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.

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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instead of confirming them, and why staying curious and open to being wrong gets better results than clinging to outdated strategies.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.

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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.

Today's question is whether you should remove email signup popups from landing pages when sending paid Meta traffic to them. Popups don't technically violate Meta's rules, but they can contribute to bad post-click experiences that drive up your costs if they hurt bounce rate or dwell time. Jon explains how Meta measures ad quality through landing page experiences, when popups become a problem versus when they might be fine, and why you should test a version without the popup to see what actually works.

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Advertisers have a tendency to overcomplicate their campaigns with multiple ad sets, restricted targeting, removed placements, and turned-off enhancements, often without clear reasons for these decisions. Jon challenges you to audit your current campaigns and question every piece of complexity you've added by asking why you made each decision, what problem you were solving, and whether there was a better solution that didn't require watering down your budget or limiting Meta's optimization.

Today's question is about campaign structure for seasonal products, specifically whether to split major holidays into separate ad sets with spending limits. Seasonal businesses face a unique challenge of running evergreen products year-round while also promoting holiday-specific items for limited periods. Jon explains how to structure a CBO campaign with multiple ad sets for different seasons, when to turn seasonal ad sets off based on performance, and whether ad set spending limits are actually necessary or just adding unnecessary restrictions.

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Advertisers blame Meta when their leads are low quality, pointing to the algorithm exploiting weaknesses like age range or placements to get cheap conversions. But the real problem with lead quality usually has nothing to do with Meta or your ads. Jon explains why your follow-up process, email deliverability, sales team, and automation are what actually determine lead quality, and the specific steps you need to take to make sure real leads don't get ignored or lost in spam folders.

Today's question is why campaigns stop working after two or three weeks when the ads generated sales initially and there's no ad fatigue. Meta starts by showing ads to low hanging fruit, the people most likely to convert, which often includes your remarketing audience even with algorithmic targeting. Jon explains why this group gets exhausted quickly, how audience size and product niche affect the drop-off, and why it's not normal to go from great performance to bad performance if your fundamentals are solid.

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