I believe in PPC bidding automation. With PPC automation, I made (my clients) fortune, and I build my campaigns in PPC automation fashion. I give the algorithm freedom, but I teach it using good input. To master the output (conversion), you must master the input.


My Beginnings and the Adwords Era

I stepped into the world of PPC in 2020. From my perspective, that was an interesting time because, at that time, bidding automation (more precisely smart bidding strategies) was becoming more prevalent. Before this point, my vision of working in Google Ads was collecting data, and optimizing based on that data. This premise still holds very true, but today I view it from a bit different perspective. 

Let me explain. 

I started PPC from zero. Before I actually started working, my touch-points with PPC were various courses. At that time, most of them were focused on the manual processing of data and manual adjustments. I imagined my day would be analyzing the keyword data, time of day performance, specific ad copy segments, etc. Two of these three things are still part of my work, but now I have an assistant working for me 24/7. And like any assistance, it requires guidance, in the case of the algorithm, it requires good input. It takes on some more manual tasks, and I can now focus more on the strategy, the big picture, and finding new ways to reach audiences – all the things I consider old-school advertising, but in a digital age.

Google AdWords Logo

Google AdWords Logo


The Step Back and Google Ads Era

I must admit, it took me some time to think about my mindset and a bit more to start changing it. I didn’t want to give up control of all the small touch points. I felt I would be less good as an advertiser. Moving away from Quality Score, learning that its metrics we see in the columns are not part of the auction as well as learning that making bid adjustments (location, audience, demographic) is not only NOT recommended but outright ignored when using most smart bidding strategies – those were all big changes for somebody new to the industry and just getting comfortable with the “Google Adwords” way. 

However, I must also admit that I like this change in our industry of paid digital advertising (not that I have a choice, mind you). My PPC work today is occasionally more based on the work outside of Google Ads: making sure to implement Google Ads Enhanced conversion tracking, work in GTM, landing page optimizations, making sure the leads are processed in a good way in the CRM, feeding back the lead data from CRM back to the algorithm, using Optymize to gain CRO insights, trying to learn more about my audiences from Spark Toro, leaning on cross-platforms for additional strategic observations (LinkedIn, in general, is pretty much up to date live database from which you can draw industry, seniority and other data to push your overall PPC strategy). 

Now, I don’t want to give a false impression that, in my view, PPC is now just to let the algo go wild. That’s the opposite of a good way. Automation today is more of an upgrade – it gives us more freedom to do good advertising, closer to what it really is, rather than just be automatons pulling levers. Even at my time (oh dear!), we had scripts to optimize keyword bids for page position. Good PPC foundations are still valid today. 

I can summarize this very well using the currently prevalent topic – migration from Universal Analytics to Google Analytics 4. In UA, we had to use the Category/Action goal structure. I liked it, but it was rigid. In GA4, we can name our events how we like (to a degree), and using the custom parameters, we can build the structure we want. But, this ups the game. We have more freedom, but also more responsibility to build a future-proof system that helps us and our clients ask the right questions.

Google Ads Logo

Google Ads Logo


Brave New World

Before I give you my take on the future of PPC, let me take you back again to the beginnings I mentioned earlier – the year 2020. Besides Google not showing all terms in the Search Term Report, even the ones that converted, at that time RSA was pushed to the front as the main ad format for Search (now the only one), and page position script was no longer working as that item was removed from the reports. A bit later, we saw the birth of Performance Max, and Microsoft replaced manual CPC with Enhanced CPC for Bing Advertising

The direction in which things are going and will go is clear – using machine learning to help advertisers be more effective. That means using machine learning to build models that will learn based on data and over time reduce the gap between the expected outcome and the actual outcome. I truly hope we will never have a 100% accurate prediction model, in advertising or the real world. In a way, we are now mentors to an AI child that is learning about the world and behavior patterns.

I remember in 2020, a rumor about Google Ads shutting down manual CPC, even keyword targeting (reminder, we lost Placement targeting for Video campaigns). Many people feared that PPC advertisers will lose their job. I would say that in today’s world of abundant data, where both you and your competitors have a wealth of information at your disposal, SAME information, we have to kick up the notch and master automation. 

It’s no longer about data access, it’s about catching the right data and using the machine to output those strategies for us. If I keep the same mindset that I had in 2020, I will become extinct. Luckily, I stepped into the world of PPC at a peculiar time, I feel blessed that I caught a glimpse of both worlds, and I am content that early on I caught the wind of automation and that it piqued my interest. That’s why I can honestly say that I’m glad how things are going in PPC – exciting times are ahead of us.

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Ivan Vatović is a PPC Specialist and Trainer at the Will Marlow Agency. Keeping up to date with the latest Google Ads releases, Ivan is in charge of educating our team on the most important industry news and changes. He’s the go-to person to ask for anything related to Google Analytics 4 and Google Tag Manager.

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