ChatGPT Astra UGC Campaign Prompts

# How to use ChatGPT Astra for UGC so well it feels illegal 

openai shipped its most capable model on september 3. i wasn't going to write this.

we've generated 2.6 billion organic views across 62 campaigns, managed 590 creators, and produced 22,504 tracked videos for mobile apps. zero ad spend.

these 15 prompts are how i'm using ChatGPT Astra to run those campaigns at a level that was physically impossible 2 weeks ago. every single one is copy-paste ready. i'm giving them all away because by the time you read this i'll already be running them on the next campaign.

save this. you will need it.

## before you run a single prompt: load your campaign context

this is the step everyone skips and it's the step that makes everything else work. without it you're asking a stranger for advice about a business they've never seen.

paste this into ChatGPT Astra before anything else:

once this is loaded, every prompt that follows gets 10x sharper. Astra stops answering a generic marketing question and starts answering yours.

## PART 1: VIDEO ANALYSIS (prompts 1-3)

everyone thinks Astra can't watch videos. they're wrong. it just can't watch them the way you think.

Astra takes text and images as input. it does not accept raw .mp4 files. but here is the thing most people miss: you don't need it to. you need a pipeline that watches the video FOR it and hands it a structured breakdown.

this is the system we actually run, and it's the technique that changed everything for us.

the pipeline: how we make AI "watch" 200+ videos per week

we built an automated video intelligence pipeline. here is how it works end to end.

1. step 1: agent watches the video

we use an AI coding agent (openai codex, claude code, or any agent with tool access) connected to two command-line tools:

- yt-dlp: downloads any TikTok, Instagram Reel, or YouTube Short from a URL

- ffmpeg: extracts frames at adaptive intervals (more frames during the hook, fewer during the middle)

the agent runs this automatically. you give it a video URL. it downloads the video, extracts 8-12 key frames (weighted toward the first 3 seconds where hooks live), pulls the transcript from captions or runs whisper for speech-to-text, and reads any on-screen text from the frames.

the output is a structured report per video (btw this is a video from one of our campaigns):

2. step 2: batch process all campaign videos

the agent doesn't stop at one video. we point it at an entire campaign. it processes every video URL from our sideshift export and generates a structured report for each one. for a 50-video batch, this takes about 20 minutes running in the background. no human involvement.

the output is one file with every video described in the same structured format: frames, transcript, on-screen text, visual elements, pacing, scene changes.

3. step 3: feed everything into astra

now you take those structured descriptions (not the raw videos, the text descriptions of what's IN the videos) and paste them into astra's 1,050,000 token context window. this is where the magic happens.

astra can now "see" 50 videos at once through their descriptions. it knows what every first frame looks like, what every hook says, how many scene changes each video has, where the CTA appears, what the transcript says, everything. and it can compare all of them simultaneously.

A. the video autopsy

once your pipeline has processed a video, feed the structured report into astra with this prompt:

the key difference from doing this manually: the agent watches the video, not you. the structured report captures details a human reviewer misses because it reads every frame and transcribes every word. and the feedback output is specific enough to send directly to the creator.

why this matters: we review hundreds of videos per week across 62 campaigns. the bottleneck was never finding bad videos. it was articulating WHY a video underperformed in a way a creator can act on. "make it more engaging" is useless feedback. "your hook creates a knowledge gap but the payoff comes at second 8 instead of second 2, which is why your 3-second retention drops to 22%" is feedback a creator can fix in their next draft.

this prompt gives you that level of specificity for every single video. we used to spend 15-20 minutes writing feedback per video. now we spend 2 minutes confirming what the model found.

B. side-by-side video comparison

take your best performing video and your worst from the same campaign. extract frames from both.

why this matters: the comparison is where the real learning happens. when you look at one video in isolation, everything feels subjective. when you put the winner and loser next to each other with the same brief, the structural difference becomes obvious. the 3-sentence feedback output is deliberate. creators don't read long emails. they need one specific thing to fix.

