Your campaign can train itself on bots
You launch a campaign. Bots interact with the ad, visit the site, click buttons, and sometimes even trigger conversion events. The platform sees engagement.
Then the algorithm does exactly what you asked it to do: find more people who behave like the people converting. Except some of the “people” were never people.
You do not only pay for the original bots. Your optimization algorithm can start using their behavior as a signal for where to spend the next dollar. If bots make up 30% of the first traffic, Meta and Google can learn from that contaminated sample and send more of the campaign toward traffic that looks like it. The campaign can be effectively poisoned before enough genuine buyers arrive.
This is how you get the CMO nightmare: the campaign starts great, something changes, and performance becomes inexplicably worse even though the creative, offer, landing page, and audience stay the same. When the bot share is only 5%, real human sessions dominate the early data and the platforms are more likely to learn from genuine prospects. Early bot traffic has an outsized effect because it can determine what the campaign learns to optimize for.
Ad-monitoring platforms are one reason these bots arrive so quickly. They track who is advertising, which audiences they target, when campaigns run, and what appears on the landing page. Some maintain 10,000–20,000 Facebook profiles to sample different audiences. They use these profiles to inspect new campaigns and collect intelligence that can later be sold. To avoid being blocked by Meta or Google, their bots use different identities, browser profiles, proxies, and human-looking actions—including clicks on forms, buy buttons, and other conversion controls.
