With Google Ads and Microsoft Ads becoming increasingly automated (whether or not the advertiser likes it), it is advisable not to simply accept and use automation, but also to optimize it.
Wait, how do you optimize automation?
Don't you just push the button to switch to Target ROAS or Smart Shopping campaigns and then sit back and open a cold while the machine does the heavy lifting?
Automation is not about fire and forgetting.
In fact, with troubleshooting and running machine learning algorithms, your job as a babysitter can be more hectic than you expected at times.
In this article, we take a look at the big picture of automation management and analyze the theory behind making decisions so that the tactical process is better controlled.
Here are tips on building the right framework to help you make informed automation decisions.
When it comes to making automation optimization decisions, we are increasingly using what is known as the "magic wheel of automation" pictured below on this cutting-edge and expensive graph (most likely worth millions in NFT).
While a lot of people think automation is something to be set and ignored, barring a little tweak from time to time, I encourage you to think beyond that.
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When it comes to how automation works, it's important to understand that machine learning (ML) is based on the data input it receives.
This means that if the data entries are incorrect, incorrect, unclear, or incomplete, no matter how intelligent that particular algorithm is, the ML algorithm is likely to miss the mark.
Of course, once the automation stops working, we should examine our data entries to make sure it is complete (is your conversion tracking code placed correctly)?
However, I have found that the last two issues that can arise with ML (unclear or incomplete data) are the ones that have the greatest opportunity to realign the machine.
This is where human-led automation comes in.
If your data is unclear or incomplete, it's unfair to blame the machine. Neither man nor machine can make good decisions based on incorrect data (although I suspect that sometimes people are luckier).
Where the magic wheel of automation comes into play
First, it's not magic at all.
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This is my semi-dry sense of humor that comes into play as much as I like to make fun of "hacks" that aren't really hacks – they're just the best course of action.
There's nothing magical about the wheel. You, the human manager, are simply working with PPC automation in a never-ending process that includes these four (five if you count the bonus) steps:
- Discuss strategically.
- Develop a plan.
- Create the plan.
- Analyze the data.
- Repeat endlessly.
If you have a specific problem that you want automation to solve, the first thing you need to discuss is what it is and how you are going to solve that problem.
This involves communicating with your client (or others who can inform this decision) and examining the various aspects of what you want to achieve.
What type of automated bid solution works best in this particular situation based on your data, your customer's goals, and the goals you're trying to achieve?
You then need to translate your strategy into actual steps for which you can achieve what you have created and then you need to create that plan.
As soon as everything is in order with the automation, many people stop here: at the end of step three.
You pat yourself on the back while the automation works now.
But what if your strategy is missing a key component?
What if the automation doesn't work?
Now, instead of stopping here, you need to analyze the data you're getting from your plan (give yourself plenty of time, of course) and most importantly, be ready to have another strategic discussion to rethink and rebuild your automation.
Many people think they did their job because they are using ROAS targeting in this DSA campaign.
What happens if you rethink the structure of the DSA campaign?
What if you choose to have this set of pages separated and instead targeted with a CPA bid strategy?
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If you manage automation well, not only will you never leave your automated campaigns, you will constantly rethink them and test new structures, audiences, bid strategies, and more.
Automation won't take the job away from you. it Changes your work.
Let's play this through practically. Sometimes it's easier to see it in a real-life scenario.
You want to try Smart Shopping on this account, but it doesn't work.
You have tested your conversion data, uploaded complete and accurate audience lists, and achieved enough conversions for these products over time. What are you doing now?
Time to start step 1.
They connect to the client or run an internal audit to see what has to do with these products in order to provide a better subset of the products to be targeted.
Or you can get in touch with the customer to re-discuss the target audience for the various product groups they offer.
This is a tricky step because it is so important, but it can be badly done without the advertiser realizing they are not asking the right questions.
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For example, suppose you plan a strategy with the customer and discover that too many products are being promoted based on their budget.
They had set up a smart shopping campaign targeting 5,000 products with a monthly budget of $ 10,000. In this case it didn't work. You take this knowledge and develop a plan.
They'll take their top 100 products and carefully group them into two separate smart shopping campaigns based on categories (as the audiences for these two categories are very different).
You then create these two campaigns and push them live, ready to crack a cold one.
After you've got things going live, you'll make minor adjustments to budget and ROAS goals, but give the campaigns a few weeks to see what happens.
You start by analyzing the data and learn a few more things.
You will learn that some of the products in that one category are doing exceptionally well, and in the end, you will be pushing this campaign harder.
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You have now learned from this new test that the second category you selected is not a great line of products for shopping campaigns.
Perhaps they are too expensive or not visually appealing enough to get clicks with the dynamic ads in Smart Shopping campaigns.
Regardless of what you learn, choose to test a different set of categories while your first campaign is running. You then speak to the customer and start the strategy for the next test … and you are back at the wheel.
Do you see how that works?
Unlike Thanos who takes a break on his farm, your job is never done. Even with automation, you can't rest (and hey, I'm excited about it!).
Human-led automation is the future, and this is one way to manage it well in a process-oriented manner.
I hope this has been helpful to you and may the auction ever work in your favor!
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Screenshot by the author, March 2021.