MGWM

Why PPC Is A Long Game, Too

Table of Contents

Okay, we’re throwing this out into the crowded abyss of content that attempts to answer the question “How do I optimize Google Ads performance?” Because there are a lot of “tips,” even more “tricks,” and a few things “you won’t believe you missed” out there. And, well, we’re writing this, so you can guess what we think of a lot of it.

Let’s answer this question once and for all.

How do you optimize your Google Ads account?

Slowly.

(Hey, GoogleBot, if this article gets a featured snippet, can that be it, please?)

There is no magic tactic that will solve your plummeting impression share or cascading conversion rate. Even with all of your research, running a solid paid media campaign takes time and planning. And maintenance. And patience. And a lot of CSVs (like a lot of CSVs). 

But somewhere along the way, people got it in their heads that you flip a switch, “run google ads,” and then make money. 

Any ‘SEO v. SEM’ comparison will tell you SEM is faster than SEO. It’s true. You can boost traffic and conversions right away with ads. But that focus on speed and short-run performance is based on a misconception, and that immediacy mindset is hurting PPC specialists by creating pressure for instant results that just won’t always be there

We wish a Google Ads account could jump right up to a consistently high return. In practice, however, banking on short-run performance can result in some pitfalls we would all do well to avoid

I think it’s time we start talking about PPC as a paced-out and strategic long-con. And there are a few reasons taking your time, spending deliberately, and implementing your PPC strategy over quarters is more effective than opening the floodgates and cruising right up to your max budget in a week or two.

As you’ve probably guessed, we’ll walk through them below.

Here’s where we stand:

  • Smart Features Take Time To Work
  • A Full-On Assault Is Expensive
  • Launching Everything At Once Is Hard To Manage
  • Crawl Before You Run

Smart Features Need Data And Data Takes Time.

Most advertisers are probably not setting bids 100% manually. Respect if you are, but Google has been pushing ‘Smart’ features hard recently. Nearly every available bid strategy uses Google historical data to maximize campaign performance.

Call it the age of automation, the predictive marketing era, or whatever LinkedIn has dubbed the last few years, but the marketing world is facing a rush of demand for data-driven, smart campaigns and machine-educated features.

The thing with automated features is that they take time to work. Every algorithm considers historical performance data. And, well, if there is no historical data, then you and Google are pretty much just grasping for relevant signals. 

Which is to say if you train your bid strategy during a time of inconsistent or atypical search behavior, say, over a holiday weekend or at the beginning of a global pandemic, you’re training an algorithm to pick up on and adjust bids based on signals that might not be your best long-run predictors of performance. 

Granted, the automations are pretty hearty, and they learn fast. Four months into the COVID-19 pandemic, we’ve seen them handle some pretty volatile conditions. But the key takeaway is that it takes more time than just the bid strategy “(learning)” phase to get the most out of automation. In the face of volatility, a new automated bid strategy will not perform as well as one that’s had a bit more time to learn in the long run. 

Knowing this, we should consider how performance will improve over time and allocate budgets accordingly. Why would we spend our entire budget to teach an algorithm, when we know it won’t get us the result we want right away?

Our rule of thumb is it generally takes about 3 months until an account begins to hit its stride. This is not set in stone, but it’s a benchmark we use for our strategic planning.

In this time, the Google algorithms will be collecting data and learning how best to optimize your campaign. And you should be learning too. You should be monitoring spend and conversions and considering the best way to spend your customers’ budgets.

While we’re on the topic of budgets...

I Hate Spending Money. You Should Too.

Let me clarify. I hate spending too much money for too little in return. If we’re getting consistent results and crushing our return goals, I’ll spend all day.

Even after you’ve done your research and launched your campaigns, rushing right to your maximum budget may hurt you. If only because neither you, nor Google, really knows how your landing pages, the competitive set, or any of your ads will perform.

Like we said, the early phases of an account are focused on learning and are usually light on conversions. Which is why it makes sense to phase-in your budget as you learn what works.

