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Linh Tran Huy

AI and Machine Learning in Advertising: Introduction


AI and machine learning in performance marketing

People familiar with the latest digital marketing practices will know that AI and machine learning play a significant role. On Google Ads, the days of manually setting keyword bids are long gone. Instead, there is smart bidding, which allows Google to set bids in real-time based on which searches or keywords are most likely to generate a conversion at a target CPA or ROAS.


Anyone who has tested manual bidding versus smart bidding will likely find that the latter outperforms the former. This is now a common best practice and is often not even tested anymore. The question therefore stands: if smart bidding is already running the show, what is the role of a skilled advertiser?


The Role of Humans in a Smart Bidding World


Smart bidding is highly effective at optimising for conversions, but it’s important to remember that it’s only as good as the inputs it receives. The human element remains critical, as it provides context, strategy, and nuance that machine learning alone cannot achieve. Let’s explore where a smart human advertiser makes all the difference.


Imagine that you're running a lead generation campaign, where the goal is to generate leads that your sales team will follow up on to convert into customers. Enabling smart bidding will likely cause a rise in lead volume due to the machine learning algorithm adjusting bids dynamically based on the probability of conversion. These adjustments happen in real time, far faster and more efficiently than any human could manage.


However, after six weeks, you may notice a significant drop in lead quality. While you may be getting more leads, your sales team is struggling to close them. In reality, Google's machine learning can optimise for the quantity of leads, but cannot differentiate between qualified leads that are likely to turn into customers and unqualified leads. The conversion signal being fed to Google is simply "leads", but the true goal should be leads that convert into sales.


Feeding the Machine the Right Data


This is where smart human advertisers come in. A savvy marketer will realise that smart bidding is excellent at driving more leads but is not inherently equipped to distinguish between good and bad leads unless it has the right data. A smart advertiser will take action to feed Google’s algorithm with enriched data: specifically, the data from your CRM that indicates which leads are actually closing into sales.


By integrating CRM data and tracking lead-to-sale conversions, the advertiser can provide Google with the proper signal—leads that generate revenue. As a result, the algorithm will shift from optimising purely for lead volume to optimising for lead quality. In practice, this might result in a decrease in total lead volume, but sales and revenue will increase because the leads Google delivers will be more likely to convert.


Machines are smarter than humans in certain areas, but the human touch is needed to feed the algorithm with relevant data in order to create an environment that is conducive for the system to maximise performance. Smart bidding and machine learning alone will not beat a human advertiser that works in tandem with AI to yield the best possible results.





If you have any questions, need advice, or want to take your digital marketing to the next level, we’re here to help. Our team offers a free audit to assess your current performance and show you how we can improve your results. Reach out today and let’s discuss how we can work together to maximise your ROI!

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