21st Century Machine Learning in Marketing & PPC. Revealing the facts.

July 31, 2020
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6 min
 reading time

Machine learning in Marketing? Yes, it is the 21st century and machine learning and AI have stormed the digital marketing scene. Question being, do you know enough about (ML) machine learning in marketing and artificial intelligence to make informed decisions regarding it?

Innovations in artificial intelligence (AI) and machine learning (ML) have opened up a whole new world for PPC marketers. From bidding to automated rules, reports, and alerts or managing multiple PPC ad campaigns, machine learning in PPC has provided us with more time to devote to higher-level strategy and less ambiguity about the results.

The Evolution of Machine Learning

Machine learning is essentially the process of leveraging algorithms to process data, extract learning from that data, and determine or predict what will or should happen next.

The objective is that over time, machines will require less human intervention to behave in the desired manner. In other words, the tools learn from the data rather than being controlled by us or their underlying rules-based programming. They learn and evolve from experience, and hypothetically, at least, they carry out tasks as we would if we were to carry them out ourselves.

In God we trust; all others bring data.

W. Edwards Deming
machine learning in marketing is critical for success

Over the past 20 years, ML has evolved substantially. It has become smarter and better able to adapt to new input instead of relying on the training data upon which it has established. Learning models have become more sophisticated, based on the task at hand and the type and volume of incoming or available data.

As a result, any algorithm-based process can now be automated to a significant degree, enabling scale and supporting new efficiencies throughout the organization.

The Role of Machine Learning in marketing and PPC

PPC is another aspect of digital marketing that has seen incredible changes and growth over the past couple of decades. As it becomes more reliant on algorithmic input, PPC is more customizable, allowing marketers to reach their targets with greater accuracy and maximizing their efforts.

Specifically, the real value of machine learning and AI in PPC has been to optimize the bidding and bid adjustment process to allow for greater competitive advantage. It has also made possible vital insights in ad copy A/B testing and keyword targeting, supporting marketers in managing more successful and economical PPC campaigns.

Additionally, AI and ML enable automated reporting, dynamic workflows, and competitor trend-spotting and analysis, driving value, and providing real-time insights that directly impact your PPC marketing campaigns’ success.

So in a broad sense, we might say that the ultimate goal of machine learning in marketing including PPC is to improve results, and it does this very well. However, as with other digital tools, there are limitations. Marketers like to feel like they are in the driver’s seat, but AI and ML tend to take that away. A good example of AI/ML-driven technology in PPC is Google Smart Campaigns. Advertisers only have access to a handful of data points—like CTR, impressions, and conversions—so there is very little control, visibility, or transparency into the campaign.

robot controlling traffic
The question is? Can machine learning in marketing help prevent click fraud?

What is PPC Click Fraud? And How Does Machine Learning Adapt To This?

PPC advertising is based on a pay-per-click model. Advertisers pay the ad network based on the number of times their ad has been clicked. Often, companies set up a daily limit to help manage their resources, so when they reach their threshold, the ad stops running.

In an effort to remove the ad from circulation or tank your advertising budget altogether, competitors might click on the ad until the budget runs out. In another scenario, the ad publishers themselves click on the ads that appear on their websites to drive up their ad revenues. Affiliates can be another source of click fraud as companies you do business with an attempt to take credit for large numbers of clicks.

Another objective, or at least a by-product of click fraud, is that the data collected from the campaign is useless as it does not come from a legitimate source.

It is estimated that about 25% of all PPC clicks are fraudulent, costing digital advertisers in the realm of $23.7 billion every year.

Lacking critical oversight, key processes can indeed escape the initial intent simply by looking legitimate. This factor (appearing to come from a genuine source) is pivotal to the success of PPC click fraud, so marketers that have not yet leveraged a solution are likely losing a lot of money.

Gaining Transparency, Retaining Control.

The happy medium between machine learning in marketing and PPC Prevention tools is simple and factual. Anyone claiming to use AI or machine learning in their click fraud prevention tool, without showing a clear paper trail for the sake of even the most basic confirmation of results, cannot be considered to be authentic. The reality is that machine learning in marketing is the hallelujah to anyone looking to lose control of their precious data and insights. Which any successful data-driven marketer would not want to do.

Data-driven marketers agree that transparent insights are the #1 reason for success.

Transparency is critical in every business practice, but in advertising, even more so. Marketers need to have complete control of the data their campaigns deliver, and most click fraud solutions simply don’t deliver in this regard. In other words – if you don’t know where your clicks are coming from, the tendency is to assume that your clicks are coming from a reputable source. Based on that assumption, you are almost certainly leaving money on the table.

Today’s digital marketers understand the need for transparency. They want to be in the driver’s seat to gain control over every aspect of their campaigns to ensure maximum value and ROI. The environment needs to be customizable to suit the industry use-case, provide insight into and oversight of each individual click to enable more reliable click fraud prevention.

ML and AI are excellent tools, but only when they also deliver the transparency and control you need to stay profitable.

machine learning in marketing and a hand typing on keyboard

Ultimately, the click fraud solution you choose should deliver detailed insights into each action taken. Without this knowledge and a “paper trail” to follow, it is impossible to understand if or when actions are being taken on your behalf. This means that you are left with a layer of ambiguity to factor in and a margin of error that both diminishes the value and skews insights.

In the effort to optimize your PPC efforts, ClickGUARD delivers data-driven insights while mitigating threats at all levels. We put control back into your hands along with your industry knowledge to provide a 360˚ solution you can rely on.

Start your free trial today to see ClickGUARD in action, or reach out to us directly to learn more.

Jason is a passionate data-driven specialist with extensive PPC & SEO experience. When not writing about SEM he can be found surfboarding the wildest ocean waves of the Argentinian coast.