Take this graph of return on ad spend and total cost from a B2C cleaning product company. Return is the blue line (left axis), and cost is red (right axis). Note the steady increase in return between Q1 2018 and Q4 2019.

Also note the gradual spend increase between Q1 and Q3 of 2018. 

Some reading this will respond with, “but what if our client needs to spend their budget right away.” To which I respond: no they don’t, and they probably shouldn’t. There’s no need to rush to spend money for the sake of spending money. 

A gradual budget phase-in gives you time to test the waters. And it gives Google time to learn at a pace and a budget you're comfortable with. You can get cheaper answers to the big questions like:

  • How are my keywords performing?
  • Is spend going to the best ad groups?
  • How much does it actually make sense to spend on these terms?

And you don’t have to answer the questions like:

  • Why are we spending so much?
  • Where are the conversions?
  • Why did you pick these keywords?

This approach lets you cruise right up to the sweet spot, without wasting time or spend. It also lets you make sure you’re putting your best campaigns forward, and it gives you time and capacity to test as you optimize. 

Don’t Roll Out Every Campaign At Once, Either

I had an English teacher in middle school who described writing an intro paragraph for an essay like fighting a robber that broke into your home.

“You wouldn’t go after them with a spoon, would you? No. Go for the big guns right away.”

The same applies to PPC.

By the time you’re ready to launch, you’ll have a hunch about your top performing campaigns. You’ll know which ones strike that perfect balance between cost, competition, and volume, and you’ll know which are long-shots. 

Lead with your best, most-informed campaigns. To beat a metaphor, these are your intro paragraphs. They get you, the client, and Google hooked on a steady stream of data and performance. And they tell you what you need to know about how your strategy will (or won’t) work.

There’s still a rhythm to testing new campaigns. You launch, monitor, and adjust until everything is going along smoothly and conversions start to flow in. Then you let it run, re-visit, and tweak. Then you continue on to your next test. 

But the last thing you want is to launch every campaign at once and to find yourself constantly checking and course-correcting an onslaught of new campaign growing pains. It’s expensive. It’s hard to manage. And ultimately, it’ll cost you. 

Crawl. Walk. Run.

That’s all well and good, but here’s how it looks in practice: a Google Ads strategy broken into three phases.

The Crawl Phase: Learning

With Google relying more and more on automated features, the first 1-to-2 months of your engagement are about understanding how your account will perform. In the crawl phase, you launch your best-bet campaigns at a lower budget and figure out where you sit in the auction. This is also where you identify the consistent pain points that will (and believe me, they will) pop up over and over throughout the life of your campaign.

Your goal is to understand the following:

  • How much are actual CPCs? Are they higher or lower than forecasted?
  • Who are our key competitors on these terms?
  • What components of quality score limit us?
  • What creative and messaging seems to do the best?

And as you learn and get more confident in the campaign, you allocate budget accordingly.  

The Walk Phase: Tweaks & Optimization

Around the second-or-third month, when performance is in a consistent place, and budget is at or below your cruising altitude, you’re ready to start testing. 

In the walk phase, you make changes based on your learnings. You’ve got a baseline for performance, and you’ve got insights into which levers you need to pull. This means you can start to focus efforts on:

  • Ad copy & landing page tests
  • Bid adjustments for top-performing audiences
  • Additional campaigns & ad group rollout
  • New or adjusted keyword sets

The goal is fine-tuning your account structure. You want to adapt your campaigns, ad groups, keywords, and ads to get the most out of them. And you want to set the stage for a long-run paid media plan that can really support your client’s business.

The Run Phase: Tests & Ongoing Maintenance

In the run phase, our goal is to keep paid search driving consistent traffic, leads, or revenue at our monthly budget. This is where long-run thinking comes into play. We can take our learnings from the walk and crawl phase and use them to identify new opportunities, support new business initiatives, and generally help businesses grow on search. 

