AI and Advertising: When to Trust Automated Recommendations
Play • 14 min

The Matrix, The Terminator, and Google Ads have one thing in common: AI that can both help and harm you depending on the situation. Many advertising platforms in recent years have become more aggressive regarding automatic recommendations powered by machine learning. These suggestions ideally should help your campaigns, but in most instances they don't. Smaller suggestions can be effective: platforms might tell you to remove an underperforming keyword or remove a negative keyword that prevents ads from showing for your main keywords. Despite our experience with invasive suggestions being useless at best, they should not be completely ignored. The ultimate goal of the machine learning behind these recommendations is to produce better results. Though infrequent, on occasion automated suggestions do find optimization opportunities. In many ways, platform representatives are not so different. Most of the time they echo the AI auto-recommendations, though this is not true with all reps. It is important to know how to distinguish good advice from bad advice while navigating the potential social pressures that may make you want to agree with a rep regardless of the story your data tells. Unlike auto recommendations, there are several unique benefits that reps provide, including access to inside information. It's important to remember your goals and the goals of the advertising platforms may not align. You (or your digital advertising agency) are ultimately responsible for getting the most return on your ad budget.

In this week's Digital Marketing Mondays, Hans and Devin discuss how to navigate recommendations from advertising platform AI and representatives to best optimize your campaigns.

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