Detecting Ad Fraud: How Technology Can Help Marketers Improve Their Ad Performance

Ad fraud is a major concern for marketers, with the cost surpassing $81 billion in 2022. This can lead to wasted ad spend and skewed data, ultimately harming campaign performance and ROI.

Reading Time: 7 mins 


  • Explore effective steps companies can take to tackle ad fraud and use tools that help identify fraudulent activity and ensure accurate data for data-driven decisions.

    Ad spend continues to be one of the most significant expenses for marketers across industries. There’s no room for missed opportunities when it comes to ad performance.

    But at the same time, Statista reports that the cost of ad fraud surpassed $81 billion in 2022, and is predicted to rise to $100 billion by 2023.

    Ad fraud misleads marketing efforts by artificially inflating metrics such as ad views, clicks, and conversions, resulting in wasted ad spend and skewed data. Marketers end up taking poor decisions based on inaccurate data, ultimately harming their campaign performance and ROI.

    Tackling ad fraud needs attention

    The Russian group “Methbot” reportedly made up to $3 million a day by generating fake website traffic and collecting fees for ad views that never actually occurred.

    Such instances lead to significant financial losses for companies and bring bad reputation to marketers. These steps can help companies tackle ad fraud and ensure that their marketing efforts are not misled:

    Work with reputable partners: Companies should work with reputable advertising partners with a track record of transparency and accountability. They should conduct thorough due diligence and research to ensure their partners are legitimate and trustworthy.

    Implement ad fraud prevention measures: Using ad fraud detection software to detect and prevent fraud can help identify suspicious traffic and fraudulent activity and provide insights into preventing it in the future.

    Monitor ad performance: Companies should closely monitor the performance of their ads to ensure that they deliver the desired results. They should track key metrics like clicks, conversions, and impressions, and analyse the data to identify any unusual patterns or trends that might indicate fraud.

    Educate employees: Companies should educate their employees on the risks and consequences of ad fraud and train them on how to identify and report any suspicious activity. This can help create a culture of vigilance and awareness and ensure that everyone is working towards the same goal of preventing ad fraud.

    Stay informed: Companies should stay informed about the latest trends and developments in ad fraud and adapt their strategies accordingly. They can attend industry conferences, read industry publications, and stay up-to-date with the latest technologies and techniques for preventing ad fraud.

    Catch early and fix

    Spotting fraudulent figures in first party data can be challenging, but some indicators can help identify them. One way to spot fraudulent figures is to look for unusual spikes or dips in performance data.

    Another way is to monitor the sources of traffic and engagement and identify those with abnormal patterns or high bounce rates. Additionally, comparing internal data with third party verification services can help identify discrepancies that may indicate fraudulent activity.

    • Ad fraud detection tools: These specialised tools can detect fraudulent activities such as bot traffic, click farms, and domain spoofing. They can monitor ad campaigns in real-time and identify any suspicious activity. Examples of ad fraud detection tools include Fraudlogix, HUMAN (formerly White Ops), and DoubleVerify.
    • Data analytics platforms: These platforms help identify anomalies in data patterns that indicate fraudulent activity. They can also identify patterns that indicate invalid or fake user behaviour. Examples of data analytics platforms include Google Analytics, Mixpanel, and Adobe Analytics.
    • Machine learning and AI algorithms: By analysing large data sets, machine learning algorithms can detect fraudulent activity patterns. These algorithms can identify patterns in user behaviour that indicate fraudulent activity. Examples of machine learning and AI-based fraud detection tools include Anodot, DataVisor, and Sift Science.
    • Data cleansing solutions: They help clean up and validate first party data to ensure its accuracy and authenticity. They also identify and remove suspicious data points indicating fraudulent activity. Examples of data cleansing solutions include Experian Data Quality, Trifacta, and Tamr.
    • Blockchain technology: This creates a tamper-proof record of ad transactions. It can help prevent ad fraud by providing transparency and traceability to the advertising supply chain.

    It’s important to note that no single solution can eliminate ad fraud. However, combining these tools and solutions can significantly reduce the risk of fraudulent activity in first-party data.

    How do these tools work? 

    Data visualisation tools identify patterns and anomalies in data that may indicate fraud. For example, a sudden spike in traffic or clicks not supported by other data points may indicate fraudulent activity. Similarly, ad fraud detection software uses machine learning algorithms to analyse ad traffic and detect fraud patterns.

    Additionally, through IP blocking or filtering traffic from known fraudulent sources or suspicious IP addresses, marketers can prevent fraudulent traffic from affecting their metrics.

    Domain blacklisting identifies and blacklists domains that are known to be associated with fraudulent activity. This can help prevent traffic from these domains from skewing metrics. Finally, bots are a common source of fraudulent traffic. Some tools can help in bot detection.

    A boost to the marketing efforts

    Ad fraud is a major concern for marketers as it can seriously harm the effectiveness of their advertising campaigns. When fraudulent traffic or clicks are included in campaign data, it can lead to misleading results, and marketers may make wrong decisions based on inaccurate data.

    Tackling it becomes crucial to ensure marketers can make data-driven decisions and optimise their campaigns for maximum impact. By removing fraudulent traffic, marketers can have confidence that their campaign data is accurate and that they can make informed decisions about where to allocate their budgets and resources.

    In addition to improving the accuracy of campaign data, tackling ad fraud can also help marketers to enhance their return on investment (ROI). Marketers can identify the channels and tactics driving real business results when fraudulent clicks and impressions are removed from campaign data. This allows them to allocate their budgets and resources more effectively and to optimise their campaigns to drive the best possible ROI.

    Fraudulent campaigns can damage a brand’s reputation and result in negative publicity, impacting sales and customer loyalty. Marketers can protect their brand’s reputation by tackling ad fraud and ensuring their campaigns deliver the desired results.

    Tackling ad fraud is critical for marketers. With the help of advanced technologies and fraud detection tools, marketers can stay ahead of fraudsters and ensure that advertising budgets are being used effectively to achieve their business objectives.

    How can you use technology to detect ad fraud and protect marketing investments?

    Find out at Martechvibe’s flagship marketing technology summit, Vibe Martech Fest, happening on 1 August 2023 at Four Seasons Hotel, Jakarta. The conference will focus on technology trends supporting marketers in evolving with the digital economy.

    For more information and registration, visit Vibe Martech Fest – Jakarta.


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