Ad creative tactics

Made in 30-60 minutes in his basement: a screenshot/screen-recording voiceover tutorial, with the QuickTime recording dot still visible, thumps and clicks audible and a misspoken number left in. Hook: 'most golfers could use a little help understanding strokes gained' (confusing to some, a chance for experts to feel knowledgeable). It then walks through a real 430-yard par 4 showing strokes gained for a drive down the middle, into the rough and into a bunker, and ends 'try out Shot Pattern so you can see strokes gained before you hit the shot'. It showed the core audience exactly what they already wanted to do.

Rank candidates by comment sentiment (e.g. 'what is that app?') first, then engagement rate, then average views. Spark when engagement is above ~7.5-10% or a video does 3-5x the account's average views. Let organic climb first: if still gaining (e.g. 100K/day) wait 1-2 days. Start with ~$20 (SideShift runs $50-100/day per video for a week); keep running while CPMs don't rise; CPMs usually rise when engagement falls from ~15% to ~5%, then kill it. Exclude sparked views from creator view bonuses. Can add an app-install anchor to track CPI. Spark can also be targeted by country/language/age.

Any creator video over 50,000 views becomes a Meta ad candidate. Run a test campaign at ~$50/day per creative; if ROAS > 1 or CTR is very high, scale stepwise (50 -> 100 -> 200 -> 300/day). Returns are not linear (diminishing returns as spend rises), so watch for creative fatigue and keep producing new creatives to get 'more tickets to the lottery'.

The top ad was an Arcads AI guy walking in a park with the hook 'If you love God but you're trying to work on your health, you need to see this', then explaining FaithFull. Hired a female UGC creator to copy it exactly: same park setting, same walk, same script and delivery. Generally makes multiple variations of any ad that scales.

Runs creative testing campaigns on Android, where events arrive immediately (cost per install, registration, checkout). Winners go into a single long-lived Android scaling campaign that builds purchase history; new winners are tested against the current champion and switched off if they lose. Only ads that hold up over time are moved into a single iOS SKAN campaign, because SKAN data arrives late and testing there would need ~$1,000/day. Started at $50-100/day, scaled to $150/day once purchases came.

Level 1: every video in its own ad set with $10-20; shut off after $5-10 if clearly off-target; after 1-2 days and $20-40 of promising spend it graduates. Level 2: ad sets (or a CBO campaign in parallel) with 4-5 videos and $100-500, tested against the same lower-funnel or download targets at bigger spend. Level 3: the 1-2 that rise to the top become evergreen campaigns taking ~90% of spend. Never turn off working level 1/2 ads, so one video may run at all three levels at different spend.

Aggregated data across thousands of videos to define what made winners. Briefs (slide decks) split concepts into lifestyle, trend, educational and testimonial; each specified the trending sound, hook type (curiosity, empathetic, reflective), captions, pace, length 10-15s with 25-27 cuts, the number of app shots, and that phone clips are POV looking down at the screen. Angles included morning routine, evening routine, wellness, mindset and vlogs (hook -> habits -> app crossing off habits). Paid someone to scroll TikTok and send a list of trending songs at the start of every week, and updated briefs regularly.

Same video concept, different platform name in the hook. 'Stop using LinkedIn to apply to jobs' reaches white-collar workers who apply to hundreds of jobs and will pay to automate it. 'Stop using Indeed' / 'Who's still using Indeed?' reaches blue-collar workers who get interviews easily and flood the comments with hate about paying to apply. Read the comments to tell whether you hit the right audience.

Make many organic creator videos (multiple creators, multiple hook styles), then put the platform minimum behind each one rather than judging by organic views, since good videos sometimes flop on timing or the algorithm. TikTok: ~20 creatives at the $20 minimum each, can switch off after ~$5; Meta: 30-40 creatives at ~$1 each since it is easier to duplicate. Judge within hours on top-of-funnel clicks only: most get 0-2 clicks, one gets 5-20. Keep spending on that one to see whether it was a fluke, then track it down to purchases and make variations (change the first or last second). Mid-virality videos (top 25%) often convert better than the most viral, clickbaity ones. For a $5K starting budget he'd spread it over as many hypotheses as possible, aiming for 100 variations, and compress '500 videos' of learning into a week. Test the same creative across Google, YouTube, Meta and TikTok; one platform can give 2x results.

Searched TikTok for 'vaping', saved the most viral videos into a spreadsheet and broke down each one's hook, value and how it was shot. Found a 20M+ view video of a guy taking apart a vape and reused the concept: showing what is inside a vape, with a quick two-second call to action for Puff Count at the end. Videos are entertainment first, never sales videos about features.

Never upload untested creatives into the scaled campaign: any change resets the learning phase and causes swings. Run a separate testing campaign that mirrors the scale setup: same optimization event (trial, not install) and one of your live core markets (the cheapest of them), not cheap unrelated markets like Thailand or Mexico where nobody knows the brand. Move only proven winners into the scale campaign. Fewer, more deliberate creative bets than pre-ATT.

Short AI-generated UGC ads built in MaxFusion with three parts: a hook that stops the scroll (take ideas from current TikTok trends), a plain explanation of the use case, and a call to action to download. Example 1: an AI creator says 'Everyone keeps asking how people make those viral AI character videos. You don't need editing skills... open it, pick a character, type what you want them to say, hit generate... Download Cantina.' Example 2 (more obviously AI): an 'emotional support brick' that got a product launch video made in Cantina, ending 'Try it. Download Cantina.' The point is installs, so no cinematic production; cheap to make, so many angles can be tested on Meta.