PDQ includes a gender segment in analytics, rules, and A/B testing - based on the shopper's first name at checkout, with ~97% coverage and zero setup.
How it works: (1) take the first name from checkout; (2) clean it (lower-case, strip accents, transliterate - "Élise" → "elise"); (3) match against a public dataset of 200,000+ names → Male / Female / Unknown. Rare names (<10 matches) default to Unknown.
What to expect: ~97–98% of names recognized; ~95–98% accuracy; most errors are gender-neutral names ("Alex," "Jamie"). Every night PDQ reviews "Unknown" and high-frequency names and adds them to the reference table, so accuracy improves automatically. [confirm coverage % + nightly job still current]
Questions? Chat or support@prettydamnquick.com.