Non-human traffic can create an “inflated number that sets false expectations for marketing efforts,” said Mr. Weinstein.
Marketers often use web traffic as a good measure for how many of their consumers saw their ads, and some even pay their ad vendors when people see their ads and subsequently visit their website. Knowing more about how much of their web traffic was non-human could change the way they pay their ad vendors.
Advertisers have told Adobe that the ability to break down human and non-human traffic helps them understand which audiences matter “when they’re doing ad buying and trying to do re-marketing efforts, or things like lookalike modeling,” he said. Advertisers use lookalike modeling to reach online users or consumers who share similar characteristics to their specific audiences or customers.
Ad buyers can also exclude visitors with non-human characteristics from future targeting segments by removing the cookies or unique web IDs that represented those visitors from their audience segments.
In addition to malicious bots, many web visits also come from website “scrapers,” such as search engines, voice assistants or travel aggregators looking for business descriptions or pricing information. Some are also from rivals “scraping” for information so they can undercut the competition on pricing.