Today’s digital marketers all compete for attention with the same ad engine automations. In this seemingly level playing field, how do you stand out? How can artificial intelligence help you be better than the rest, rather than simply fit in? Your answers lie in automation layering. In, Unlevel the Playing Field, Frederick Vallaeys reveals how to combine the best of human creativity and machine efficiency to create winning digital marketing programs.

This follow-up to Frederick’s first book dives into three key areas of search marketing: bidding, targeting, and messaging, to illustrate how automation layering can take your campaigns to the next level of profitability. Whether you’re an agency or an in-house marketer focused on eCommerce or lead gen, this book shows how to differentiate yourself in the digital marketing crowd with a new path to increase sales, improve returns, and the opportunity to make ad platforms work for you. 

This is The Author Hour Podcast and I’m your host, Frank Garza. Today, I’m joined by Frederick Vallaeys, author of a brand-new book, Unlevel the Playing Field.

Frank Garza: Fred, welcome to the show.

Fred Vallaeys: Thanks for having me on, Frank, it’s great to be here.

Frank Garza: To start off with, can you share a bit about your personal and professional background?

Fred Vallaeys: Probably the most interesting part is that I was at Google pretty early on, I was one of the first 500 employees there and I was working on the ad words product as it was called at the time. 10 years doing that, I was the ads evangelist so I was lucky enough to get to travel and speak at a lot of conferences and help a lot of advertisers just figure out who this whole complicated ad words thing was working. Nowadays, I run a company called Optmyzr so we build software that saves advertisers time and makes them have better results whether they’re advertising or Google ads, Microsoft ads, Amazon ads, all of those difficult online digital marketing platforms.

Frank Garza: Yeah, you mentioned the travel there and one of the things that caught my eye in the beginning part of your book was you’re talking about how you used to travel a hundred thousand miles per year before COVID hit, and then all that had to change. Can you talk about how big of a change that was for you and then the town hall that you ended up starting because of it?

Fred Vallaeys: Yeah, I mean, it was a huge change, right? Because I sort of lived for that travel and that was the primary way that I get in front of audiences to share the message on how we were thinking about optimizing digital ads. Then, all of a sudden, the rug got pulled out from under everyone and then like, “Well, what do we do now? How long is this thing going to last?”

We just decided to start a PPC Townhall and what was interesting is that the initial thing that happened, I think everybody started doing these Zoom webinars. I was watching a bunch of them and I was like, “Oh my god, these are so boring, all hands on the screen, nothing is moving.” It’s like, I’m already doing enough meetings that look exactly like this and now, people expect me to sit through webinars instead of going to one of these fun conferences where you get to have — you got a big stage, you got the big projector, you get to talk to people, you got to interact, everything’s lively, you go and have a drink afterward. So, that just didn’t jive for me and then I found a software that let us do a much more engaging, interactive format that is much more like a TV show and we’re like, “Well, let’s play with this.” 

We brought on some pretty good guests and we had fun. For me, it was just a way of staying in touch with my industry friends and still seeing them and because I can’t imagine — I mean, now, we’re coming up on three years and I wouldn’t recognize some of these people anymore if I saw them in person, I’m sure.

Unleveling the Playing Field: Automation Layering

Frank Garza: Yeah, let’s define a term here. We’re going to talk about PPC and PPC Marketing quite a bit and we get all kinds of people that tune into this podcast. Just in case they’re not familiar with what PPC is, can you define that for us?

Fred Vallaeys: Yeah, PPC is pay-per-click advertising. As the name suggests, it means that you pay for every click that you get and it’s really mostly associated with Google. On Google, there are ads at the top and the bottom of the search results page and the advertisers who placed those ads, they generally choose the keywords for which they want to advertise and then they only pay if somebody interacts on the ad by clicking on it.