C. batch format analysis across competitors

this one requires more setup but it's the most valuable research prompt in this entire article.

go to 3 competitor apps' TikTok or IG accounts. screenshot the first frame of their 10 most recent videos (30 screenshots total). note the view count for each.

why this matters: this is competitive intelligence that used to require hiring an analyst for a week. you're getting a structural breakdown of your entire competitive landscape from the visual layer. the key insight for us was discovering that 3 of our competitor apps were using the exact same first-frame template (text in top-left, face in bottom-right, colored background) and we weren't. we tested it the next week and our hook rate jumped 18%.

## PART 2: CAMPAIGN INTELLIGENCE (prompts 4-8)

this is where Astra's 1,050,000 token context window stops being a spec sheet and starts being a weapon.

for context: our entire database of 22,504 video captions with metrics fits in that window with room to spare. for the first time ever, the whole book fits on the desk instead of one page at a time.

D. caption clustering

this is prompt #1 in order of impact. if you only run one prompt from this entire article, run this one.

why this matters: this is the prompt that found our 4.2x problem. we had two campaigns for the same app. identical briefs. campaign A did 12,333 views per post. campaign B did 2,921. campaign B had more posts and more creators.

the caption clustering showed that campaign A had converged on one hook structure and repeated it across all creators. campaign B had 41 creators each running their own interpretation. the brief was the same. the execution drifted. nothing in our process caught it because no human reads 3,109 captions side by side.

a 1,050,000 token window does. and now we run this every monday.

E. brief drift detection

your brief has 5 components. your creators execute maybe 3 of them. the other 2 disappear silently and you don't notice until the campaign wraps.

why this matters: the messaging block is the one that silently disappears. we proved it. across 41 creators on one campaign, only 7 consistently executed the key messaging. the other 34 were making content that looked right but said the wrong thing. the course-correction messages alone saved that campaign $40,000 in wasted creator fees the following month.

F. comment mining

this one is embarrassing. we had 131,182 comments across our campaigns and nobody was reading them systematically until 3 months ago.

why this matters: your next viral hook is already written. it's sitting in your comment section in the exact words your audience uses to describe your product. the phrase "wait this actually works?" appeared 847 times across our campaigns. that became a hook. it did 2.1M views because it was already validated language from the audience itself.

G. creator performance analysis

stop making creator decisions based on follower count. this prompt builds a scoring model from your own data.

why this matters: we had a creator with 4,400 followers who hit 28M views across a campaign. we had another with 85,000 followers who averaged 306 views per post. follower count told us the opposite of reality. this scoring model finds the creators who actually perform, and it updates every week as new data comes in. the efficiency metric alone saved us $12,000 last quarter by catching overpaid underperformers.

H. cross-platform format translation

what works on TikTok doesn't automatically work on Instagram Reels. the mechanics are different. this prompt adapts your winners.

why this matters: we tracked this across 122,504 posts. Instagram Reels delivered 3.2x more views per post than TikTok in our data. but the formats that won on each platform were structurally different. the same video cross-posted without adaptation performed 40-60% worse than a platform-native version. this prompt gives you the platform-native brief without having to figure out the differences yourself.

## PART 3: BRIEF GENERATION (prompts 9-12)

most people use AI to write briefs from scratch. that gives you generic output because the model is writing from what it learned on the internet, not from what works for your product.

these prompts write briefs from your own data.

I. hook generation from your own winners

this is the difference between "generate me 30 hooks" and "generate me 30 hooks in the exact structural pattern that already works for my app."

why this matters: when you prompt for hooks without feeding the model your own data, you get the same hooks every other brand is running. when you feed it your winners first, every output is calibrated to what already performs for YOUR audience. the difference is the gap between a creator script that sounds like ChatGPT and one that sounds like it was written by someone who watches your content daily.

