@Jake Roper would you be open to sharing your best low ticket offer ad campaigns?

Here's what I'm currently doing but I see many service-based leaders running a different campaign structure, I'll go over both below: OUR STRUCTURE: CBO -> Broad Adset (Per concept*) -> 5 Ads *Each concept contains 5 ads / and we create around 6/8 concepts per month for a client That's it, so it would be a single CBO with around 10 adsets with 5 ads each - then we put the winners inside another adset and the campaign works as both scaling and testing, this is what we use but I feel like this is more of an eCommerce approach. Everything optimized for qualified calls NOW HERE'S WHAT I SEE FROM OTHERS: CBO -> 3 Adsets (Broad/Interests/LLAs) -> As many ads as you have Why do I feel like I need to change this approach? Well in B2B SaaS calls are more expensive and obviously you need to spend more money and at the same time, in different mentorships they push this structure as well.

Just launched my ads today. I understand results take time and that losses happen before the upside, so I’m not expecting instant ROI. But I want to make sure I’m testing creatives the right way from the start. Right now I’m thinking: - Use my TOF campaign as the testing ground. - Create new ad sets and load different creatives into them Is that the correct approach for testing? Or should I structure it differently? Also, how do I clearly identify a winning creative? What metrics or signals should I be looking for early on to know something is worth scaling? And once I find winners: - Do I create a new campaign, run 1 ad set, stack all winning creatives inside, and switch to CBO for scaling Or is there a better structure to scale efficiently? Would appreciate any guidance on how you’d approach testing → identifying winners → scaling properly.

@Jake Roper in your Adstra content system Notion doc, you show a tool where you are tracking a user clicking an ad and then retargeting to a Youtube video. I believe that tool is Hyros. Does Hyros track Youtube view to retargeting facebook ad, so the other way around? Also when do you feel like it makes sense to invest in a tool like Hyros?

Hey I’m currently running into an issue with audience size in my Meta ads and wanted your guidance on the best way to approach this. Right now, I’ve uploaded a CSV file of around 11,000 leads — all homeowners with expired listings specifically in Houston, Texas. My goal is to target people who are already in pain (failed listing, still motivated to sell), so this dataset is extremely valuable to me. However, when I use this CSV as a Custom Audience and also set the ad location to Houston, Meta is showing that my audience size is too narrow (below 1,000), which is affecting delivery. Here’s what I’m trying to achieve: - Maintain high intent targeting (expired listings only) - Increase audience size so ads can actually deliver and optimize - Avoid diluting the quality of leads A few questions I’d really appreciate your input on: 1. Why is the audience shrinking so much, even though my CSV has ~11k contacts? 2. Is layering the Houston location on top of the CSV causing overlap and reducing size? 3. Would you recommend using this CSV differently (e.g., lookalike audiences, broader geo, etc.)? 4. What’s the best structure here if I want both precision AND scale? If you were in my position, how would you structure the campaign to keep targeting high-intent homeowners while ensuring the audience is large enough for consistent delivery and performance? Appreciate your help on this I want to make sure I’m setting this up properly before scaling