# Email Pattern Finder - Likely Work Emails from Name + Domain (`flash_scraper/email-pattern-finder`) Actor

Generate the most likely work email formats (first.last@, flast@, first@...) from a full name and company domain, ranked by how common each pattern is, plus an MX domain check. Read-only B2B prospecting: builds address strings and does a DNS lookup only - never sends email or probes mailboxes.

- **URL**: https://apify.com/flash\_scraper/email-pattern-finder.md
- **Developed by:** [Flash Scrape](https://apify.com/flash_scraper) (community)
- **Categories:** Lead generation, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.40 / 1,000 person processeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## Email Pattern Finder — find the email address pattern of any company from a name + domain

**Find the email address pattern of a company** and turn plain names into ranked work-email guesses. Give it a company domain and a list of full names; it returns each person's most likely addresses (`first.last@`, `flast@`, `first@`…) scored by how common each pattern is, plus a DNS check that the domain can actually receive mail and which provider runs it (Google Workspace vs Microsoft 365). It's the natural front end of a **find → verify → enrich** prospecting flow — **no API key, no proxies, no per-seat email-finder subscription**, just pay-per-result.

### What it does

- **Generates up to 12 ranked email candidates per person** from a library of common corporate patterns: `first.last`, `flast`, `firstlast`, `f.last`, `first`, `first_last`, `firstl`, `first-last`, `lastfirst`, `last.first`, `lfirst`, `last`.
- **Scores each candidate 0–99** based on how common that pattern is in the wild (`first.last` ranks highest), and surfaces the single `best_guess` per person.
- **Checks the domain's MX records** via a DNS-over-HTTPS lookup to confirm the domain can receive mail at all — if no mail server exists, every candidate's confidence is cut, so dead domains can't inflate your list.
- **Detects the email provider** from the MX host (Google Workspace, Microsoft 365, or other) — useful both as a deliverability signal and as a firmographic data point.
- **Normalizes names**: strips accents (`José` → `jose`), splits first/last name, and handles single-name inputs (those only get the `first@` pattern rather than fabricated surnames).
- **Accepts messy domain input** — `acme.com`, `https://www.acme.com/about`, it all resolves to the bare domain.
- Lets you **restrict generation to specific pattern IDs** when you already know the company's format and just want it applied to a batch of names.

Everything is **read-only and privacy-respecting**: the actor only builds address strings from the names you provide and performs one DNS lookup on the domain. It never sends an email and never probes individual mailboxes.

### Use cases

- **Sales prospecting** — you found 20 decision-makers on LinkedIn at a target account but no contact info. Paste the names + domain, get ranked address guesses in seconds instead of paying per-credit on Hunter or Apollo.
- **Recruiting outreach** — reach engineers and managers directly at their work address instead of fighting the InMail queue.
- **Lead-list completion for agencies** — you're delivering a lead list on Fiverr/Upwork and half the rows have a name and company but no email; batch-fill the gap and mark each row with its confidence score.
- **CRM enrichment** — export contacts missing an email, group them by company domain, run each group through the finder, and re-import the `best_guess` column.
- **Pattern discovery** — confirm one address for any employee (from a signature, a press release), see which pattern it matches, then re-run the actor with that pattern locked in via `patterns` for the whole department.

### Input

| Field | Type | Default | Description |
|---|---|---|---|
| `domain` | string | *(required)* | The company domain emails should use, e.g. `acme.com` or `https://acme.com`. |
| `names` | array | *(required)* | People to generate email guesses for, one full name per line (e.g. `Jane Doe`). |
| `verifyMx` | boolean | `true` | Look up the domain's MX records (DNS) to confirm it can receive mail and detect the email provider. Boosts confidence. No mailbox probing, no email sent. |
| `maxCandidatesPerPerson` | integer | `6` | How many ranked email guesses to return per person (1–12). |
| `patterns` | array | *(empty)* | Optional: only generate these pattern ids (e.g. `first.last`, `flast`, `first`). Leave empty for all. |

