The Challenge
A retail payments company was preparing to launch a new product into an increasingly crowded market. Early test results had not trended positively, and the team lacked alignment across the C-suite on how to reposition the offering. Their marketing and data teams were operating inefficiently, their customer outreach was imprecise, and leadership had not yet established a clear AI strategy or communicated a coherent vision to employees and customers.
What They Built
Sean Wood and Human Pilots AI ran an executive alignment workshop, AI readiness assessment, and structured two-week sprint cycles with cross-functional AI pods — using Claude, ChatGPT, and Gemini to sharpen customer positioning and personalize outreach without changing the product itself.
Sean Wood and Human Pilots AI began with an executive workshop designed to surface and resolve misalignment in how the C-suite understood the product's positioning problem. Only after that alignment was reached did the team proceed to an AI readiness assessment covering data quality and human capital. High-impact, low-risk use cases in marketing and customer communications were identified as the entry points. The delivery structure was two-week sprint cycles with cross-functional AI pods — small, focused teams experimenting with how AI tools could sharpen the specificity and personalization of customer outreach. Claude, ChatGPT, and Gemini were used to analyze available customer data, refine messaging, and retrain how the team communicated the product's value proposition. The product itself did not change. What changed was the precision and relevance of how it reached customers. During the pilot period, lead response rates increased 200%. Over the full engagement, the company also recorded a 12% sales lift and a 40% productivity gain across the marketing and data teams.
AI Role
12% lift in sales during the pilot period as repositioned product messaging resonated with target customers — achieved without changing the underlying product.
Infrastructure
• Claude (customer data analysis and messaging refinement) • ChatGPT (content generation and outreach drafting) • Gemini (data synthesis and positioning analysis) • Microsoft Copilot 365 (productivity and document workflows)
Integration Points
• AI tools connected to available customer data for personalization analysis • Outreach drafts generated by AI pods and reviewed before distribution • Sprint retrospectives used to identify highest-performing messaging approaches for iteration
Mid-market retail and financial services companies with C-suite sponsorship that need help identifying where to start with AI, how to measure ROI, and how to scale transformation across complex organizations.