That’s where pay-per-click came from, that’s where PPC came from. Nowadays, it’s kind of a misnomer almost because with Google ads, you can do audience targeting, you can get on the display network, you can do video ads. There’s these other ad systems like I was saying, Facebook, Amazon and sometimes you pay-per-click, sometimes you don’t but generally just refer to as pay-per-click industry or search engine marketing — SEM is another term we use.

Frank Garza: This is your second book. As you were writing about your first book in the intro to your new one — I’m going to read you a quote here from that — it says, “Since my previous book, digital marketing in an AI world came out, just three years ago, the landscape has already changed dramatically.” What has changed so much that you felt like you needed to write another book?

Fred Vallaeys: The first book was about this whole push towards automation, so I’ve been doing pay-per-click for 20 years and that’s kind of when it was roughly invented. It was around since the late 1990s. Everything was manual so you had to go in, you had to choose your keywords, you had to set beds for every keyword that you picked, you had two write an @ text for every single keyword or at least, every single ad group.

Then over the years, Google kept automating, they were like, “Well, you can just sort of tell us a broad match keyword and we’ll show your ad for anything that’s kind of related to that keyword and you don’t have to do the bidding anymore. We’ll do automated bit management, you just got to tell us what your goal is.”

“When it comes to the ad, instead of writing out three lines of @ text, why don’t you just tell us 15 variations of a headline and we’ll just put that together automatically for you.” There’s an ongoing move towards Google and the ad engine’s doing much more of the work that we used to do — doing it for us — so that first book was about not fighting this change. It’s like, it’s going to happen, right? Moore’s law is just dictating that these systems are going to get better and better.

I wrote that first book about collaborat[ing] with automation, you’re going to have better results if you worked together with it. The second book I really wanted to write because I started speaking at conferences, I’d give this whole talk about how automation was like a good thing and at the end of the session, people would always ask the same question. They were like, “Yes, but wait. Everybody else in this room that’s just listened to your talk, we’re going to be using the same tools from the same ad engines. How exactly do I stand out?”

Even more concerning, do people attending my sessions — they tend to be PPC experts who are doing for a living, right? They’re really into this but their fear was that, now, you even have these advertisers who don’t really care about advertising that much, they just know they should be doing it so they turn on a bunch of stuff from Google that’s automated. So, these experts were like, “Well, does that mean I’m on a level playing field with all these newbies and is that going to make my life all that much harder?”

The second book is about solutions. We know this automation is happening but let’s talk about some specific things we can do to unlevel the playing field back in the favor of the expert who wants to push their PPC campaigns to that next level.

Frank Garza: One of the ways you talk about doing that unleveling the playing field is automation layering. Can you talk about what is automation layering?

Fred Vallaeys: Yeah, so the concept of automation layering is that I think a lot of the advertisers are just scared of what the engines like Google are doing, right? When you put all your faith in them and you just let them automate the way that they are going to do stuff, it’s a little scary because they’re managing your bids, they’re managing your keywords and all this stuff.

Ultimately, the advertiser wants to exert a lot of control over these automations but they can be really time-consuming very quickly, right? Because now, in the past, you would have been setting bids for keywords but now you’re monitoring how Google is doing the bidding for you and that’s not great. So the whole concept of automation layering is that you should build your own lightweight automations that monitor the ones from Google. 

Google’s really good at heavy machine learning, the type of stuff that we could never individually invest in enough to do — We’re talking about hundreds of millions of dollars to build these high-end sophisticated machine learning systems. What we as individual advertisers can do is we can write little scripts, little tools, little helpers that monitor what Google’s doing. 

If all of a sudden, Google is placing a bid that seems exorbitantly high, it sends us an email and says, “Hey Fred, go and take a look like this keyword. Google’s automatically bidding but it seems like they may have gone off the rails a little bit, go and check it out.” That’s what automation layering is all about. It’s like, how do you put these lightweight automations that you control on top of Google so that Google is still doing your bidding as supposed to going off on its own.

Frank Garza: Is there an example you can give us of how you’ve seen a business do this with one of their ad campaigns or something that a business could do that would help us understand what it looks like?

