EcommerceMarketing

Marketing Segmentation

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

Start with 500 free creditsDocumentation

Email gender · 1 credit per lookup · no monthly fee

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

The problem

Broad, undifferentiated sends waste budget and annoy the half of your list the message was never meant for. You want to tailor the women's range to one group and the men's range to another, but you have no demographic signal to segment on beyond crude purchase history.

With Encrata

Use the inferred gender as one input to your segmentation, not the only one, and build audiences that lean toward the products each group is most likely to want. Because the signal is probabilistic, keep segments soft and always give people an easy way to opt into the other, so a wrong guess costs a click, not a customer.

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

Marketing Segmentation 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
}

One soft input among many

Feed the inferred gender in as one weighted input alongside purchase history, browsing behaviour, and stated preferences, never as the sole basis for a segment. Build audiences that lean toward likely-relevant ranges, and because the signal is probabilistic, keep the segments soft with an obvious path for anyone to opt into the other, so a wrong inference costs a click instead of a customer.

Relevance without the risk

Teams that segment this way see tighter relevance without the backlash that crude gender targeting invites, because the message leans rather than assumes. Measure it on engagement and unsubscribe rate together, if a segment's opt-outs climb, the inference was carrying too much weight, and dialling it back toward behavioural signals usually fixes it.

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

Respondents

Skew detected

72% one group · rebalance before you run

Research Sampling

Balance respondent groups or detect demographic skew before running interviews, polls, or user studies

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