We marketers can be a sensitive bunch. And if we screw up, we have exactly the skills required to spin the situation in our favor, as you may have noticed. But we mean well, and generally, we’re pretty good at our jobs.
Even so, we get lost in the weeds frequently. Only a few of us have statistics backgrounds, and we necessarily live in a world of overlapping and confusing inputs and outputs. As a result, even if we do a great job in general, the most basic performance issues can sometimes slip by us, obscured by the noise, both statistical and metaphorical, inherent in today’s frenzied retail environment.
Our more numbers-driven colleagues can help keep us on the rails with a little financial oversight. And as it turns out, two of the most common macro issues that affect direct-to-consumer retailers’ Google Ads accounts are easily spotted by non-marketers.
If the overall return on your holiday ad spending — that is, revenue/costs or return on ad spend (ROAS) — wasn’t in line with expectations, I’m certain you’re already aware. But don’t just look at the top line. Both of the issues I’ll discuss here are relative, indicating inefficiencies or imbalances in how funds are spent. They’re common problems that tend to afflict one segment of the account at a time, and therefore get averaged out by the time they land on the top-line P&L.
So, assuming your overall Google Ads marketing channel behavior is as you’d expect, it’s time to dig deeper. Here are the two most insidious issues that I see sneak into ecommerce search campaigns, and how you can identify them in the wild.
Marketers have a lot of (very loud) opinions on search terms that include your brand, domain, trademarks and/or related words. For our purposes, we’ll leave that debate aside, because we’re interested in the other traffic — that generated by searches that are relevant to your product but don’t include your brand terms. For example, searches for “nike running shoes” include the Nike brand, whereas searches for “running shoes” do not, and they behave very differently. While specific strategies will vary from company to company, the foundation we should all build on is the assumption that you should make money on each sale. Maybe you have a loss-leader, or some recurring revenue model, or other variation. That’s fine. It moves the center of the target a bit, but it doesn’t change the game.
If brand terms manage to sneak out of their pens, they can boost the apparent performance of the campaigns that they wander into, potentially obscuring unprofitable campaign behavior. How can we check for that? Go straight to the underlying data.
Within your Google Ads account, go to “Keywords” on the left bar, and then “Search Terms” on the top bar. You can then create filters that exclude your brand, like so:
In the table, you will see the remaining search terms after your filter is applied. If there are variations on your brand — say, with or without spaces, or common alternative spellings or misspellings — add more filters to further refine the results. You don’t need to get too aggressive with these filters, though, as this particular affliction will pop out very quickly if even a handful of exceptions slip through.
Next, we’ll pick our date range, for example, “Q4 2019,” and our columns. You’ll need at least the “Cost” column and the “Conv. value” column, which is essentially revenue. There will be a light-gray row for “Total: Filtered search terms.” That will give us the total non-brand spend and revenue for the period.
For example, we might see this:
If you expected a ROAS of 3.50x on this non-brand campaign activity, as this client was, then fantastic! If, however, your margins were only 20%, then spending ~26.6% of revenue on any slice of traffic is hurting your overall performance.
If there was another million in brand revenue in this account, you can see how that would quickly sweep a loss under the rug.
My fix: Compare your non-brand ROAS to your margin constraints. If the marketing campaign is afflicted with this particular infection, you’ll spot it quite easily.
If you’re a direct-to-consumer retailer, brand searches are generally a large portion of overall Google Ads account activity. If your marketing team is using Smart Shopping campaigns, which are highly automated by Google, you won’t have access to the search-term data for that part of your account. That might blunt the efficacy of this spot check.
The next spot check, on the other hand, will work regardless of any Smart Shopping campaigns your team is running.
Mobile clicks typically aren’t worth as much as desktop clicks. Why? Google has a lot more mobile user impressions to sell than it does desktop ones. But these mobile users don’t buy as often. So that mobile traffic — even with multi-device attribution and other tracking tricks — is worth less than desktop traffic. In some accounts, the value difference can be dramatic.
Fortunately, there are features in Google Ads that allow marketers to shape their investments across devices. If one segment of traffic is worth twice as much as another, then you’d expect to spend twice as much to earn it.
The result would be a relatively similar ROAS across device types.
If your campaign fails to account for that difference in conversion behavior and uses the same bids, regardless of the device the potential customer is browsing on, then that campaign will be left holding the bag when your competitors don’t make the same mistake. You’re paying full price for a bunch of discount-bin traffic.
In the worst instances of this mistake, mobile clicks will balloon, gobbling up more and more of your total budget. In some cases, I’ve seen an account that should have been spending about 40% of its budget on mobile burning more than 80% on that segment. Not only were they losing money on mobile clicks, they were underspending on the more valuable — that is, likely to convert into sales — computer segment.
To detect this issue, create a quick custom report. Start by going to the “Reports” tool in the top bar:
Create a new “Table” report, then grab “Device” from the parameter search on the left:
Then, still using that search, grab “Cost” and “Conv. Value,” and drag those into the report.
I also like to include “conv. Value / cost” to make it even easier to read the results. Verify your date range, and you should get something like this:
There’s usually some variability in the ROAS, but it should be fairly minor. When you spot a difference that’s a factor of two, though, you have a problem. If Desktop had a ROAS of 5.77, but Mobile ROAS was only 1.82, it would be a textbook example of this problem. In that hypothetical case, not only would the ROAS on Mobile be ugly, these clicks would have gobbled more of the overall budget, shoveling cash into Google’s coffers with, statistically, few sales for you.
My fix: Verify that your ROAS is roughly consistent across device types, especially over long periods of time.
There are a few exceptional cases where these patterns might be justified, but not many. As a result, if you find them, they almost certainly warrant a conversation with your CMO. Expect a great reception — after all, once marketing fixes the problem, their performance should be even better!
Roy Steves is co-founder of StatBid, a paid search agency specializing in eCommerce. He began his career as a web developer, first with the company that’s now Build.com, and later with an online pool supplies retailer, PoolSupplyWorld. At that company, he realized that there was a lot of opportunity in Google AdWords, and that it seemed like success should just be a matter of applied algebra. After adding 30% to the business in the first year, and doubling it by the second year, Roy migrated from engineering to CMO by the third year.
PoolSupplyWorld’s explosive growth led to an acquisition by Leslie’s Poolmart, a national retailer with over 900 stores in 35 states, and a new role for Steve as VP of digital marketing. After successfully integrating the two teams, Roy started StatBid as a vehicle for talking shop and helping more businesses capitalize on the opportunity in paid search.