Does Manual Bidding Actually Work?

Today's question is whether to launch a brand new campaign with creative testing or start testing later with new creatives. There's no absolute right answer, but Jon has a preferred approach with clear reasoning behind it. He explains why starting new ads with a test answers questions you'll have later, avoids the messy workaround of duplicating existing ads, and ensures you get meaningful data from the start. Want your question to be answered on a future episode? Go to JonLoomer.com/Question and record your question today.

Ads that were working fine suddenly tank, and advertisers assume Meta changed who they're showing ads to or messed up delivery. But there's usually a simpler explanation. Jon breaks down the five real causes of sudden performance drops, including randomness, competitive variables, website issues, and event delays, and why obsessing over daily results drives you crazy when seven-day averages are what matter.

Today's question is about using manual bidding like cost caps to control costs while scaling budget when campaigns perform well. By default, Meta tries to get the most results while spending your entire budget, which means a mix of auction costs. Jon explains why setting manual bid controls usually leads to inconsistent delivery and questionable quality, how it might restrict you to low-quality placements, and why outsmarting the algorithm rarely works. Want your question to be answered on a future episode? Go to JonLoomer.com/Question and record your question today.

Most advertisers obsess over targeting inputs that either do nothing or actively hurt results. Jon explains why he ignores audience suggestions, age restrictions, detailed targeting, and lookalikes entirely, how he uses value rules to handle demographic problems instead, and why the only inputs worth touching are locations and exclusions.

Today's question is about testing different customer personas using the creative testing tool. Advertisers used to create separate ad sets for each persona with adjusted targeting, but that's outdated now. Jon explains why all customer personas can exist in one ad set, how Meta finds the right audience for each ad combination through creative diversification, and when splitting by persona actually makes sense versus when it's unnecessary complexity. Want your question to be answered on a future episode? Go to JonLoomer.com/Question and record your question today.

Audience suggestions cause confusion because advertisers think they're tight constraints when they're not. Jon proposes how Meta could eliminate suggestions entirely while keeping audience controls like location and exclusions. The result would strip away the illusion of control, prevent mistakes based on false assumptions, and force advertisers to focus on what actually matters without pretending inputs do more than they do.

Today's question is about determining what works from top performing ads to inform the next batch of creative. Creative testing used to isolate single elements, but now ads generate thousands of combinations through text options, placements, and enhancements. Jon explains why finding one winning combination isn't the goal anymore, how to use the creative testing tool to identify themes instead of specific winners, and why success comes from many winning combinations in aggregate. Want your question to be answered on a future episode? Go to JonLoomer.com/Question and record your question today.

Advertisers believe something works and only pay attention to evidence supporting it while ignoring contradictions. They blame Andromeda or the algorithm when strategies stop working instead of questioning their assumptions. Jon explains why confirmation bias makes experienced advertisers the worst offenders, how to test beliefs instead of confirming them, and why staying curious and open to being wrong gets better results than clinging to outdated strategies.

Today's question is about preventing customers from purchasing the same audiobook bundle twice through ads. Excluding customers is a balance of risks versus benefits, and no single custom audience catches everyone. Jon explains why you should exclude multiple custom audiences including website purchasers and email lists, how to improve match rates, and why keeping audiences dynamically updated limits repeat purchases. Want your question to be answered on a future episode? Go to JonLoomer.com/Question and record your question today.

Audience suggestions feel like control, but Meta ignores them constantly, especially for age and gender. There's no proof they impact detailed targeting or lookalikes, yet they cause confusion and wasted effort creating multiple ad sets. Jon explains why Meta should eliminate audience suggestions entirely, how the illusion of control hurts results, and why you'd be better off without them.