Example input:

```json
{
  "domain": "stripe.com",
  "names": ["Patrick Collison", "Jane Doe"],
  "verifyMx": true,
  "maxCandidatesPerPerson": 6
}
````

### Output

One dataset row per person:

| Field | Description |
|---|---|
| `name` / `first_name` / `last_name` | The input name and its parsed parts |
| `domain` | Normalized company domain |
| `mx_found` | Whether the domain has mail servers (`null` if `verifyMx` was off) |
| `email_provider` | Detected provider from MX (e.g. Google Workspace, Microsoft 365) |
| `best_guess` | The single most likely address |
| `best_guess_confidence` | Its 0–99 score |
| `candidates` | All ranked guesses, each with `email`, `pattern`, and `confidence` |

Example row:

```json
{
  "name": "Jane Doe",
  "first_name": "jane",
  "last_name": "doe",
  "domain": "stripe.com",
  "mx_found": true,
  "email_provider": "Google Workspace",
  "best_guess": "jane.doe@stripe.com",
  "best_guess_confidence": 95,
  "candidates": [
    { "email": "jane.doe@stripe.com", "pattern": "first.last", "confidence": 95 },
    { "email": "jdoe@stripe.com", "pattern": "flast", "confidence": 88 },
    { "email": "janedoe@stripe.com", "pattern": "firstlast", "confidence": 78 },
    { "email": "j.doe@stripe.com", "pattern": "f.last", "confidence": 72 },
    { "email": "jane@stripe.com", "pattern": "first", "confidence": 65 },
    { "email": "jane_doe@stripe.com", "pattern": "first_last", "confidence": 60 }
  ]
}
```

Export to **CSV, Excel, or JSON** from the Apify Console or via API.

#### Example output

A real sample from a live run:

| name | domain | best\_guess | best\_guess\_confidence | mx\_found |
|---|---|---|---|---|
| Patrick Collison | stripe.com | patrick.collison@stripe.com | 95 | true |
| John Smith | stripe.com | john.smith@stripe.com | 95 | true |
| Jane Doe | stripe.com | jane.doe@stripe.com | 95 | true |
| Maria Garcia | stripe.com | maria.garcia@stripe.com | 95 | true |

### Pricing

**Pay-per-result**: you're charged only per person processed — a fraction of a cent per validated row. No subscription, no monthly credit packs that expire. A **free Apify plan** is enough to run your first batches and test the output on real accounts before paying anything.

### Tips / FAQ

#### Does it verify that the mailbox actually exists?

No — and that's deliberate. The actor generates **pattern-based guesses** ranked by real-world commonality and verifies the **domain** (MX lookup), not individual mailboxes. It performs no SMTP handshakes and sends nothing. For mailbox-level checking, pipe the `best_guess` column into the [Bulk Email Verifier](https://apify.com/flash_scraper/email-verifier).

#### How accurate are the guesses?

`first.last@` alone covers the largest share of corporate mailboxes, which is why it scores 95. Accuracy is highest at companies with standardized IT (most SMBs and mid-market firms); it's lower at very large enterprises with legacy formats or duplicate-name collisions. The confidence score tells you how much to trust each row — and if you can confirm one real address at the company, lock its pattern via `patterns` and accuracy for the rest of the batch jumps.

#### What happens with single names or names with accents?

Accents and diacritics are transliterated (`René Müller` → `rene.muller@…`). A single-token name (e.g. just `Madonna`) only generates the `first@` pattern — the actor won't invent a surname.

#### Why did all my confidences drop for one domain?

The MX check found no mail servers, so every candidate's score was reduced (to roughly 60% of its base, floor 5) and `mx_found` is `false`. That usually means the domain can't receive mail at that apex — check whether the company actually uses a different email domain.

#### Can I process people from many different companies in one run?

One run handles **one domain** with any number of names. For a multi-company list, group your rows by domain and trigger one run per domain via the Apify API — each run is billed only for the people it processes.

#### How do I integrate it?

Start runs from the [Apify API](https://docs.apify.com/api/v2) or SDK, schedule recurring runs with Apify **Schedules**, and export the dataset as CSV/Excel/JSON or push it onward with Apify integrations (webhooks, Zapier, Make).

