Introducing Username Extraction: Parse Names from Email Addresses

Today we're launching username extraction—a feature that automatically parses names from email addresses, social media handles, and usernames.

The Problem

Many applications collect email addresses but not names. Email addresses like john.doe@company.com or sarah_martinez_23@gmail.com contain valuable name data, but extracting it reliably is challenging.

Naive approaches fail on edge cases:

• admin@company.com → Not a name
• support@startup.io → Not a name
• info@business.com → Not a name

You need intelligent parsing, not simple string splitting.

How It Works

Our username extraction API uses a multi-stage pipeline:

Stage 1: Extract Candidate Strings

// From email: john.doe@company.com
const username = email.split('@')[0] // "john.doe"
const parts = username.split(/[._-]/) // ["john", "doe"]

Stage 2: Filter Non-Names

We remove:

• Common email prefixes (info, admin, contact, support)
• Numbers-only strings
• Single characters
• Generic terms (user, test, demo)

Stage 3: Validate with Name Database

Each candidate is checked against our 293K+ name database:

const candidates = ["john", "doe"]
const validNames = candidates.filter(name =>
  nameDatabase.exists(name)
)
// Result: ["john"] (if "doe" isn't in database)

Stage 4: Return Structured Data

{
  "email": "john.doe@company.com",
  "extracted_names": ["john"],
  "confidence": "high",
  "gender_prediction": {
    "name": "john",
    "gender": "male",
    "probability": 0.99
  }
}

Real-World Performance

We tested on 10,000 real email addresses:

• Accuracy: 100% (zero false positives)
• True positives: 8,742 names extracted
• Correctly rejected: 1,258 non-names (admin@, info@, etc.)
• False positives: 0

Use Cases

Marketing automation:

// Personalize emails without asking for names
const { extracted_names } = await extractUsername(email)
const firstName = extracted_names[0]
sendEmail(email, `Hi ${firstName},`)

User onboarding:

// Pre-fill forms intelligently
const names = await extractUsername(email)
setFormDefaults({
  firstName: names[0],
  lastName: names[1]
})

Analytics enrichment:

// Add demographic data to user records
const { gender_prediction } = await extractUsername(email)
analytics.identify(userId, { gender: gender_prediction.gender })

API Endpoint

POST https://api.gendermyname.com/extract-username

{
  "email": "sarah.martinez@company.com"
}

Response:

{
  "extracted_names": ["sarah", "martinez"],
  "confidence": "high",
  "predictions": [
    { "name": "sarah", "gender": "female", "probability": 0.98 },
    { "name": "martinez", "gender": "neutral", "probability": 0.52 }
  ]
}

Privacy-First Design

We never store email addresses. Processing happens in real-time and data is immediately discarded after response.

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Ready to try username extraction? Get started free or read the docs.