Most detected bots now mimic human behavior. What that means for traffic quality in affiliate marketing?

Bots that imitate real users now make up most of the bot-flagged invalid traffic measured by Spider Labs: 64.4% in June 2026, up from 20.4% in January 2025. For affiliate marketing, and especially for grey zone verticals where lead quality determines payouts, this suggests that checks at the click or registration level may no longer be enough on their own. In our view, verification needs to move deeper into the funnel.

Ad fraud has always existed in digital advertising. Over the past eighteen months, the data suggests bots have become much better at imitating real users. According to fraud detection vendors, today's bots don't just click links and leave. They move cursors, space out actions at irregular intervals, and generate session data such as scroll depth and session duration that looks like a real person navigating a site. The signals that used to indicate a human user are no longer reliable on their own.

What the data says about bot traffic in 2026

Spider Labs, which sells ad fraud detection services, estimates that $25.3 billion in ad spend was exposed to fraud in the first half of 2026. The company applies its observed fraud rate of 5.58%, up from 4.32% in 2025, to projected global digital ad spending, so this is an estimate rather than a directly measured loss.

Other vendors report very different numbers for 2026, from about 1% invalid traffic at Integral Ad Science to 40% at Anura by June, depending on what they measure and how, and not all of them show an increase. What several of them share is a warning about sophistication. Anura, like Spider Labs, describes AI-driven bots that imitate realistic mouse movements, scroll depth and session duration.

The more telling figure from Spider Labs is the share of advanced bots. In June 2026, 64.4% of bot-flagged invalid traffic mimicked human behavior, up from 20.4% in January 2025. In Spider Labs' data, the overall fraud rate rose and the bots became more sophisticated.

DataDome published findings in September 2026 that measure something different, bot traffic to websites rather than ad clicks, but point in a similar direction. Across its customer sites, malicious bot traffic grew 124% between July 2025 and June 2026, while human traffic grew 13.2% over the same period. In a June test of the homepages of 21,491 popular websites, 65.3% failed to stop even one of ten test bots.

Where grey zone funnels are exposed

Neither report measures fake leads directly. Our reading is that anyone running SOI or DOI campaigns, or any funnel where registration completions and session activity determine payouts, is exposed to this shift.

If bots can move through a funnel the way humans do, completing forms and generating the session data that standard verification checks look for, the traffic can appear clean at the top. The click looks legitimate and so does the registration. The problem only surfaces downstream, when the conversion that was supposed to follow the lead never arrives.

This hits the relationship between affiliate, network, and advertiser directly. Affiliate payouts are based on lead quality, and advertiser revenue depends on what actually converts. When invalid traffic passes checks at the registration level, both sides of that equation get distorted, and the dispute is hard to resolve because the evidence at the point of the lead looks clean.

Where verification needs to go

In our view, the signals hardest for bots to fake consistently are downstream outcomes that cost something to produce: verified payments, activations, retention over time, and conversion rates at later stages of the funnel. Neither report tests this, so treat it as practical judgment rather than a finding. Session patterns can help, but advanced bots already imitate cursor movement and click timing convincingly enough that session behavior alone isn't a reliable differentiator.

Volume metrics such as clicks, registrations, and lead counts need to be read alongside conversion context. A high lead count with low downstream conversion is a signal worth investigating, because bots that imitate users may produce lead-level data that looks convincing on its own.

Frequently asked questions

Is $25.3 billion the actual amount lost to ad fraud?
No. Spider Labs applies its observed fraud rate to projected global ad spending to produce this estimate. It reflects exposure to fraud, not confirmed losses. Estimates differ widely between vendors, so treat any single figure as an order of magnitude at best.

Does this affect all verticals equally?
Probably not, though the data we reviewed doesn't isolate grey zone verticals. Our reasoning is that verticals where payouts are tied to registrations or lead completions, and where downstream conversion data is harder to access or disputed, are more exposed. Many grey zone verticals fit that description.

What should I actually check?

Start by comparing your downstream conversion rates with your lead volume. If the gap between registered leads and paying or active users is larger than expected, and standard checks at the registration level show nothing wrong, the problem may sit further up the funnel than your current verification covers.

At Offerpump, we know what clean traffic looks like because we see the other side of it every day. As an advertiser, we monitor what converts, not just what registers, and we build partnerships with affiliates whose traffic holds up downstream.

If you want to talk about what that looks like in practice, send us a message.