### Related actors

- [Bulk Email Verifier](https://apify.com/flash_scraper/email-verifier) — the natural next step: verify and score the guessed addresses before you send.
- [Company & Domain Enricher](https://apify.com/flash_scraper/company-domain-enricher) — enrich the same domains with company name, socials, and tech stack.
- [Phone Number Validator](https://apify.com/flash_scraper/phone-number-validator) — clean the phone column of the same lead list.

***

Found a bug or missing a feature? Open an issue on this actor's **Issues tab** — typical response within 1 business day.

# Actor input Schema

## `domain` (type: `string`):

The company domain emails should use, e.g. 'acme.com' or 'https://acme.com'.

## `names` (type: `array`):

People to generate email guesses for, one full name per line (e.g. 'Jane Doe').

## `verifyMx` (type: `boolean`):

Look up the domain's MX records (DNS) to confirm it can receive mail and detect the email provider. Boosts confidence. No mailbox probing, no email sent.

## `maxCandidatesPerPerson` (type: `integer`):

How many ranked email guesses to return per person.

## `patterns` (type: `array`):

Optional: only generate these pattern ids (e.g. 'first.last', 'flast', 'first'). Leave empty for all.

## Actor input object example

```json
{
  "domain": "stripe.com",
  "names": [
    "Patrick Collison",
    "Jane Doe"
  ],
  "verifyMx": true,
  "maxCandidatesPerPerson": 6
}
```

# Actor output Schema

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

No description

# 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 = {
    "domain": "stripe.com",
    "names": [
        "Patrick Collison",
        "Jane Doe"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("flash_scraper/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 = {
    "domain": "stripe.com",
    "names": [
        "Patrick Collison",
        "Jane Doe",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("flash_scraper/email-pattern-finder").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 '{
  "domain": "stripe.com",
  "names": [
    "Patrick Collison",
    "Jane Doe"
  ]
}' |
apify call flash_scraper/email-pattern-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=flash_scraper/email-pattern-finder",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Email Pattern Finder - Likely Work Emails from Name + Domain",
        "description": "Generate the most likely work email formats (first.last@, flast@, first@...) from a full name and company domain, ranked by how common each pattern is, plus an MX domain check. Read-only B2B prospecting: builds address strings and does a DNS lookup only - never sends email or probes mailboxes.",
        "version": "0.1",
        "x-build-id": "NRbQh07dXFv6rRU6i"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/flash_scraper~email-pattern-finder/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-flash_scraper-email-pattern-finder",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/flash_scraper~email-pattern-finder/runs": {
            "post": {
                "operationId": "runs-sync-flash_scraper-email-pattern-finder",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/flash_scraper~email-pattern-finder/run-sync": {
            "post": {
                "operationId": "run-sync-flash_scraper-email-pattern-finder",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "domain",
                    "names"
                ],
                "properties": {
                    "domain": {
                        "title": "Company domain",
                        "type": "string",
                        "description": "The company domain emails should use, e.g. 'acme.com' or 'https://acme.com'."
                    },
                    "names": {
                        "title": "Full names",
                        "type": "array",
                        "description": "People to generate email guesses for, one full name per line (e.g. 'Jane Doe').",
                        "items": {
                            "type": "string"
                        }
                    },
                    "verifyMx": {
                        "title": "Check domain MX",
                        "type": "boolean",
                        "description": "Look up the domain's MX records (DNS) to confirm it can receive mail and detect the email provider. Boosts confidence. No mailbox probing, no email sent.",
                        "default": true
                    },
                    "maxCandidatesPerPerson": {
                        "title": "Max candidates per person",
                        "minimum": 1,
                        "maximum": 12,
                        "type": "integer",
                        "description": "How many ranked email guesses to return per person.",
                        "default": 6
                    },
                    "patterns": {
                        "title": "Limit to specific patterns (optional)",
                        "type": "array",
                        "description": "Optional: only generate these pattern ids (e.g. 'first.last', 'flast', 'first'). Leave empty for all.",
                        "items": {
                            "type": "string"
                        }
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```