Low-quality and bot-driven traffic make it nearly impossible for marketers to make informed decisions about their ad spend without the right tools.
The digital media landscape offers a wealth of information that marketers can use to make buying decisions — yet more money is being wasted on bad media buys than ever before. Even in the age of big data, accurate statistics about ad delivery and viewability are hard to come by, and even harder to effectively link back to the buying process. Other important metrics, like ad performance, aren’t available until the impressions have already been purchased.
In the midst of all this, ad fraud and low-quality traffic can sometimes be difficult to detect before they start driving thousands of worthless clicks to your website. Without help from some heavy-duty analytics tools, humans alone aren’t capable of making truly accurate ad investment decisions.
Without Good Attribution, Ad Investment Decisions Are Arbitrary
Marketers today need to run their campaigns across a growing number of channels, each with their own set of controls and metrics that marketers use to measure success. The result is a fragmented, siloed marketing organization — marketers are often assigned to individual channels and thus rarely have a holistic view of campaigns. Even when communication between these channel-based marketers is good, the data is siloed such that observing the relative influence various channels have on an eventual purchase is practically impossible.
Gauging the importance of each respective channel to overall conversions, also known as attribution, is a huge challenge for marketers today. Without good attribution, campaign planners can’t invest budget in various channels according to their actual importance. The decisions will be largely arbitrary, meaning that brands will have little control over the performance of cross-channel campaigns.
Even if performance data weren’t siloed and marketers had a better sense of journeys to purchase, there’s simply too much online activity for them to determine attribution on their own. The chances of an eventual purchase are influenced by literally millions of variables, and humans don’t have the cognitive ability to synthesize all of them into anything better than a rough estimation.
Ad Fraud Is a Multibillion-Dollar Headache for Advertisers
Another crisis that has been tormenting the marketing world for quite some time now is ad fraud. Bots posing as human browsers can drive traffic to websites (up to 50% of publisher traffic, according to AdWeek), and will cost advertisers an estimated $172 billion in 2028, explains the Association of National Advertisers.
Being able to see when a given ad is attracting fraudulent activity is sometimes difficult, but transparency into a publisher’s ad inventory is only a small part of the problem. The biggest obstacle to preventing fraud is the lack of accurate statistics about ad delivery, despite the fact that most marketing departments today rely on a fair number of ad tech platforms, which generate and process a great deal of data. Like viewability, ad delivery is difficult to track, and it’s always being imitated more convincingly by bots.
The information marketers have about delivery is often so little and so inconclusive that it becomes nearly impossible to link it back to the purchasing process. Meanwhile, data on ad performance can only be collected after the ad unit has been purchased and the damage to your budget has already been done. Once again, while more data on the performance and delivery of ads exists today than ever before, humans still aren’t able to piece it together in a way that consistently improves their buying decisions and maximizes their ROAS.
The Need for 24/7 Monitoring
There’s another problem keeping marketers from making better media investment decisions: sleep. Put more specifically, human marketers can be vigilant all throughout the workday, but they simply can’t be optimizing campaigns 24/7. Even when poor-quality or fraudulent traffic can be easily and quickly detected, it doesn’t always appear between 9am and 5pm: without someone there to react and adjust investment, your entire budget for a given campaign could be sucked away by nonhuman digital traffic overnight.
Marketers need to be able to analyze more data about ad inventory, delivery, and viewability more quickly, and they need to be able to do so at any time of day. It’s a daunting challenge, and won’t be possible to overcome without better analytics.
That’s why many are placing their hopes in artificial intelligence (AI) marketing: marketing platforms that use thousands of variables to identify and weed out fraudulent and low-quality traffic sources, all without the need for regular human supervision. AI marketing platforms can use cognitive technology to learn from previous decisions and apply those learnings in future media purchases, always allocating spend more efficiently. As they say, when you can’t beat them, join them: to take down ad bots, marketers should start to rely on some smart tech of their own.
