The PPC track at SMX Advanced kicked off with a keynote by Ginny Marvin where she considered the future of an industry where automation is increasingly doing more of the work humans used to do. Her message was that we can’t escape automation so we must find a way to coexist with the machines.
The topic of automation in PPC comes up a lot but I suspect that when our industry talks about the impact of automation, what is considered are mostly automations built by the likes of Google and Microsoft… disruptive (but not necessarily bad) capabilities like Smart Bidding, close variant keywords, responsive search ads, etc.
But nobody ever said that advertisers can’t be disruptors too. They too can build automations to change the game and give themselves a competitive edge.
Having to build your own
Automations from the engines are better with human help
In my new book, Digital Marketing in an AI World, I explain that humans plus machines usually perform better than machines alone. This is not a new concept and one most of you have probably come across in some form or other. One specific example I used to share in presentations came from Wired in 2014 and said that, “The National Weather Service employs meteorologists who, understanding the dynamics of weather systems, can improve forecasts by as much as 25 percent compared with computers alone.”
Because of the potential for better results, PPC pros want to remain involved. They have knowledge about the business that could meaningfully impact results. Sometimes there simply is not enough data for a machine learning system to come up with the same insight. So it’s generally agreed upon that humans + machines can outperform machines alone.
Generally, we tend to translate this concept into the PPC world by saying that account managers need to work together with
the ad engines like Google, the results are generally thought to be better than if the automation didn’t have the help of a smart PPC account manager.
Automations from the engines are better with automations from advertisers
Then I started thinking about the role human PPC managers need to play for the premise to be true that humans + machines outperform machines alone. I realized that the humans in that equation could actually be replaced by machines as well, but in this case, machines that are controlled by the PPC pro and not the ad engine. PPC pros could benefit from the control (since they define the automation) and the time savings (because they don’t need to exert control manually).
So we should try to replace some forms of human control with new layers of automation and see if that delivers the same benefits as humans + machines. If we can write down the steps we take, we can teach a machine to do those steps for us. And it can be a simple rule-based approach which is much simpler to create than something based on machine learning.
The concept behind automation layering is not a new idea. In engineering, solutions can be broken down into systems that can themselves be connected to other systems. Each system accepts inputs and returns outputs and so long as there is agreement over the format of inputs and outputs, many systems can be strung together and work seamlessly together to solve more complex problems.
Likewise, an automation could interact with other automations. In PPC, let’s call this principle “automation layering.” This is an important concept because it’s the next evolution of what PPC pros have been doing for years: using their own insights to control what Google does. But just like Google is getting ever-more automated, our control over it should also become more automated.
that follows their logic, PPC teams can still reap the benefits of having more control over automations created by the ad engines.
Let’s look at why automation layering makes sense in PPC.
Escaping automation is not an option
The reason humans worry about
Despite promising great things, the truth is that success with new automations depends on experimentation and reskilling, both tasks that require time to do well. To take an example from aviation, cutting corners with reskilling when new automations are launched can lead to disastrous results as seen with the 737-Max. Luckily in PPC the stakes are not as high, but I believe the analogy is relevant.
Automation layering for close variants
Some new
Some account managers now spend extra time monitoring search terms triggered for exact match keywords. This would be a great form of human control to turn into automation layering where the PPC manager turns their structured logic for how they check close variants into
There are two specific ways I’ve shared to layer an automation on top of Google’s exact match keywords to keep control when they expand to close variants with similar meaning.
The first way is to simply check the performance of the close variant to that of the underlying exact keyword. If a user-defined threshold for performance is met, it can automatically be added as a new keyword with its own bid, or as a negative keyword if the performance is significantly lower. Note that close variants when used in conjunction with Smart Bidding should already get the appropriate bid to meet CPA or ROAS targets, but regardless it can’t hurt to add your own layer of automation to confirm this.
The second way is to use the Levenshtein distance calculation to find how far the close variant is from the exact keyword. It is a simple calculation that adds up the number of text changes required to go from one word to another. Every character added, deleted, or changed adds one point. Hence going from the correct spelling of my company name “Optmyzr” to the common typo “Optmyzer” has a Levenshtein distance of 1 (for the addition of the letter “e”). Going from the word “campsite” to “campground” on the other hand has a score of 6 because 4 letters need to be changed and 2 need to be added.
With a Google Ads script, we could write our own automation that turns these manual checks into fully automated ones. Because it’s an automation that we can define, it’s as powerful as the more manual human control that we used to have to put in to get the benefits normally associated with humans + machines.
Automation layering for Smart Bidding
Other
The machines are simply better at doing the math that predicts future conversions and using this expected conversion rate to turn an advertiser’s business goals around CPA or ROAS into a CPC bid that the ad auction can use to rank the ad against all others.
That said, remember that Smart Bidding is not the same as automated bidding. Part of the bid management process is automated, but there’s still work for humans to do. Things like setting goals and ensuring measurement is working are just two examples of these tasks.
Besides needing to dial in adjustments for seasonality, special promotions and figuring out how to connect these limited controls to business goals like acquiring new customers, driving store visits or driving higher repeat sales, there’s still the point that most companies care about profits. Despite what we may think after hearing of Uber’s $1 billion quarterly loss, the reality is that most companies don’t have hordes of cash from VCs and a recent IPO so profits are what helps these businesses grow. Curiously, Google Ads doesn’t really have a Smart Bidding strategy geared towards profits.
So it’s up to the human PPC pro to bridge that gap and perhaps add some automation layering. One way to drive towards profitable PPC is to take margins into account when setting ROAS goals.
More profitable items (the ones with higher margins) can have lower ROAS targets. Remember ROAS in Google is “conv value/cost” (i.e., conversion value divided by ad costs). Assuming the conversion value is the cart value of the sale, for an item with a better margin more of that cart value is the product markup. So a lower ROAS can still deliver a profit whereas for items with low margins, less of the cart value is the markup and hence a higher ROAS is needed to break even.
PPC pros could manually assign different products to different smart shopping campaigns with different ROAS targets but that would be tedious and time consuming, especially if the margins for existing products were to change due to promotions and sales events. A smarter solution would be to apply automation layering and use a tool or script that sends products automatically to the right smart shopping campaigns where Google’s automations could take over.
Conclusion
The engines are automating many things we used to have lots of control over because we used to do them manually: from finding new keywords, to setting better bids, to writing ads. But when the people behind the businesses that advertise on Google get a say, results can be better than if the engine’s automation runs entirely on its own.
Just like Google is adding automations, so should you. Use the concept of Automation Layering to your advantage to retain the level of control you’re used to while also saving time by letting the machines do your work.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
About The Author
Frederick (“Fred”) Vallaeys was one of the first 500 employees at Google where he spent 10 years building AdWords and teaching advertisers how to get the most out of it as the Google AdWords Evangelist.
Today he is the Cofounder of Optmyzr, an AdWords tool company focused on unique data insights, One-Click Optimizations™, advanced reporting to make account management more efficient, and Enhanced Scripts™ for AdWords. He stays up-to-speed with best practices through his work with SalesX, a search marketing agency focused on turning clicks into revenue. He is a frequent guest speaker at events where he inspires organizations to be more innovative and become better online marketers.