Creating UGC Videos with AI: ChatGPT and Sora 2 Tutorial

Creating UGC Videos with AI: No Actors Required

TLDR: This tutorial shows you how to create user-generated content (UGC) style video ads using ChatGPT for detailed product analysis and scripting, combined with Sora 2 for video generation. The entire workflow takes under 10 minutes and eliminates the need for hiring creators or filming.

User-generated content ads have become the gold standard for social media marketing because they convert exceptionally well. The authentic, casual feel of someone genuinely talking about a product resonates with audiences in ways that polished corporate content simply cannot match. However, the traditional UGC production model comes with significant pain points: finding the right creators is time-consuming, hiring them is expensive, and waiting for deliverables can stretch timelines far beyond what marketing teams need.

The approach outlined here flips this model on its head by leveraging AI to generate the entire creative pipeline. The workflow starts with something simple - a clean product image. The authors emphasize that quality matters here: products should be photographed against plain backgrounds with good lighting, and having multiple angles helps the AI better understand the product's three-dimensional nature.

What's particularly clever about this methodology is the systematic prompt engineering approach. Rather than jumping straight to video generation, the process uses ChatGPT as an analytical layer first. The initial prompt extracts detailed visual descriptions, identifies the main benefit, uncovers the emotional appeal, generates usage scenarios, and crafts authentic-sounding customer phrases. This intermediate step creates a rich context that dramatically improves the final video output.

The second stage generates five distinct UGC video concepts, each with different angles - testimonials, unboxing experiences, day-in-the-life scenarios, problem/solution narratives, and tutorials. Each concept includes the critical "hook" moment (those first two seconds that stop the scroll), the product reveal, suggested duration, and natural-sounding dialogue. The emphasis on authenticity is notable - the prompts specifically request filler words like "honestly," "literally," and "okay so" to avoid the stilted feel of traditional advertising copy.

For architects and teams considering this approach, there's an interesting workflow pattern here worth noting. The methodology keeps all prompts in the same ChatGPT conversation, allowing the context to accumulate and inform subsequent generations. This is a practical application of context window management that produces more coherent outputs than isolated prompts would.

Key takeaways:

• UGC-style content can be generated entirely with AI using a structured prompt engineering workflow
• The process requires minimal input: just clean product images and basic product information
• Using ChatGPT as an analytical layer before video generation produces significantly better results
• Authentic dialogue patterns (including filler words and casual phrasing) are essential for believable UGC content
• Multiple concept variations allow for A/B testing different creative angles

Tradeoffs:

• Gain production speed and cost reduction but sacrifice the genuine human element that made original UGC compelling
• Eliminate creator coordination overhead but lose access to organic creative ideas that real users might contribute
• Achieve consistency and scalability but risk content feeling formulaic if the same prompts are reused excessively

Link: Tutorial: How To Create UGC Videos With ChatGPT + Sora 2

The summaries provided are based on my analysis and may not fully represent the original authors' perspectives. I recommend reading the original articles for complete context.