Over the past 40 years, the internet has transformed into a vast information highway driving global innovation, growth, and connectivity, boasting billions of daily active users and trillions of daily interactions. However, as the internet has grown in scale and complexity, the quality and authenticity of its traffic have diminished. The web is increasingly inundated with automation tools, bots (both good and bad), and users who, for various reasons, aren’t real. In the marketing industry, this type of traffic is known as Invalid Traffic (IVT).
To better understand this phenomenon and its impact on businesses, we have prepared the inaugural annual State of Fake Traffic report.
By analyzing billions of data points from tens of thousands of anonymous campaigns, funnels, and websites protected by us, we have gained accurate insights into the scope of the fake traffic problem and how it affects different platforms, industries, and regions. In this blog post, we’ll examine the leading referral sources for fake traffic to show which platforms are the primary sources of bot traffic. For more detailed information on how specific industries, regions, and platforms are affected by fake traffic, you can download the full 35-page report here.
What Is Invalid Traffic (IVT)?
Invalid traffic consists of web traffic from bots, fake users, and invalid users who cannot convert into legitimate customers. This can include harmless bots like search engine web crawlers or malicious traffic like ad fraud botnets.
Google defines invalid traffic as “any activity that doesn’t come from a real user with genuine interest.” This includes accidental clicks caused by intrusive ad implementations, fraudulent clicks by competing advertisers, ad botnets, and more.
For Google, IVT is a concern primarily because it can be used to artificially inflate a publisher’s ad revenues—a practice that violates Google Ad service terms. However, invalid traffic isn’t limited to paid traffic; it also makes up a large portion of direct traffic and unique site visitors, leading to numerous negative effects ranging from tainted marketing analytics to wasted retargeting efforts.
The Impact of Invalid Traffic on Marketing Organizations
Historically, IVT has been a major concern for IT and security teams aiming to protect organizations from attacks orchestrated by bad actors hiding their online footprints. However, as today’s CMOs are realizing, IVT is also a pervasive problem for marketers and go-to-market teams.
For marketers and businesses that rely on web traffic to drive sales, this presents a unique challenge: due to the prevalence of IVT, virtually every marketing funnel, campaign, and operation is affected to some degree—and often in highly detrimental ways.
Where IVT exists:
Audiences, CDP Segments, and CRMs Are Contaminated: Target audiences, customer data platforms (CDPs), and customer relationship management (CRM) systems are polluted with invalid users.
Campaigns Are Optimized Toward Fake Users: Campaigns are inadvertently optimized based on fake user behavior, leading to ineffective strategies.
Revenue Opportunities Are Missed: Real sales opportunities are lost as resources are wasted on invalid leads.
Analytics and BI Systems Are Skewed: Data analytics and business intelligence (BI) systems are distorted by bad data, leading to poor insights and worse decision-making.
Websites and Conversion Funnels Are Disrupted: Invalid leads and visitors corrupt websites and conversion funnels, presenting a challenge that must be addressed sooner or later.
Examining Invalid Traffic by Source
Fake traffic is a persistent threat affecting all digital marketing channels. When left unaddressed, this fake traffic will waste ad budgets and create negative downstream effects like poorly optimized and ineffective campaigns, muddled analytics, and incorrect attributions.
Despite all efforts by search engines, ad networks, and social media platforms to reduce fraud and fakery through dedicated teams and built-in tools, significant amounts of fake traffic continue to infiltrate all platforms.
Our analysis of billions of fake traffic referrals revealed a general level of parity in fake traffic across most platforms, with some notable exceptions. The general findings of our research are summarized in the following chart:
Insert Chart Here Showing Fake Traffic Rates Across Different Platforms
Social Fake Traffic Rates Rise as Professional Networks Attract Bad Actors
Overall fake traffic rates on social media platforms are lower than comparable search and display ads. However, one category of social media—professional networks—had by far the highest fake traffic rates among all platforms examined.
Professional network platforms had an average invalid referral rate of 12.4%, with 9.7% of paid traffic and 15.3% of organic traffic being invalid.
These platforms are a convenient group of high-value targets for hackers.
For ad fraudsters, the incentive is even stronger. In 2022, the cost per click (CPC) for professional networks averaged $5.58, up to five times higher than typical social and PPC costs. From an attacker’s perspective, this makes targeting a campaign on these sites five times more efficient.
Click Hijacking Attacks Drive Fake Traffic to Display Ads
Display ads are one of the oldest forms of online advertising, allowing businesses to reach a wide audience and increase brand awareness. However, because these ads are delivered to third-party websites, they are often easily manipulated by malicious actors. Display ads are particularly vulnerable to click hijacking attacks, which increased by 125% across all platforms in 2022.
The intensity of these attacks has led to a fraud rate of 7.2% in display ads in 2022, which is 40% higher than the rate in search ads.
Click hijacking occurs when a valid user clicks on an asset that appears legitimate—such as a link or ad—but is actually a hidden malicious element that can load malware or redirect users. Last year, researchers discovered a series of Google Chrome extensions, installed over a million times, that hijacked searches and injected affiliate links into web pages, disrupting user experience and costing retailers thousands of dollars due to affiliate fraud. In the case of display ads, an attacker can cause a display ad to be clicked without the user’s knowledge by using various techniques like adding hidden layers or altering a web page’s code. The attacker then collects payment from the advertiser for the fraudulent click.
These types of attacks can be difficult to detect and prevent because they occur on the client side, and the user’s browser often cannot distinguish between a legitimate click and a hijacked one.
Viewbots Inflate Streaming Numbers and Burn Ad Dollars
Streaming platforms had unprecedented reach in 2022. The top streaming site reaches more people than all TV networks combined in the 18-49 age bracket, delivering more ads to them—ads that statistically have a higher chance of capturing the viewer’s attention and ultimately converting.
However, many of these ad viewers are not human. In 2022, streaming platforms produced the highest invalid rate for paid traffic at 11.1% in any category. Based on ad revenue figures from just one streaming platform, this could equate to over $3 billion in wasted ad spend.
So where is all this traffic coming from? The answer lies in a relatively new form of fake traffic: viewbots. These bots are pieces of automated software used to artificially inflate the view counts of streaming videos or live streams for fake content creators, generating fake interactions and fraudulent ad impressions.
Most viewbots are simple scripts that open a video in a headless browser, but more sophisticated viewbots can also create fake accounts to mimic logged-in viewers and may even include a chat bot feature that fills the stream’s chat or comment section with artificial chatter to make viewer numbers appear more legitimate. Some viewbots even click on ads to increase the perceived click-through rate. And these bot networks can be rented for as little as $10 per month.
The impact of these fake viewers goes beyond fake clicks; many established content creators offer partnership programs where they earn commissions for mentions or ad impressions.
If these impressions are generated by bots rather than real people, then the ad budget used to create and place these ads is wasted.
If it costs $2,000 for 100,000 impressions and 15-20% of those impressions are fake, that’s $300-400 wasted. Considering that most ad campaigns on these platforms measure impressions in the millions, the costs of these fake impressions can add up quickly. Moreover, as fake traffic skews key performance indicators, decision-making becomes increasingly challenging.
