While cybersecurity and fraud are making the headlines, advertising fraud continues to be overlooked and undervalued as a genuine issue impacting organizations. Often dismissed as a dilemma for the marketing team to solve alone, the losses and impact on organizations are too consequential not to be an integral part of your cybersecurity strategy. The 2021 cost of digital ad fraud worldwide was $65bn, according to Statista, double the value of fraudulent transactions made by payment cards worldwide. Many businesses are at a critical time economically, and when tightening their bottom line, any loss is too great.
The reason so few organizations have measures in place to defend themselves is that across many industries, there is so little acknowledgement of the issue, creating a lack of understanding, awareness and visibility. And without these things, it’s difficult for organizations to take the proper steps to defend themselves, and this creates an advantage for fraudsters that can operate easily under organizations’ radars.
With the problem ranging from social media to mobile, there is much for organizations to digest, but those who do understand and address it can create a competitive edge.
From Social to Mobile to PPC
Ad fraud is a subset of invalid advertising traffic, categorized as malicious and intentional. Cyber-criminals carry out a range of methods, sometimes including the use of malicious bots, to exploit organizations and take a share of their advertising budget. When broken down into facts and figures, ad fraud is having a much bigger impact than many decision-makers may assume.
The complexity of the advertising ecosystem is one of the reasons it’s so difficult to tackle. Cyber-criminals aren’t restricted by one advertising type but find and exploit vulnerabilities across various advertising channels.
For example, the rise of social commerce has led companies to make significant investments in social media advertising on platforms like Facebook, and Statista estimates ad spending in this industry to reach $226bn this year.
However, the vast marketing budget spent on Facebook has inevitably led to a huge increase in the prevalence of invalid and fraudulent activity. In the first quarter of 2022, Statista stated that Facebook took down 1.6 billion fake accounts used to maliciously click on ads, negatively affecting advertisers by wasting their budgets. Additionally, bots, click farms, competitor clicking, and false engagement are just some of the common examples of invalid traffic (IVT) on various social media platforms today.
Additionally, attribution fraud and SDK spoofing are a menace to the mobile advertising ecosystem in particular and completely disrupt revenue and marketing data. Engagement such as clicks and installs may be awarded to a fraudulent source instead of the correct one, also known as misattribution. This means the results you use to decide which channels get more budget and which gets less are inaccurate, spelling disaster when scaling campaigns.
The consequences also spill over to pay-per-click advertising. Cyber-criminals will click on a Google Ad for a product or service with the intent to artificially inflate the number of clicks or impressions that the advertisement receives either by the advertiser or by someone hired to click on the ad. Click fraud can be difficult to detect, costing the advertiser a lot of money if they pay for each ad click.
While financial loss is one challenge, invalid traffic creates other consequences, such as polluting the key marketing metrics and data you use to scale, misrepresenting engagement analytics and restricting business growth.
Staying Agile and Intelligent
Platforms are beginning to cotton on to the existence of ad fraud and provide some built-in measures to address it. However, with more acknowledgement of the issue, fraudsters must evolve their techniques to evade detection. And, while ad fraud is evolving, cyber defenses are not.
Intelligent attacks need intelligent defences. Many organizations are leveraging machine learning, a type of artificial intelligence (AI) that analyses app engagement for abnormal behaviors. This includes events happening on mass or irrational engagements, such as illegitimate in-app purchases going through mobile measurement partners (MMPs), which are the companies that help track and measure how people use their smartphones and other mobile devices.
Implementing machine learning into your ad fraud protection strategy will allow you to combat invalid traffic and ad fraud with a proactive and preventative approach. Machine learning also operates in real-time, which means it is more accurate and able to stop fraud before it occurs than reacting to fraud as it evolves with new rules.
All departments in organizations are pressured to make every penny count. Advertisers constantly battle for more money, while cyber skills shortages and overstretched security teams struggle to keep up with a growing attack surface. However, without protection, marketing teams risk damaging their budgets, misplacing resources and seeing a conversion rate that doesn’t match the time invested into boosting their ads.
Uniting Against Fraud
One of the biggest differences between an organization that makes savings and one that doesn’t is proactivity. Organizations across the globe are taking charge of their cyber defenses in order to protect their data, reputation and margins, and now they must do the same for ad fraud.
The impact of ad fraud is limitless and the issue affects everyone in every organization, from the marketer to the C-suite. The losses are too significant to ignore and ROI must be prioritized. Cybersecurity teams need to work in parallel with their marketers to lessen the impact made by ad fraud. If you’re creating a strategy to keep your business safe – include ad fraud.