Fred Vallaeys: The bidding example that I just gave is a good one, right? We’re certainly seeing — and this was a case that I think I put this one in the book as well but — there was a company and they had put half of their campaigns on automated bidding from Google and all of a sudden very unexpectedly, their manually managed campaigns were starting to really perform very poorly. What was happening is the competitors of these advertisers, they had noticed that the automated bidding from Google was pushing their bids higher and higher, right? 

It was more effective at competing against this competitor, so the competitor came in and they said, “We’re going to raise our bids manually across the board.” So that started having a secondary level impact on all of the campaigns from the advertiser. They thought we’re experimenting with automated bidding on half of our campaigns but what they didn’t see coming was that the other half of the campaigns would be impacted through a second level effect. 

An automation layer is something as simple as something that looks for anomalies, so there is a great script that we have that will look for anomalies and it will say typically on a “Tuesday at 11:00 in the morning, you have about $500 of cost on this campaign.  But today, it looks like you’re more than 20% above that level for a typical Tuesday at 11 AM, so go and take a look at it.” And so this is the type of automation layer that just keeps an eye on everything that you’re doing. 

While all of these automations from Google go and do their thing and it flags things that weren’t your retention — and that’s kind of a monitoring automation layer. There’s then also automation layers that you can put in place to do really sophisticated account structures for example. When it comes to shopping campaigns, a lot of advertisers want to have really detailed structures where every product lives in its own product group. 

I mean, that’s because they have better bidding control over these but if you have a catalog of 50,000 products that can be really tedious to set up, right? Once you set it up, then Google goes and does a lot of its automation to make sure these campaigns work well but you could literally spend a whole week building out that structure to support what Google needs to do. So we have an automation layer where you basically say, “Okay, here is how I want to structure my campaigns.”

I want to have one campaign for every brand that I sell and then maybe I want to split it for the sub-category and then I want to put every individual product, every skew in its own product group. You take five minutes telling the tool how to do this and then the tool cranks up your structure that would have taken you a week to build manually and now you got this automation layer that’s really built the campaign structure that’s in support of Google’s high-end sophisticated machine learning.

Humans vs. Machines

Frank Garza: There is a chapter that’s called or that’s titled “When Machine Learning Breaks Down” and you talk about how there’s some things that humans can do better than machines and vice-versa. What are some of the things that humans perform much better at than machines?

Fred Vallaeys: Yes, so nowadays, humans still tend to be better at a couple of things. First of all, is like messaging, right? Knowing what is going to resonate with your target audience and so even though Google has made a lot of efforts in the end roads in automating the ad creative or the text that somebody will see in the ads that you have, it’s still really up to the humans to feed in what are the right things that may resonate with your prospective customer. 

That is the first level. The next level is about machines that are really good at finding a signal and doing machine learning but they have to run a lot of tasks to get to a place where they have enough data and as humans, we know our businesses, right? If you sell automotive parts, you sell car batteries, well you know that the first time of the year when it starts freezing and you got frost, that’s usually when a lot of car batteries will not start in the morning. 

That’s when people will come into your store to buy a lot of car batteries. Does Google know about this? Well, they may figure it out eventually but it could take them a couple of years to start seeing this sort of a pattern, so you as the human who has an automotive parts business, well, you know these things. If you can tell Google, “Hey, look at the rudder” or like we as a company, we’re going to tell Google it’s going to freeze tomorrow. 

So I am going to increase my budgets or I’m going to increase my targets so that Google is ready for it. Google has no idea why I am doing this but I’ve done it right, so now the frost happens and boom, I’ve got plenty of bids in so that everyone is looking for a battery sees my ad and I am not running out of advertising budget in the middle of the day when this could have been one of my biggest days of the year for selling these batteries. 

Frank Garza: You talk a lot about, I think mostly about, advertising on Google in the book. Is this book mostly for people who use Google? Or people who do a lot of PPC advertising on places like Amazon, Facebook, and other platforms, will it help them too? 

