Ad fraud, driven explicitly by internet bot activity, reached a new high in 2023 with growing AI capabilities. Historically, the certain level of acceptance of bots in media efforts and data collection was the cost of doing business with a digital presence. The wasted ad spend, inflated performance metrics, and no conversions brought attention to ad fraud in 2023.
A recent research from Juniper put this into measurable impacts -
- Ad fraud caused a loss of 22% in ad spending in 2023. A staggering number where Cost Per Click (CPC) and average lead cost in high-tech is expensive. Imagine your planned $5MM ad spend for the year and $1MM lost to click farms and bots.
- Estimated ad fraud to cost $100B of the ad spend by the end of 2024—a 20% increase from 2023.
- With an ad fraud measurement and mitigation strategy, organizations can recover at least 30% of the wasted ad spend.
The rise of SIVT (Sophisticated Invalid Traffic) through AI is changing how bots behave, making it even more challenging to separate the types of bots. To address this problem, we must better understand how these bots operate.
Ad fraud mitigation is an evolving solution requiring a continuous feedback loop. We will need preventative measures at the software application level and post-analysis solutions to solve this new challenge.
Ad Fraud - ignore it at your own risk!
In 2024, advertising efforts are ramping up on first-party data activation and targeting. However, businesses often ignore the impact of bad bots on data and the need to limit bad first-party data. With research showing ad fraud on the rise, increasing ad spending will only increase your loss in ad spending. Ignoring this issue is costly to your business.
The Interactive Advertising Bureau (IAB) surveyed the upcoming challenges for media investments in 2024. In this survey, the 'mitigating ad fraud' concern was 8th. In contrast, 'having enough first-party data' was a top three concern. But your first-party data now includes bots impacting your traffic data.
A big concern is why ad fraud is not higher on everyone's list. You can directly measure the impact of the lost ad spend, but a few factors impact how we perceive and address ad fraud -
Over Expectation and Trust in the MarTech Platforms
A common expectation is that marketing platforms (where ad buys and placements occur) actively monitor and eliminate bot traffic. This includes all types of web crawlers and social bots. Unfortunately, ad frauds have reached new levels of sophistication, mimicking human behavior and good bots. Ad bots make it difficult for bot management solutions and marketing platforms to separate humans from malicious bots in the ecosystem.
MarTech platforms have a relatively low threshold and allow bad bots to pass through until they later identify them as such. By then, these bots will have shifted to a new source.
Actively monitoring your media analytics and performance data, such as traffic, fallouts, and conversion KPIs, is necessary to support the platform's effectiveness. A feedback loop to these platforms with analysis identifying bot data is critical to combat bots sooner and effectively.
Ad fraud and Bot Management is not a one-time fix
The bot monitoring, measurement analysis, and mitigation cycle are continuous. This process does not end with an initial fix. This process is ongoing (remember the game 'Whac a Mole'?). This process requires continuous team collaboration, communication, and the ability to act quickly.
Cookieless future readiness
The lack of complete understanding of the impact of the cookieless future is limiting marketers from taking action on bots. Marketers are also moving to an ID-based tracking but have not accounted for bots in that data. Organizations must realize that reducing ad fraud and cookieless future readiness are not mutually exclusive. The changing advertising landscape requires accurate and clean data for activation and measuring effectiveness and performance.
The complexity of identifying and addressing ad fraud
The advertising journey and ecosystem are all susceptible to fraudulent traffic. No platform or ad network is safe. Click farms, click boots, pixel stuffing, and other ad bots are all evolving and require constant monitoring and identification.
Addressing this is an intensive effort across people, processes, and technology to work effectively in addressing ad fraud. Making it easier to ignore than address.
Mitigating Ad Fraud
We will never eliminate ad fraud and bad bots- that's the first thing we must accept. Setting this expectation of your data quality is critical. Your goal is to reduce the impact of ad fraud and bad bots on your advertising efforts, performance data, and, ultimately, your budget. Analyzing your data for actual human engagement is a repetitive task that ensures effective marketing targeting.
These mitigation strategies have helped improve our clients' return on ad spending (ROAS). Implementing them has positively impacted overall performance and trust in data.
Media Analytics Solution
Almost all organizations have some form of bot identification and filtering platform applied to their incoming web traffic data. As noted earlier, these platforms are effective when they have faster and more continuous input on bot data.
Leveraging a media analytics solution that continuously monitors your collected data for bot traffic would address that requirement. Post-analysis of data for checks on signals such as source computer validation, comparing to other bot behaviors, source response times, time of day, number of clicks, and many more parameters would drive confirmation of human activity.
The right solution can impact your ad spending and performance data within a few weeks. For example, we eliminated 91% of invalid traffic with the Media Analytics program in one scenario. This, in turn, increased the overall conversion rate and reduced bounce rates.
Combining Media Analytics with People-Based Identity Solutions
With the cookieless future readiness, ID tracking solutions have become prevalent in most organizations' MarTech stack. Combining a media analytics solution that uses AI/ML and a non-deterministic approach with your people-based data would significantly improve your data transparency with the ability to strive for data accuracy.
A non-deterministic approach by a media analytics solution provides the ability to classify data based on humans v/s. Bots. Combining your people-based data with a media analytics solution would offer the ability to reach the right audience and actual humans more effectively.
Leveraging a media analytics solution as part of your advertising ecosystem will ease the process of monitoring active bots. This solution and collaborative team efforts to review and act on the analysis will help mitigate the bot impact. Bot impact analysis must be part of your ongoing performance data review process. This ensures stakeholders are aware and vested in this mitigation.
Conclusion: Act Now
While dedicating efforts to combat ad fraud is not easy, it is necessary with the changing advertising landscape. Ad bots are impacting your data and your campaign performances. Apply the right ad bot mitigation strategy with the right Media Analytics solution. Customizing this to your business process allows you to garner accurate data and reduce wasted ad spend.