How I Made $30k in 30 Days With AI Avatars (Step By Step Guide)

Summary

The presenter outlines a workflow for creating AI-avatar videos, publishing them on Instagram and Facebook Reels, and monetizing them through Amazon attribution and higher-commission brand partnerships. He says the approach can be scaled by delegating video production—and eventually posting and scriptwriting—to virtual assistants (VAs).

Operating playbook

• Set up the account and avatar: Create an AI character using a reference image and an image-generation tool. The presenter recommends making the character distinct from real people, specifically avoiding celebrity look-alikes when selling products.
• Find and adapt content ideas: Browse Instagram for inspiration, transcribe a video, and use Claude to rewrite the transcript into a short script. The example is a video about cinnamon and pineapple.
• Generate clips: Use Google Flow/Veo to create short clips featuring the avatar. The presenter says Veo clips are limited to eight seconds and that scripts and generations need testing to avoid awkward expressions, eye movements, or other visual glitches.
• Edit and publish: Assemble clips in CapCut, isolate the voice, remove dead space and any watermark, add transitions and captions, then publish or schedule the Reel through Meta Business Suite. He cross-posts to Instagram and Facebook.
• Delegate and scale: Initially, the creator makes the scripts and videos himself. Once the workflow is established, VAs can produce videos from scripts. The presenter says he has five VAs and is working on hiring a manager and a poster. He also plans to train a VA to write scripts.

Cadence and scaling approach

• His preferred routine is three scripts/videos per day, or roughly three posts per day per account.
• He says he previously aimed for 20 videos a day across five avatars.
• He reports that his VAs have made videos for him for the past two to three weeks. He now mainly writes scripts and reviews or posts their work.
• His longer-term goal is to delegate scriptwriting as well, so he is less involved in daily production.

Monetization and reported metrics

• The presenter reports $67,000 in Amazon tracked revenue over the prior 30 days, beginning on April 17, and estimates a little over $20,000 in profit. He says his calculation is based on an estimated 30% profit of the reported ordered revenue. These are his claims, not independently verified results.
• He says Amazon’s displayed commission reflects its 1% commission, while most of his earnings come from brand partnerships. He cites:
  • 200% commission for sales attributed to an Instagram bio link—for example, $60 on a $30 product.
  • 50% commission for sales attributed to DMs—for example, $15 on a $30 product.
• He explains that Amazon’s attribution cookie lasts one week, and tracked revenue may include purchases of other products made after someone clicks a link. He recommends downloading Amazon reports to distinguish direct sales and calculate earnings more accurately.
• He also cites roughly $1,800 in tracked revenue for one day. The dashboard figures he mentions are not fully reconciled in the video.

Practical takeaways and risks

• Treat video generation as an iterative production process: test scripts, clip lengths, expressions, and edits, and discard weak generations.
• Standardize the workflow before delegating it. Give VAs scripts and a clear production process, then add management and posting roles as volume grows.
• Track profit and attributed sales, not just headline tracked revenue; commission rates and attribution rules materially affect actual earnings.
• The example script makes health-related claims. Businesses using this model should verify product and health claims and ensure content and advertising comply with applicable platform rules and regulations.

Presenter/source: Dizzsells, from the Dizzsells YouTube channel.