B2C Contamination Detector
Paste search terms, flag the consumer-intent ones
Pure rule-based scanner that flags consumer-intent search terms hiding in B2B search-term reports — DIY hobbyists, students, retail-minded queries — so you can negative them in bulk before they hit your spend cap.
- Paste a search-term report into the input — terms only, one per line.
- The detector runs each term against a curated B2C signal pattern (DIY, hobby, kids, school, home, etsy, amazon, retail, plus 60+ others).
- Each term is tagged B2C, possibly-B2C, or B2B with the matched signal.
- Copy the B2C list as a negative-keyword block ready for the Editor.
Negatives — copy ready
No B2C contamination flagged yet.
Why this exists
In industrial B2B, 10–25% of search-term spend is typically going to consumer intent that no Smart Bidding model can disentangle. Manually flagging this is a slog; rule-based filtering does 80% of the work in seconds.
Frequently asked
How do I find B2C contamination in a B2B search-term report?
Look for terms that mention DIY, hobby, kids, schools, retail brands (Amazon, Etsy, Walmart), home use, gifts, or anything implying consumer-grade pricing. This detector flags 60+ such patterns automatically. The output is a copy-paste-ready negative-keyword list.
Why does Smart Bidding amplify B2C contamination?
Smart Bidding optimizes to whatever conversion you feed it. Consumer queries have lower CPC and the model finds them, then routes more spend their way. Over time, the model "learns" that consumer queries convert (because lead-stage conversions are cheap) and conversion quality collapses. Negatives cut this off at the source.
Will I miss real B2B queries by adding these as negatives?
Possibly — words like "best", "review", and "vs" sit in the "possibly B2C" bucket precisely because they show up in legitimate B2B comparison searches. The detector flags those separately so you review manually before negativing them.