J. personalized brief per creator

this is the one that blew our operations team's mind. instead of one brief for all creators, you generate a brief adapted to each creator's style.

why this matters: we tested this across one campaign. 20 creators got the standard brief. 20 got the personalized version. the personalized-brief group produced videos with 31% higher brief compliance and 22% higher average views. same app, same campaign, same month. the only difference was that each creator received instructions translated into their own creative language instead of corporate marketing speak. at scale across 590 creators, this alone is worth more than any other prompt in this list.

K. campaign script writer

for creators who need more direction than a brief. some want the exact script. this writes it from your data, not from thin air.

why this matters: we use the "guide, don't script" approach as default. but some creators need more structure, especially newer ones. the difference between a script written from your campaign data vs a script written from nothing is the difference between a video that sounds native and one that sounds like an ad. this prompt produces scripts that creators actually want to film because they see their own voice in the words.

M. weekly research brief

replace your team's 2-3 hour research ritual with a 15-minute prompt session.

why this matters: the monday research ritual was 2-3 hours of manual spreadsheet analysis. this prompt does it in 15 minutes and catches patterns a human misses because it reads every single row instead of sampling. the "1 experiment to test" output is what keeps campaigns from going stale. we've been running this weekly for 8 campaigns and the experiment suggestions have a 40% hit rate. that's 40% of the time the model surfaces a test we wouldn't have thought of that actually works.

## PART 4: OPERATIONS (prompts 13-15)

L. creator feedback generator

the hardest operational task in UGC is writing feedback that is specific enough to change behavior without killing the creator's motivation.

why this matters: we review hundreds of drafts per week. consistency is the killer. one UGC manager writes a paragraph of feedback, another writes "looks good." this prompt standardizes the output without standardizing the voice. the ban on "engaging" and "compelling" forces specificity. "your hook creates curiosity but the payoff comes at second 8 instead of second 3" is 100x more useful than "make the hook more engaging."

N. campaign post-mortem

run this when a campaign ends. it catches the patterns that the wrap report misses.

why this matters: post-mortems are the most important document in a campaign and the one most people skip. this prompt means there's no excuse. the "missed opportunity" section is worth the entire exercise. it consistently surfaces the obvious-in-hindsight test that nobody thought to run.

O. the full campaign audit

this is the nuclear option. dump everything into the context window and ask the question nobody asks.

why this matters: i'll tell you a number that should terrify anyone running UGC at scale. in our data, 3 creators out of 590 account for 38% of all views. that's not a program. that's three people. this prompt catches that reality and forces you to build around it instead of pretending your averages represent your actual performance.

## how to use these prompts

do not run all 15 at once. here's the order.

day 1: load your campaign context. then run prompt 4 (caption clustering). this is the single fastest insight you will get. 30 minutes of work. do it today.

day 2-3: run prompt 1 (video autopsy) on your best and worst video. then run prompt 2 (side-by-side comparison). you now understand WHY your content performs the way it does.

week 1: run prompts 5 (brief drift) and 6 (comment mining). you now know what your brief is actually producing vs what you intended, and what your audience is actually saying.

week 2: run prompts 7 (creator scoring) and 9 (hook generation). you now know which creators to scale and have 30 new hooks calibrated to your data.

week 3: run prompt 10 (personalized briefs) for your top 10 creators. run prompt 12 (weekly research) every monday from this point forward.

ongoing: prompt 13 (creator feedback) on every draft. prompt 14 (post-mortem) at every campaign end. prompt 15 (full audit) once per quarter.

90 days of running this system and you will have better campaign intelligence than agencies that have been operating for years. i know because we built these prompts from managing 2.6 billion views worth of campaigns. the prompts are the system. the system is what scales.

## the real talk

95% of people reading this will save it and never paste a single prompt. that's fine.

if you want my team to run this entire system for your app (every campaign, every creator, every brief, every week of execution) that's what we do at The Viral App.

2.6 billion organic views. 590 creators. 62 campaigns. zero ad spend.