When you run a live stunt show touring 26 cities in a six-month season, the last thing you need is a full day of fact-checking listings. But that was the reality for Larissa Guetter, co-founder of ATV Big Air Tour, until she started using ChatGPT Work to automate the busywork that was eating her week.
In a September 2026 OpenAI case study, Guetter describes how a two-person team now handles marketing, merchandising, and AI search optimization—tasks that used to take days—in a few hours. Here’s what she did and what other small businesses can learn from it.
From 8 Hours of Fact-Checking to 1 Hour
ATV Big Air Tour’s events are promoted by third parties—organizers, ticketing sites, local media—who don’t always get details right. Guetter was manually checking about 30 online publications daily, a task that consumed a full workday each week.
She set up a scheduled ChatGPT Work briefing that runs every morning. It scans her priority sources, flags inconsistencies across the web, and even surfaces listings she hadn’t found. The tool also suggests the right contacts at each publication and drafts correction emails. What used to take 8 hours now takes about 1 hour per week, according to the case study.
The key wasn’t just automation—it was the handoff. ChatGPT didn’t replace her judgment; it gave her a daily digest of problems and a draft response, so she could review and send in minutes.
Inventory Photos to Reorder Recommendations in 15 Minutes
Merchandise is a big revenue stream for the tour, but inventorying and reordering was a manual nightmare. Guetter uploaded photos of her stock to ChatGPT Work. The tool organized the inventory, built a spreadsheet and a visual inventory website, and generated reorder suggestions in under 15 minutes.
She reviewed the recommendations, adjusted quantities, and sent the final order to her supplier. The whole process—from photographing items to placing the order—dropped from two to three days down to two to three hours.
What’s notable here is the workflow design: ChatGPT handled the tedious parts (cataloging, spreadsheet creation, reorder logic) while Guetter kept the final decision. That split is a practical template for any small business owner drowning in repetitive tasks.
Becoming Her Own CMO with AEO
Guetter’s growth strategy hinges on being discoverable in AI search. She set up a daily ChatGPT Work automation focused on answer engine optimization (AEO). Each day, it audits her website to check whether event dates, locations, and ticket details are structured clearly enough for AI tools like ChatGPT to surface.
One audit found that ChatGPT couldn’t retrieve about 90% of the site’s FAQs. ChatGPT Work flagged the issue and recommended fixes. The result: website analytics showed OpenAI search and user-bot hits jumping from 183 to 2,421 across consecutive 30-day periods—a 1,223% month-over-month increase, after filtering out training bots.
For a two-person team, this is a way to act like a marketing department without hiring one. The takeaway: AEO isn’t just about keywords; it’s about structuring content so AI can parse it reliably.
The Practical Lesson for Small Teams
ATV Big Air Tour’s story isn’t about replacing workers—it’s about compressing time on tasks that don’t need human hours. Guetter’s approach shows three repeatable patterns:
- Automate monitoring: Use scheduled briefings to catch errors or changes across many sources.
- Turn physical inputs into structured data: Photos became a spreadsheet and reorder plan in minutes.
- Optimize for AI discovery: Regular audits ensure your site is readable by AI assistants, not just humans.
Guetter’s quote in the case study is telling: “If I didn’t have ChatGPT Work, I don’t know where our business would be right now, because I would still be doing all these tedious tasks.” That’s the real value—freeing up time to focus on the show itself.
One limitation: the case study is a single example, and results will vary by business. But the workflow patterns—scheduled checks, photo-to-data pipelines, and AEO audits—are transferable to any small operation looking to scale without adding headcount.
Sources
AI-assisted summary compiled from the sources above, reviewed by a human before publishing.