SaaSPersonalization

Careful Personalization

Adjust greetings, language, or defaults while keeping neutral fallbacks that users can override.

Start with 500 free creditsDocumentation

Email gender · 1 credit per lookup · no monthly fee

GreetingHi Jane
Neutral fallbackOn

Users can always override

The problem

A little personalization lifts engagement, but gendered personalization done carelessly backfires hard: assume wrong and the greeting reads as presumptuous, or worse, offensive, and the very message meant to feel personal instead feels like a mistake the recipient has to correct.

With Encrata

Treat inferred gender as a soft hint with a confidence score, personalise only when the probability is high, and default to neutral language everywhere else. Give people a visible way to set their own preference, so the inference is a starting point the user can always override, never a label pinned to them.

How it works

1

Send the address

Call the gender endpoint with just an email address; the name in the local part is enough to work from.

2

We infer the verdict

Encrata reads the name embedded in the address and returns a likely gender and country with a confidence score.

3

Use it with care

Segment, personalise or enrich on the verdict, always keeping neutral fallbacks and letting people override. One credit per lookup.

One call, structured answer

Careful Personalization runs on the email gender lookup at 1 credit per lookup. Same API key, same JSON shape as every other Encrata lookup.

  • A single male / female / unknown verdict with a 0-100 confidence score
  • Country signal included, so ambiguous names resolve by region
  • 1 credit per lookup, with free repeats for six months
  • unknown is returned honestly when a name is ambiguous, never a guess
Terminal
curl -X POST "https://app.encrata.com/api/email/gender" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"email": "jane.doe@example.com"}'
response.json
{
  "email": "jane.doe@example.com",
  "gender": "female",
  "country": "US",
  "probability": 98,
  "credits": 1
}

High confidence or neutral

Personalise only above a confidence threshold you set deliberately, and default to neutral language for everything below it. Use the probability score as the gate: a high-confidence verdict can inform a gendered greeting, a low-confidence one gets the safe fallback, and every user has a visible setting to state their own preference, which always wins over the inference.

Personal without presuming

Done this way, personalization lifts engagement without the presumptuousness that torpedoes it, because the message only leans when the signal is strong and always yields to what the user tells you. The neutral fallback is not a compromise, it is the correct default, and treating it that way is what keeps a helpful touch from becoming an offensive assumption.

More email gender use cases

View all
jane.doe@acme.com
+ Gender fieldFemale · 98%

Gender Enrichment

Add a probabilistic gender field to lead and customer profiles when users have not provided one

CRMEnrichment

Newsletter reach

58%
42%
Female 58%Male 42%

Audience Analytics

Understand campaign reach by inferred gender in aggregate across lists, subscribers, and event signups

MarketingAnalytics
Women's collection12,480
Men's collection9,020
2 segments built

Marketing Segmentation

Tailor content, product recommendations, or creative tests where gender relevance is legitimate

EcommerceMarketing
Start with 500 free credits
$curl https://encrata.com/api/agent/lookup -H "Authorization: Bearer YOUR_API_KEY" -d '{"e": "satya@microsoft.com"}'