how he made 83k in 30 days with AI dropshipping (product leaked)

Case Study: AI-Assisted Organic Dropshipping

Results and background

Matas, a 19-year-old from Lithuania, reports generating about $85,000 in revenue in his first month with a Halloween projector product. The video title says $83K, while the spoken interview says $85K.

His previous highest month was about $20,000 in revenue. Before this product, he says he had tested around 10 products while creating content for a brand, generating roughly $40,000 with a few of them. Later, he tested five products using AI and made about $10,000.

These figures are revenue, not profit. The interview provides no costs, margins, or net-income data.

Playbook and operating tactics

• Find a product with a creative edge: Matas noticed a few sellers promoting the projector but believed their content was weak. He started by adapting competitors’ concepts, then developed more original video concepts to stand out.
• Iterate content across platforms: Facebook videos took off first. Instagram initially performed poorly; after about 50 posts, a video featuring a U.S. flag helped the account reach a more relevant audience and gain traction. He also says changing concepts and using story-based videos helped sustain performance.
• Use AI with references and reusable workflows:
  • He used a reference video, selected several clips or images, and asked the AI tool to describe the movements. He also used its voice feature.
  • He saved successful concepts with names so he could reuse them and specify changes in later prompts. He says this reduced production of a repeatable concept to roughly five minutes.
  • For product-focused scenes, he emphasized supplying an accurate product reference image to avoid AI-generated substitutes.
  • He tested image-generation settings rather than assuming which would work best. He preferred a medium setting because the highest quality sometimes looked “too good to be real.”
• Treat creative production as a feedback loop: Early videos took three to four hours to make. Matas recommends learning from failed outputs and refining the process rather than quitting after initial mistakes.
• Keep the storefront simple but specific: The interviewer recommends clear product imagery, a strong offer, benefit-focused copy, and an FAQ tailored to the intended customer. The advice is to research the audience and define the ideal customer profile (ICP), rather than copying generic AI-written copy without reviewing it.
• Make creator onboarding hands-on: The operation expanded to three creators, including creators in the UK and Germany. The interviewer describes giving creators a complete strategy, Loom walkthroughs, and regular coaching rather than simply handing them a product. Matas says he held two one-hour calls each week with two creators.
• Scale, then transition products: The team planned to add creators and products as the projector began to fade, potentially testing another marketing angle for one to two weeks before moving to a stronger product.

Metrics and timelines mentioned

• Reported product-month revenue: About $85K; no profit or margin figures disclosed.
• Previous peak month: About $20K in revenue.
• Early performance: Matas says the first three videos went viral and that a run of roughly 40 videos performed well; the subtitles are unclear on the exact meaning of “40 videos in a row.”
• Instagram: Meaningful traction came after about 50 posts.
• Creator expansion: Two creators were brought on around the second week of the product run; the interview later refers to three creators total.
• Q4 opportunity: The speakers describe Q4 as a gift-buying period and claim conversion rates can double or triple. This is their general claim, not a measured result from the case study.
• Mentioned $12K day: The interviewer mentions a $12K day, but the context does not clearly establish whose store or which date it refers to.

Example and caveats

The seasonal product was a Halloween projector. The speakers note that it appeared to convert less effectively in Europe, where Halloween demand was lower than in the U.S.

The video is also a mentorship testimonial and includes promotion of the interviewer’s program. Its performance claims are self-reported and do not include fulfillment costs, advertising or creator expenses, refunds, or profit.

Presenters and sources: Matas (case-study guest) and Esteban Poudrier (interviewer).