# Email Pattern Finder — staff names into addresses (`apexfaucetdotxyz/email-pattern-finder`) Actor

Crawl a company site, infer its email pattern from published addresses, and turn every named employee into a contactable address.

- **URL**: https://apify.com/apexfaucetdotxyz/email-pattern-finder.md
- **Developed by:** [Martin Raum](https://apify.com/apexfaucetdotxyz) (community)
- **Categories:** Lead generation, Business, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## Email Pattern Finder — staff names into addresses

Companies publish their team and hide their addresses. One accountancy firm in
testing listed **41 named staff and zero emails**. Those names are worthless to a
salesperson until you can address a message to them.

This crawls the site, collects any published addresses on the company's own
domain, works out which pattern the company uses, and applies it to everyone else.

### How it decides

It tests every observed `name → address` pair against 11 common patterns
(`first.last`, `flast`, `f.last`, `firstlast`, `last.first`…) and counts
agreement. Confidence is reported honestly:

| evidence | confidence |
|---|---|
| 3+ matching published addresses | **high** |
| 2 | medium |
| 1 | low — one match can be coincidence |
| 0 personal addresses published | **not inferable** — you get ranked guesses, labelled as guesses |

Only addresses on the company's *own* domain are used. An agency or partner
address would infer the wrong pattern entirely.

### Works outside English

Job titles, contact-page names and personal names are matched in **English,
Spanish, German, French, Italian, Portuguese and Dutch**. An English-only version
found zero people on every Spanish site tested — which reads as "this firm
publishes no staff" when the truth is we were not looking at the right page.

It also handles **Spanish and Portuguese double surnames**. "José García López"
is addressed `jose.garcia@`, using the paternal surname — not `jose.lopez@`.
Taking the last name made every such firm un-inferable; both conventions are now
tested and the winning one is reported (`first.last|paternal`).

### What it does not do

**It does not verify deliverability.** SMTP probing is intrusive, unreliable and
gets your infrastructure blacklisted. Every address is marked `published`,
`inferred` or `guess` so you know exactly what you have. Anyone claiming verified
addresses from a crawl alone is overstating it.

### Output

```json
{
  "domain": "example.co.uk",
  "pattern": "first.last", "patternConfidence": "high",
  "patternEvidence": [{ "name": "Sarah Jones", "email": "sarah.jones@example.co.uk" }],
  "peopleCount": 41, "addressableCount": 41,
  "contacts": [
    { "name": "David Hardie", "title": "Accountant",
      "email": "david.hardie@example.co.uk", "source": "inferred", "confidence": "high" }
  ]
}
```

### The pipeline

```
Local Business Finder → Lead Contact Finder → Email Pattern Finder
     companies              named people           addresses
```

Each stage is useful alone; together they turn a town and a trade into a contact list.

# Actor input Schema

## `websites` (type: `array`):

Domains to process. Feed it the website column from the Local Business Finder.

## `maxPagesPerSite` (type: `integer`):

Pages to crawl looking for staff and published addresses. The crawler reads the site's own navigation rather than guessing URLs.

## `includeGuessesWhenUnknown` (type: `boolean`):

If the site publishes no personal addresses, no pattern can be inferred. With this on you still get the most likely address (first.last is the commonest pattern) plus alternatives, clearly labelled as guesses.

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

Proxy settings for the requests.

## Actor input object example

```json
{
  "websites": [
    "coapt.co.uk",
    "perrysaccountants.co.uk"
  ],
  "maxPagesPerSite": 10,
  "includeGuessesWhenUnknown": true
}
```

# Actor output Schema

## `dataset` (type: `string`):

Staff with inferred or published email addresses.

## `overview` (type: `string`):

Browse the results as a table.

# 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 = {
    "websites": [
        "coapt.co.uk",
        "perrysaccountants.co.uk"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("apexfaucetdotxyz/email-pattern-finder").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 = { "websites": [
        "coapt.co.uk",
        "perrysaccountants.co.uk",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("apexfaucetdotxyz/email-pattern-finder").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 '{
  "websites": [
    "coapt.co.uk",
    "perrysaccountants.co.uk"
  ]
}' |
apify call apexfaucetdotxyz/email-pattern-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,apexfaucetdotxyz/email-pattern-finder"
        }
    }
}
```

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/x4XdkMrd7b42JkDz3/builds/LGZjQg22kz1OVeQrf/openapi.json