CMA 2025 Conference
Getting Better Answers from AI: A Smarter Approach for CatMan Teams
One of the most practical takeaways from the CMA 2025 Conference came from Colin Ching and Liliya Babraunichaya at Microsoft (big thanks to them!). They shared a simple yet powerful way to get better results from AI—one that I immediately started using.
It’s called the GCSE Framework, a structured approach that turns vague AI prompts into clear, actionable insights. Instead of asking broad questions and hoping for the best, this method helps you steer AI in the right direction by including these key elements:
The Four Elements of the GCSE Framework
1. Goal – What are you trying to achieve?
2. Context – What background info helps?
3. Source – Where is this coming from?
4. Expectation – What does success look like?
When prompting an LLM like ChatGPT, structuring your ask using these four elements can significantly improve the quality of responses. Here’s the GCSE Framework in action:
“Help me assess how inflation is doing as part of my macroeconomic assessment in a deck (Goal). I need this to inform our promotional pricing strategy (Context). Share the data source, as I’ll need to cite it in my slide (Source). Show quarterly inflation changes over the last five years (Expectation).”
See the difference? Instead of a generic response, you get something structured, sourced, and relevant—exactly what’s needed in category management.
Most people treat AI like a vending machine—drop in a question, get an answer. But it works better as a sous-chef: prepping, refining, and organizing the information so you can put the final touches on it.
If AI is part of your workflow, give the GCSE Framework a shot. A little structure goes a long way.
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