Your data is hiding insights you can’t afford to miss

Welcome to Prompt, Tinker, Innovate—my AI playground. Each edition explores a practical AI use case, why it matters, and a hands-on experiment to try.

Your mission? Test the prompt, tweak it, and uncover how AI can elevate your thinking. Before you know it, you’ll be innovating with AI in your daily life—one experiment at a time.

This week’s playground: Using AI to surface overlooked insights in large datasets

Why this matters

You're sitting on a goldmine of information: customer feedback, brand sentiment data, qualitative research, pipeline metrics, and digital journey insights. But buried in that volume of data is the why behind your numbers, the how behind customer behavior, and the what now you need to act on.

Traditional dashboards show you what’s happening. AI helps you understand why—by cutting through complexity to surface unexpected trends, emotional signals, and high-impact patterns. It’s like adding a strategist to your analytics team.

Use case spotlight: AI for comprehensive data analysis

Whether it’s a spreadsheet of survey responses, a CSV export from your CRM, or transcripts from customer interviews, AI can help you uncover patterns hiding in plain sight. Here’s what it can do once you upload your data:

• Reveal how customers really feel. Upload a file of reviews, support tickets, or survey comments—and AI can detect tone, emotions, and recurring sentiment. You'll see what customers love, what frustrates them, and how opinions vary across segments.

• Summarize themes in open-ended feedback. Got qualitative research, interview transcripts, or long-form comments? AI can instantly group responses by topic, surface what people are talking about most, and help you spot patterns you may have missed.

• Track how people talk about your brand. If you've exported social listening data, product feedback, or customer service logs, AI can show how brand sentiment is trending—and flag areas where perception may be shifting.

• Pinpoint friction in your sales or conversion funnel. Upload pipeline reports or sales stage data, and AI can highlight where deals slow down, where prospects drop off, and which stages are consistently underperforming.

• Understand user journeys. If you’ve got clickstream or behavioral data, AI can trace how people move through your site or product—revealing what paths lead to success and where users lose interest or stall out.

Your AI experiment: Try this prompt

👉 Time to tinker: Drop this prompt into ChatGPT, Claude, or Gemini—and upload your dataset. This could be customer feedback, product survey data, pipeline exports, NPS comments—anything rich in context and complexity.

📝 Prompt: “Act like a strategic partner with a sharp eye for insight. Analyze this dataset and identify key themes, sentiments, and recurring patterns. Go beyond surface-level observations—highlight anything surprising, counterintuitive, or that challenges common assumptions. Summarize the main takeaways in plain English, as if briefing a non-technical executive, strategist, or product lead. Be concise, insightful, and clear about what deserves a closer look.”

💡 Pro tip: Refine your output with targeted follow-ups:

• "What’s one unexpected insight that might challenge our assumptions?"

• "What might be misinterpreted if seen out of context?"

• "If this dataset drove one strategic decision, what should it be?"

What did you discover?

Did AI surface an insight that changed your perspective? Did it validate a hunch—or challenge it?

See you next week for another AI experiment.