Introduction
The trade-off we're considering for Messenger Business is whether to add more customer tagging options or improve existing classification. This decision impacts how businesses categorize and interact with their customers on the platform. I'll analyze this trade-off by examining the current product state, potential impacts, and experimental approaches to guide our decision-making process.
I'd like to start by asking a few clarifying questions to ensure we're aligned on the context and objectives of this decision. Then, I'll walk through my analysis framework, covering product understanding, hypothesis formation, metrics identification, experiment design, and ultimately, a recommendation with next steps.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Helps understand the baseline and potential for improvement Expected answer: We have 10-15 tags with varying adoption rates Impact on approach: Low adoption might suggest focusing on improving existing tags
Why it matters: Aligns solution with business priorities Expected answer: It's a significant factor in ad targeting and customer segmentation Impact on approach: High importance would justify more resources for improvement
Why it matters: Identifies key areas for improvement Expected answer: Businesses want more granular classification options Impact on approach: Could lean towards adding more tagging options
Why it matters: Assesses technical constraints and effort required Expected answer: Adding tags is simpler, improving algorithms is more complex but scalable Impact on approach: Might favor improving existing classification if technically feasible
Why it matters: Helps prioritize and scope the solution Expected answer: 3-month timeline with a dedicated team of 5 Impact on approach: Short timeline might favor incremental improvements over major overhauls
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