": "not_found",
    "_errorDetail": "no report published for 'definitely-not-a-platform'. Run mode 'reference' to list every available platform."
}
```

### What you can build with it

- **Market share dashboards** - one `platform` run with `allPlatforms`, refreshed monthly, ranks the entire ecommerce platform market by live stores and growth.
- **Competitive migration analysis** - net flow between two platforms, quarter after quarter.
- **App and technology adoption** - how many Shopify stores run a given review app, analytics tag or shipping carrier, and how that compares on BigCommerce.
- **Geographic expansion research** - which countries a platform is strongest in before you localise a product for it.
- **Prospect discovery** - the top and newest store lists give real domains with traffic ranks.

### Notes & limits

- **The reports update roughly weekly** - `reportUpdated` on every `PLATFORM` row tells you exactly when.
- **The newest quarter is partial.** It is flagged with `isPartialQuarter` / `latestQuarterIsPartial`; comparing it to a full quarter understates growth.
- **Breakdowns are top-N lists**, not exhaustive - the report publishes roughly the top 10-20 values per dimension.
- **Store lists are what the report publishes**, typically 10 top stores and 10 new stores per platform. The publisher's full store database is a paid product and this Actor does not access it.
- **Smaller platforms publish fewer sections.** `sectionsFound` shows which ones had data, so an empty breakdown is visible rather than mysterious.

### Scheduling tips

- `platform` with `allPlatforms`: weekly or monthly is plenty - the source updates weekly.
- `growth`: monthly, and append to your own table; quarterly values are revised as data comes in.
- `migration` and `stores`: monthly.

### Troubleshooting / FAQ

**A platform returns `not_found`.** The slug is not one the publisher covers. Run `reference` for the full list - slugs are lower-case and have no spaces (`bigcommerce`, not `BigCommerce`).

**A breakdown dimension comes back empty.** That platform's report does not publish that section. Check `sectionsFound` on its `PLATFORM` row.

**The latest quarter looks lower than the previous one.** It is still in progress. Filter on `isPartialQuarter = false` when charting trends.

**Can I get the full list of stores on a platform?** Not from the public reports - only the top and new store lists they publish. This Actor stays on the public side.

### Legal & fair use

This Actor reads report pages that the publisher makes freely available to anyone, without an account and without circumventing any access control, and it does not touch the subscriber-only store database. The output is aggregate market statistics plus the store lists the reports themselves publish. Check the publisher's terms before redistributing the data commercially.

# Actor input Schema

## `mode` (type: `string`):

platform = headline stats for a platform (live stores, quarter-over-quarter and year-over-year growth). growth = the full quarterly store-count series back to 2019. breakdown = stores by country, category, app, technology, theme, shipping carrier and more. migration = how many stores switched to and from the platform. stores = the top and newest stores published in the report. reference = every platform report available.

## `platform` (type: `string`):

A single platform slug, e.g. shopify, woocommerce, bigcommerce, wix, squarespace, magento. A full report URL works too.

## `platforms` (type: `array`):

Several platforms to compare in one run. Run mode 'reference' first to see all 110 available slugs.

## `allPlatforms` (type: `boolean`):

Ignore the list above and process every platform report published (about 110). Useful for a full market snapshot in one run.

## `dimension` (type: `string`):

Limit the breakdown to one dimension.

## `dimensions` (type: `array`):

Several dimensions at once. Leave empty for all of them.

## `maxItems` (type: `integer`):

Maximum records per run. A full breakdown of one platform is roughly 150 rows.

## `maxConcurrency` (type: `integer`):

How many platform reports to fetch in parallel.

## `proxyConfiguration` (type: `object`):

Optional. The reports answered every request without a proxy.

## Actor input object example

```json
{
  "mode": "platform",
  "platform": "shopify",
  "platforms": [
    "shopify",
    "woocommerce",
    "bigcommerce"
  ],
  "allPlatforms": false,
  "maxItems": 1000,
  "maxConcurrency": 4,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `results` (type: `string`):

All platform, growth, breakdown, migration and store records produced by this run.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "platform": "shopify",
    "platforms": [
        "shopify",
        "woocommerce",
        "bigcommerce"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("fanndev/ecommerce-platform-market-share-scraper").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "platform": "shopify",
    "platforms": [
        "shopify",
        "woocommerce",
        "bigcommerce",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("fanndev/ecommerce-platform-market-share-scraper").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 '{
  "platform": "shopify",
  "platforms": [
    "shopify",
    "woocommerce",
    "bigcommerce"
  ]
}' |
apify call fanndev/ecommerce-platform-market-share-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fanndev/ecommerce-platform-market-share-scraper"
        }
    }
}
```

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 <APIFY_API_TOKEN>` 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/Q4EaJJW34ABIwiBzE/builds/hxpNW3OJIKv1hGk61/openapi.json