← Glossary Term

Answer laundering

Answer laundering is the practice of planting content in the community threads that AI engines trust, so the engine repeats it back to buyers as neutral advice. The recommendation reads as organic and was bought. It works because AI answers lean on community sources: Google's AI responses cite Reddit in roughly a fifth of cases.

Why it works

Models weight community threads heavily because those threads read as unpaid human experience, which is exactly the signal a buyer wants and exactly the signal that can be manufactured. Companies have already been caught flooding an 830,000-member subreddit with posts written so AI engines would repeat them.

The laundering happens in the handoff. A planted post is obviously promotional in its own thread and becomes neutral advice once a model paraphrases it into an answer.

The ten-minute audit

Write the five questions a buyer would ask an AI before choosing in your category. Run them through ChatGPT and Perplexity. Click every community citation the answer rests on, then read the post history of whoever recommends your competitor.

If the glowing mentions trace back to a handful of accounts created last month, you are not losing to a better product.


The argument behind the term: Answer laundering: the short take →

Related terms: Native Organic Distribution · Distribution debt · The citation gap · Ghost citation

Loud on purpose

Steal the term.
Then go measure yours.

New takes most weeks on how products actually get found, quoted and chosen.