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Share on XWhat marketers need to know about the schemes infiltrating ad spend
In a perfect world, every ad impression would be presented to, and viewed by, an actual human that is potentially interested in a specific product or service. Unfortunately, the programmatic ad space is rife with malicious actors perpetrating a plethora of fraud schemes preventing this from happening, leading to wasted time, effort, and ad budgets.
That’s why it’s more important than ever to actively protect your brand from sneaky fraudsters, given the difficulty distinguishing between a human and a bot impression.
What is ad fraud?
Ad fraud refers to any invalid impression resulting from a deliberate activity that prevents the proper delivery of ads to real users at the right time and place. This fraudulent traffic activity results in a financial loss for the advertiser and/or publisher. These deceptive practices not only diminish the effectiveness of marketing campaigns but also obscure true audience engagement, making it difficult for marketers to measure the actual impact of their efforts.
By generating artificial traffic, fraudsters can significantly inflate costs and reduce the overall return on investment (ROI) for ad spend. This makes it crucial for advertisers to implement robust ad fraud detection and prevention measures to safeguard their budgets and enhance the accuracy of their analytics.
What are the different types of advertising fraud?
Fraudsters fool advertising platforms with invalid traffic, clicks, impressions, and conversions via bots (or botnets) and other advanced methods, preventing ad content from being delivered to legitimate users. They are then rewarded with significant financial gain due to advertisers paying for impressions that were never actually seen by humans. In addition to the financial loss, brand reputation also stands to be harmed or diminished.
As bot traffic is clearly not the intended audience for advertisements, it’s typically classified as invalid traffic, or IVT. While IAS tracks many different types of IVT, there are two major common types:
- General Invalid Traffic (GIVT): Traffic generated by benign crawlers or other non-malicious bots. Easily identified and filtered through basic means.
- Sophisticated Invalid Traffic (SIVT): Malicious and evasive traffic designed to circumvent protections around ad display. It is difficult to identify and track, and requires advanced analytics, data science techniques, and/or direct human intervention.
The reality is that fraudsters continue to employ ever more sophisticated tactics to defraud the programmatic ad ecosystem and steal money from advertisers, and those tactics are expected to continue to evolve at a rapid pace.
No market in the advertising industry is immune to ad fraud, and it spreads across major ad environments, including open web, social media, connected TV, and mobile. Some major types of ad fraud include domain spoofing, device spoofing, app spoofing, ad stacking, and many more.
Common ad fraud schemes
While fraudsters continue to evolve their tactics, the most common forms of ad fraud fall into three main categories: click fraud, impression fraud, and conversion fraud. Understanding these schemes is crucial for protecting your advertising budget and ensuring you’re getting real value from your digital efforts. Let’s take a closer look at how each type of fraud works and the impact it can have on your campaigns.
1. Click Fraud
Click fraud is a deceptive practice where fraudulent clicks are generated on online advertisements, inflating the number of ad engagements without any real interest from users. This type of fraud can be highly damaging to advertisers who rely on pay-per-click (PPC) campaigns, as they end up paying for clicks that have no chance of leading to a sale or meaningful interaction.
One common form of click fraud involves bots—automated software programs that are designed to mimic human behavior and click on ads. These bots are often sophisticated enough to bypass detection systems, making it difficult for advertisers to distinguish between real clicks and fraudulent ones.
Another common method is through click farms, where groups of individuals are paid to click on ads repeatedly. These workers can produce massive amounts of fraudulent clicks in a short period.
Though these clicks are technically from humans, they hold no value for the advertiser because the users have no intention of engaging with the content. Competitors may also engage in click fraud by deliberately clicking on a rival’s ads to deplete their advertising budget, ultimately reducing their visibility. This form of sabotage can skew campaign metrics and lead to unnecessary financial losses.
2. Impression Fraud
Impression fraud, also known as “ad stacking” or “pixel stuffing,” occurs when fraudulent activities inflate the number of ad impressions. Unlike click fraud, where clicks are artificially generated, impression fraud manipulates the visibility of an ad.
For instance, in ad stacking, multiple ads are layered on top of one another in a single ad placement, but only the top ad is visible to users. Every ad in the stack is counted as an impression, even though they’re not actually seen.
Pixel stuffing is another technique used in impression fraud. In this method, ads are placed in tiny, almost invisible, areas of a webpage—often just a few pixels wide—so they technically “load” but are never actually seen by the human eye. This manipulation results in inflated impression counts, giving advertisers the illusion that their ads are being viewed by a large audience.
The downside is that no real value is being created for advertisers, who are paying for exposure that doesn’t exist. Over time, this can severely undermine an advertising campaign, distorting performance metrics and wasting valuable ad spend.
3. Conversion Fraud
Conversion fraud, also known as lead or sales fraud, is perhaps the most costly form of ad fraud because it directly affects the bottom line by falsifying high-value actions, such as form fills, downloads, or purchases. Fraudsters may use a variety of tactics to simulate legitimate conversions. For example, they might deploy bots to fill out forms or use fake data to complete online transactions. This can give the appearance that an ad campaign is successful when in reality, the conversions are worthless.
In some cases, fraudsters may use stolen credit cards or identities to make fake purchases, leading to financial and reputational harm for businesses. Fake leads generated by conversion fraud can also clog sales pipelines, wasting time and resources for marketing and sales teams that follow up on non-existent prospects. Beyond the immediate financial costs, conversion fraud can lead to skewed data, making it difficult for marketers to accurately gauge the effectiveness of their campaigns. Over time, this can distort a company’s overall marketing strategy and lead to poor investment decisions.
Ad fraud adds up
In 2022, estimated programmatic ad fraud losses topped $80 billion USD. With programmatic ad spend expected to increase exponentially year over year, projected ad fraud losses could easily cross $170 billion USD by 2028. Combine this with significant damage to brand reputation, and you have a recipe for disaster without protection at your side. In addition to this, ad fraud and pay-per-click operations are commonly used as a profitable foundation for major malicious actors’ infrastructure such as Distributed Denial of Service (DDoS) botnets, ransomware, and Advanced Persistent Threat (APT) groups.
The stakes are higher than ever when it comes to disrupting these operations and maintaining brand integrity.
The exponential rise in both the sophistication and volume of ad fraud means that advertisers must be more vigilant than ever. Without effective ad fraud detection and prevention measures, not only do advertisers risk losing financial resources, but they also face a potential erosion of consumer trust. Ultimately, ad fraud doesn’t just steal money; it diminishes the overall efficiency and credibility of the digital advertising ecosystem.
The silver lining? IAS can help.
Detecting and combating online advertising fraud is an ongoing challenge — but IAS is here to help. While most solutions rely solely on an automated check to detect any invalid traffic, IAS’s unique, three-pillar approach is powered by unmatched scale and machine learning, providing the most accurate detection and prevention.
The IAS three-pillar approach uses:
- Rules-based detection with automated rule checks to identify anomalous behavior patterns
- AI/Machine learning that uses big data to detect any hidden, uncommon patterns
- The IAS Threat Lab employs malware analysis and reverse engineering to uncover emerging threats
Paired with the filtering abilities of IAS Threat Lab, automated rule-based detection, and the power of AI and machine learning, IAS’s ad fraud product suite ensures that no fraud goes undetected to protect peace-of-mind while scrolling.
Want to start detecting ad fraud today? Contact an IAS representative.