Fred Vallaeys: Yeah, absolutely. I used to work at Google so that’s what I know best and Google is also still the place where the majority of digital advertising spend is going. I just use that as kind of like the benchmark. It is also when you look at Microsoft Advertising, they copy a lot of what Google [is doing] and then actually, that is not a great work that they love, right? But a lot of the systems are similar for whatever reason. 

I mean you choose keywords, you set bids, you have ads, et cetera, so these concepts that I talk about from the Google ads world translate very nicely to Microsoft and Bing ads. They translate nicely as well to Amazon ads because they have a very similar system in terms of how accounts are structured. When it comes to things like social advertising like Facebook, their concepts are a little bit different and it’s also interesting because Facebook ads came around much later than Google ads. 

A lot of these systems they have in place actually have fewer controls than you would get on a system like Google because they just had better machine learning at their disposal at the time they first introduced ads. What was interesting for me is that in the world of Google, people are looking for books like the one I wrote because they are so used to managing everything manually and it is scary to give up that control and give it to the ad engines. 

Whereas I think on a platform like Facebook, that’s always been the status quo — like just tell us a few things on what you want to achieve and then the system goes and achieves it for you, so that’s a key difference. I think the book is mostly useful for those Google ads, Microsoft ads, and Amazon ads advertisers. 

Frank Garza: I want to ask you a little bit about the process of putting together this book. This is your second one and I’m curious about your experience writing the second one versus the first; things like was it easier, was it more, something is more challenging? Were there learnings from the first one that you could leverage? Could you just talk about the experience of writing the second book versus the first? 

Fred Vallaeys: I think when you write your first book, the whole process is a little bit newer so everything is probably a bit slower I would say. By the second book, you kind of get to the gist of [it]; you write your North Star, you figure out what chapters and the structure and then you start filling in the gaps from there. In that way, I think it is more efficient but I think it is also a bit challenging.

Where it’s less efficient is kind of remembering what did I write and the process of writing a book is funny, right? Because it takes so long, to be honest. You go through it so many times and by the end you’re like, “Did I actually write something that’s interesting?” because you feel like in your own head, you’ve gone through it a thousand times and it’s just like not that exciting anymore. 

Now you get to the second book and the question compounds itself because you’re like, “Wait, did I cover that plenty in the first book and am I doing a disservice to people who read that first book who ended up picking the second book? But I also want the second book to be a standalone, so I do have to repeat some things.” And so I think mentally, those are some of the challenges that you go through as an author. 

I hope I struck the right balance here of taking the concepts from the first book, building on top of them without repeating them too much. 

Frank Garza: Well, congratulations because I know writing a book is such a feat. Is there anything else about you or the book that you want to make sure our listeners know before we wrap up? 

Fred Vallaeys: A lot of these concepts that we talked about in the book we try to support them with the company that we have, Optimyzr, for those advertisers looking to do automation layering and just make your lives a little bit easier. We build a lot of those tools to support that. 

At the same time, I am a big proponent of scripts, which are free so you could certainly read this book and pick up on the concepts and go and build your own free automations from it but I know a lot of people are strapped for time strap for resources. If that’s you, we do have some capabilities to help you with the concepts we described in the book. 

Frank Garza: Fred, this has been such a pleasure. I’m so excited for you and the upcoming book release. The book is called, Unlevel the Playing Field. Besides checking out the book, where can people find you? 

Fred Vallaeys: On Twitter, I am @siliconvallaeys, so spelled like my last name, Vallaeys, Silicon Vallaeys. And then the website is optmyzr.com, Optmyzr — everybody puts in the extra E at the end, there is no E in Optmyzr. So you could find us there and then I speak at a lot of conferences. I’m really hoping that those will pick up again soon. I am scheduled to go to Austin and Munich at the beginning of the year, so fingers crossed those events happen and we all get to see each other in person again. 

Frank Garza: Great, thank you, Fred. 

Fred Vallaeys: Thanks, Frank.