Stop! Why You Shouldn’t Blindly Implement Google Ads “Recommendations”

Irene Leontari


· PPC Management

Google’s in-platform prompts look reassuringly helpful; with just a few clicks you can increase your traffic and improve your sales. They even dangle an optimisation-score uplift if you click the blue button. But those suggestions are generated by an algorithm whose primary customer is Google, not your business. Treat them as conversation starters, not commandments, and you won’t fall into the trap of overspending for quickly diminishing returns.

What Google’s PPC suggestions really are

The Recommendations and Auto-Apply tabs surface machine-generated tactics ranging from bid-strategy swaps to budget increases. If you opt in to auto-apply, changes can go live every day without any human sign-off. The idea is that it makes PPC campaigns super easy to manage in-house, by someone without much detailed knowledge of the platform. The reality is that it takes control away from the budget holder and puts it directly into Google’s hands.

Three reasons to pause before clicking ‘apply’

  1. Goal misalignment
    Google optimises for platform-level metrics (e.g. higher overall ad spend). Your KPI might be cost-per-sale, profit margin, or lead quality – but Google can’t manage this at the same granular level as someone who fully understands the business. Suggestions that improve Google’s revenue can harm yours.
  2. Insufficient context
    The algorithm cannot see offline returns, seasonal stock issues, or brand-safety nuances. A prompt to broaden match types might ignore that half your calls come from very specific long-tail terms.
  3. Hidden opportunity cost
    Applying Google’s recommendations en-masse removes the control that experienced PPC managers use to test, learn and refine. Once budgets, bids or match types are loosened, clawing them back can take weeks as the algorithm has to re-learn what works.

Here are a few examples we’ve seen recently where Google’s automation has caused issues:

Example 1: PMAX campaigns with no exclusions

A retailer let Google launch a PMAX campaign straight from the Recommendations tab. Because no placement or audience exclusions were set, most of the spend landed on low-intent ad inventory; revenue was flat and the retailer was (obviously) unhappy that Adwords wasn’t working for them.

Example 2: Keyword variants draining budget

Google likes to prompt you to turn on broad-match close variants to expand the reach of your campaigns. Unfortunately, we’ve seen this quickly waste budget on keywords that don’t quite make sense for the business. Broad match is great for testing, but you should be vetting for negative keywords quickly to narrow down what’s actually relevant and what actually converts.

Example 3: Automated budget uplift causing runaway spend

Google also likes to recommend that you raise your budget to avoid throttling campaigns. Just like with broad match keywords, this can quickly balloon spend, without raising leads proportionally in line. Especially for small businesses where budgets might be tight, this can cause a real problem quite quickly.

A quick framework for vetting recommendations

StepWhat to checkAction
1. RelevanceDoes it help your KPI (profit, qualified leads, LTV)?If unclear, reject.
2. Impact sizeUse drafts/experiments to estimate lift vs. risk.Test 50/50 for two conversion cycles.
3. Data sufficiencyWill the change reset learning or split data pools?Apply gradually or segment campaigns.
4. MonitoringSet alerts for CPA / ROAS / impression share swings.Reverse quickly if metrics slide.

Which suggestions can be worthwhile?

Always eyeball them first; even “safe” fixes can clash with brand tone or regulated-industry rules.

Conclusion

Google’s optimisation score and recommendation prompts can make it feel like the account is underperforming, but remember that many auto-suggestions chase spend, not strategy. Treat each prompt as a hypothesis to prove or disprove with controlled testing. By adding human context and commercial common sense, you’ll keep Google Ads working for your bottom line, not the other way round.


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