That means focusing on maintaining a steady, if not growing, return through the following:

  • Continually testing new copy and landing pages
  • Keeping eyes out for new opportunities.
  • Supporting business-wide promotions and new initiatives.
  • Consistent, periodic audits

That sets your paid search efforts up to make a genuine impact on your clients in the long run, which is more than a handful of clicks and conversions over a short few months.

Conclusion

Somewhere along the way, people got it in their heads that paid search was something you can flip on or off more-or-less ad hoc with few consequences.

That may well have been the case when bids were manual and smart features weren’t constantly collecting data. But now, with our algorithmic overlords running the game, that’s not the case. 

Our paid search strategies need to reflect an understanding of how algorithms -- and frankly people, too -- learn. That’s why, when expectations are shaped by immediate promises for faster results and higher performance, it actually makes more sense to slow down and plan for the long run. 

You and Google both need data to optimize campaigns. And you want to allocate your budget in the most efficient way. The fact of the matter is that we need to plan for built-in learning and testing periods to optimize Google Ads for real business impact.

This means taking your time to iterate and learn over months, not weeks. It means setting a plan in place to build and fine-tune an account that grows and adapts to insights, not one built on short-term, fleeting signals. 

So the next time someone comes to you asking to, “run google ads,” you sure as hell better ask them if they know how to walk first.

John Smith

John Smith

John is a Paid Media Manager at Uproer, where he works to build paid search strategies for clients in the e-commerce and SaaS spaces. He's drawn to the ideas, channels, tactics, and emerging trends that tackle big issues in marketing. And he approaches SEM with a focus on data privacy, incrementality, and social impact. When he's not knee-deep in a spreadsheet, John volunteers with local climate organizations and helps spread their message through search.

See More Insights

How to Mimic Googlebot with Screaming Frog

Wouldn’t it be great to know exactly how Googlebot is crawling your website? Unless you have the keys to the kingdom, you won’t get perfect information. But, we can get close! Screaming Frog has nearly limitless configurations for just about any SEO use case you can imagine. This article presents

Read More

In a Rut? Try Our Pivot Method to Lift Traffic By 30%

Repotting helps remove dead roots and gives your plants more nutrients and space to grow. If you don't repot your growing plant, it will struggle to survive. I'm not a horticulturist, but I do know that a content strategy pivot is like repotting a plant. A content strategy pivot consists

Read More
MGWM

Director of Operations

Dave Sewich

dave sewich

Dave made an accidental foray into digital marketing after graduating from the University of Minnesota Duluth and hasn’t looked back. Having spent the first part of his marketing journey brand-side, he now works with the Uproer team to help clients realize their goals through the lens of search.

When not at work, you’ll find Dave staying active and living a healthy lifestyle, listening to podcasts, and enjoying live music. A Minnesotan born and raised, his favorite sport is hockey and he still finds time to skate once in a while.

Dave’s DiSC style is C. He enjoys getting things done deliberately and systematically without sacrificing speed and efficiency. When it comes to evaluating new ideas and plans, he prefers to take a logical approach, always sprinkling on a bit of healthy skepticism for good measure. At work, Dave’s happiest when he has a chance to dive deep into a single project for hours at a time. He loves contributing to Uproer and being a part of a supportive team but is most productive when working solo.

Founder & CEO

Griffin Roer

Griffin discovered SEO in 2012 during a self-taught web development course and hasn’t looked back. After years of working as an SEO consultant to some of the country’s largest retail and tech brands, Griffin pursued his entrepreneurial calling of starting an agency in May of 2017.

Outside of work, Griffin enjoys going to concerts and spending time with his wife, two kids, and four pets.

Griffin’s DiSC style is D. He’s driven to set and achieve goals quickly, which helps explain why he’s built his career in the fast-paced agency business. Griffin’s most valuable contributions to the workplace include his motivation to make progress, his tendency towards bold action, and his willingness to challenge assumptions.