This episode reveals how Cuddle Clones leveraged AppLovin to achieve an unprecedented $80K/day in sales during Q4, after experiencing diminishing returns on Meta. It highlights the critical importance of channel diversification and quickly testing new platforms, especially during peak seasons, to unlock profitable growth when traditional channels falter.
Key takeaways
Diversify ad channels beyond Meta, especially in Q4 when CPMs rise and competition intensifies. AppLovin can scale rapidly, even from zero, if your product resonates.
For custom or seasonal products, explore ad platforms that can deliver rapid, high-volume sales within a short window. Cuddle Clones achieved $80K/day on AppLovin in one week.
Leverage "managed service" ad platforms or onboarding credits to quickly test new channels without initial cash outlay or extensive platform expertise. This mitigates risk and speeds up execution.
Prioritize channel diversification for long-term stability and to mitigate the impact of a single platform's underperformance.
Utilize third-party attribution tools like Triple Whale for accurate performance validation across new ad platforms, rather than solely relying on platform-reported metrics.
Think you've maxed out your paid advertising? Think again.In this episode, Miranda Pettinger (365 Holdings/Cuddle Clones) shares how she scaled AppLovin from zero to $80,000/day in just 7 days during Black Friday—and why it's now their highest-spending channel, even surpassing Meta.Miranda doesn't just share success metrics—she breaks down the exact strategy, creative approach, and measurement framework that made it possible. This is the blueprint for brands ready to diversify beyond Meta and Google.If you're spending serious money on Meta and hitting scale ceilings, AppLovin might be your most underrated growth opportunity. Miranda proved it's possible to find incremental customers, better ROAS, and massive scale—all while simplifying your account structure.—Sponsored by OMG Commerce - go to (https://www.omgcommerce.com/contact) and request your FREE strategy session today!—Chapters: (00:00) Introducing Miranda and Cuddle Clones(07:54) The Journey from Zero to $80,000 a day.(13:27) Targeting, Media Buying and Creative on AppLovin(17:03) Understanding AppLovin(19:38) Analyzing Customer Behavior and Incrementality(22:59) Fermat: Optimize Shopper Experience with AI(23:53) Limitations on AppLovin and Final Thoughts(31:15) Crafting Compelling Ads(37:24) Analyzing Successful Ad Elements(42:17) Targeting and Audience Engagement(46:27) Brand Recall and Interactions(50:25) Utilizing AI for Ad Optimization(53:35) Creative Diversity and Longevity(58:41) Final Thoughts(01:03:08) Save Money and Connect Your Marketing Channels with Channable—Connect With Brett: LinkedIn: https://www.linkedin.com/in/thebrettcurry/ YouTube: https://www.youtube.com/@omgcommerce Website: https://www.omgcommerce.com/ Request a Free Strategy Session: https://www
Frequently asked about this episode
What does this episode say about channel diversification?
Diversify ad channels beyond Meta, especially in Q4 when CPMs rise and competition intensifies. AppLovin can scale rapidly, even from zero, if your product resonates.
What does this episode say about e-commerce growth strategies?
For custom or seasonal products, explore ad platforms that can deliver rapid, high-volume sales within a short window. Cuddle Clones achieved $80K/day on AppLovin in one week.
What does this episode say about paid acquisition?
Leverage "managed service" ad platforms or onboarding credits to quickly test new channels without initial cash outlay or extensive platform expertise. This mitigates risk and speeds up execution.
What does this episode say about q4 holiday planning?
Prioritize channel diversification for long-term stability and to mitigate the impact of a single platform's underperformance.
What does this episode say about channel diversification?
Utilize third-party attribution tools like Triple Whale for accurate performance validation across new ad platforms, rather than solely relying on platform-reported metrics.
