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What youre about to read is not actually from me. Its a compilation of PPC-specific lessons learned by those who actually do the work every day in this age of machine learning automation.

Before diving in, a few notes:

Its simple, a machine cannot optimize toward a goal if there isnt enough data to find patterns.

For example, Google Ads may recommend Maximize Conversions as a bid strategy, BUT the budget is small (like sub $2,000/mo) and the clicks are expensive.

In a case like this, you have to give it a Smart Bid strategy goal capable of collecting data to optimize towards.

So a better option might be to consider Maximize Clicks or Search Impression Share. In small volume accounts, that can make more sense.

The key part of machine learningis the second word: learning.

For a machine to learn what works, it must also learn what doesnt work.

That part can be agonizing.

When launching an initial Responsive Search Ad (RSA), expect the results to underwhelm you. The system needs data to learn the patterns of what works and doesnt.

Its important for you to set these expectations for yourself and your stakeholders. A real-life client example saw the following results:

As you can see, month two looked far better. Have the proper expectations set!

Many of us whove been in the industry a while werent taught to manage ad campaigns the way they need to be run now. In fact, it was a completely different mindset.

For example, I was taught to:

Any type of automation relies on proper inputs. Sometimes what would seem to be a simple change could do significant damage to a campaign.

Some of those changes include:

Those are just a few examples, but they all happened and they all messed with a live campaign.

Just remember, all bets are off when any site change happens without your knowledge!

The best advice to follow regarding Recommendations are the following:

Officially defined as the impressions youve received on the Search Network divided by the estimated number of impressions you were eligible to receive, Search Impression Share is basically a gauge to inform you what percentage of the demand you are showing to compete for.

This isnt to imply Search Impression Share is the single most important metric. However, you might implement a smart bidding rule with Performance Max or Maximize Conversions and doing so may negatively impact other metrics (like Search Impression Share).

That alone isnt wrong. But make sure youre both aware and OK with that.

Sometimes things change. Its your job to stay on top of it. For smart bidding, Target CPA no longer exists for new campaigns. Its now merged with Maximize Conversions.

Smart Shopping and Local Campaigns are being automatically updated to Performance Max between July and September 2022. If youre running these campaigns, the best thing you can do is to do the update manually yourself (one click implementation via the recommendations tab in your account).

Why should you do this?

This doesnt need to be complicated. Just use your favorite tool like Evernote, OneNote, Google Docs/Sheets, etc. Include the following for each campaign:

There are three critical reasons why this is a good idea:

Imagine youre setting up a campaign and loading snippets of an ad. Youve got:

Given the above conditions, do you think it would be at all useful to know which combinations performed best? Would it help you to know if a consistent trend or theme emerges? Wouldnt having that knowledge help you come up with even more effective snippets of an ad to test going forward?

Well, too bad because thats not what you get at the moment.

If you run a large volume account with a lot of campaigns, then anytime you can provide your inputs in a spreadsheet for a bulk upload you should do it. Just make sure you do a quality check of any bulk actions taken.

Few things can drag morale down like a steady stream of mundane tasks. Automate whatever you can. That can include:

To an outsider, managing an enterprise level PPC campaign would seem like having one big pile of money to work with for some high-volume campaigns. Thats a nice vision, but the reality is often quite different.

For those who manage those campaigns, it can feel more like 30 SMB accounts. You have different regions with several unique business units (each having separate P&Ls).

The budgets are set and you cannot go over it. Period.

You also need to ensure campaigns run the whole month so you cant run out of budget on the 15th.

Below is an example of a custom budget tracking report built within Google Data Studio that shows the PPC manager how the budget is tracking in the current month:

Devote 10% of your management efforts (not necessarily budget) to trying something new.

Try a beta (if you have access to it), a new smart bidding strategy, new creative snippets, new landing page, call to action, etc.

If you are required (for example by legal, compliance, branding, executives) to always display a specific message in the first headline, you can place a pin that will only insert your chosen copy in that spot while the remainder of the ad will function as a typical RSA.

Obviously if you pin everything, then the ad is no longer responsive. However, it has its place so when you gotta pin, you gotta pin!

Its simple: The ad platform will perform the heavy lifting to test for the best possible ad snippet combinations submitted by you to achieve an objective defined by you.

The platform can either perform that heavy lifting to find the best combination of well-crafted ad snippets or garbage ones.

Bottom line, an RSA doesnt negate the need for skilled ad copywriting.

If youve managed campaigns for an organization in a highly regulated industry (healthcare, finance, insurance, education, etc.) you know all about the legal/compliance review and frustrations that can mount.

Remember, you have your objectives (produce campaigns that perform) and they have theirs (to keep the organization out of trouble).

When it comes to RSA campaigns, do yourself a favor and educate the legal, compliance, and branding teams on:

To use an automotive analogy, think of automation capabilities more like park assist than full self driving.

For example, you set up a campaign to Bid to Position 2 and then just let it run without giving it a second thought. In the meantime, a new competitor enters the market and showing up in position 2 starts costing you a lot more. Now youre running into budget limitations.

Use automation to do the heavy lifting and automate the mundane tasks (Lesson #11), but ignore a campaign once its set up.

This is related to lesson #5 and cannot be overstated.

For example, you may see a recommendation to reach additional customers at a similar cost per conversion in a remarketing campaign. Take a close look at the audiences being recommended as you can quickly see a lot of inflated metrics especially in remarketing.

You have the knowledge of the business far better than any algorithm possibly could. Use that knowledge to guide the machine and ensure it stays pointed in the right direction.

By some accounts, Im mostly referring to low-budget campaigns.

Machine learning needs data and so many smaller accounts dont have enough activity to generate it.

For those accounts, just keep it as manual as you can.

Speak with one of your industry peers, and youll quickly find someone who understands your daily challenges and may have found ways to mitigate them.

Attend conferences and network with people attending the PPC track. Sign up for PPC webinars where tactical campaign management is discussed.

Participate (or just lurk) in social media discussions and groups specific to PPC management.

Many of the mundane tasks (Lesson #11) can be automated now, thus eliminating the need for a person to spend hours on end performing them. Thats a good thing no one really enjoyed doing most of those things anyway.

As more tasks continue toward the path of automation, marketers only skilled at the mundane work will become less needed.

On the flipside, this presents a prime opportunity for strategic marketers to become more valuable. Think about it the machine doing the heavy lifting needs guidance, direction and course corrective action when necessary.

That requires the marketer to:

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21 PPC lessons learned in the age of machine learning automation - Search Engine Land