Thanks, But No Thanks: When Recommendations Don't Help

Logging into any ad platform lately means getting bombarded with popups and notifications. You get used to it, and dismiss them without thinking, like Neo in The Matrix.

One of the usual offenders is automated recommendations. Designed to look helpful, they point out opportunities to enable unused features, usually with the goal of taking up cheaper ad space, yielding targeting/creative control, or simply spending more money. They insist these are not recommended frivolously, but as best-practices to improve your results from advertising online.

Is it as cut-and-dry as that?

Talk to anyone who spends a significant amount of time in Google Ads, and they will have some opinions on this. Some will say the automated recommendations are something to be, at best, selective about, and at worst, completely disregarded.

Here are two examples of automated recommendations in Google Ads which, we would argue, are rarely beneficial to adopt. These are closely related; both dealing with search keywords, and both done in the name of simplifying campaign setup… but how do they affect search campaign performance? Let’s explore.

Recommendation 1: Remove Non-Serving Keywords

Their rationale: you’re targeting a keyword that is low volume, so much so that it rarely shows up at all, meanwhile you’re also targeting keywords that are searched all the time. Forget the low volume keyword, strengthen your presence where there is more activity.

Our counterpoint: we’re targeting that keyword because it’s valuable, not because it’s common. It doesn’t cost us any money while it lies in wait (shout out to pay-per-click), so there’s no downside to leaving it on for if/when that search comes along.

Example: a high-end luxury car.

Dealership websites typically have useful showroom pages, where customers of the most rare vehicles they sell can get information and contact to order. Even if the dealership doesn’t carry that vehicle in stock all the time, it’s absolutely available, and they want to attract its buyers.

Just because a keyword is rare doesn’t mean you don’t want to capture it. The opposite is true; you want to show up with a highly tailored ad addressing that specific keyword rather than miss your chance to get in front of the potential customer. Google is eyeing the budget you have reserved for this keyword in case it gets triggered on occasion, hoping you’ll instead add it to the daily amount you spend on your busier campaigns to ensure they get that money.

Verdict: thanks for the advice, but that keyword stays on.

Recommendation 2: Remove Redundant Keywords

Their rationale: some of the keywords you are targeting are variations of essentially the same thing. The system can figure out the intent of what you - and the users searching - are trying to do, so it would be simpler to consolidate, run with just one keyword, and not fragment your efforts.

Our counterpoint: we want data to see not only which variations perform better, but to observe how customers talk, which allows us to either align with their language, or correct their misunderstanding for branding purposes.

Example: a grocery store named “Superstore”.

Google will tell you that including both “superstore” and “super store” in your targeted keywords is adding unnecessary clutter, and the customer probably means the same thing, so just go with one and let them serve the same ad in both cases.

However, the advertiser could recognize this as an opportunity to still attract those customers who got the name slightly wrong, and enforce the proper name, staying consistent to build familiarity. They could even get cheeky with it and address the misspelling in the ad copy, adding in humor and disrupting that user out of their routine.

Verdict: thanks again, but no, we’ll keep that too..

So What?

All digital advertising platforms have their own systems of automated recommendations, and not everyone takes a step back to determine if opting into every feature adds real value, instead of just noise or filler.

Of course, these are always presented as objectively beneficial, even grading advertisers with an “optimization score” which is not a reflection of performance, but how closely they are adhering to the default best-practices.

The problem with best-practices is that it’s debatable for whom the outcome is “best”.

Any recommendations made by the ad platforms need to be tested, with good tracking & data sample sizes, to see what actually works in your favor.

That’s our job. One of the main benefits of working with an agency like IBA is tapping into our years of digital advertising experience working with clients in different markets, industries, and budget sizes. Our decision-making balances the testing of cutting-edge new features with decisions rooted in solid data. Even if you’re starting fresh, that experience is in your corner.

Let us help navigate which features might actually benefit you, not just spend your marketing budget indiscriminately. Learn more about what makes us tick here, or get in touch with us any time!