VP of Product
Customer & Market Research
What You Do Today
Stay connected to customers and the market — reviewing research, attending customer calls, analyzing usage data, and ensuring your team's decisions are grounded in actual customer needs, not assumptions.
AI That Applies
AI-powered customer insight aggregation that synthesizes feedback from support tickets, sales calls, user research, NPS surveys, and product analytics into actionable themes.
Technologies
How It Works
The system ingests support tickets as its primary data source. NLP models process the text input by identifying entities, classifying intent, and extracting the structured information needed for downstream decisions. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The customer empathy.
What Changes
Customer insights aggregate automatically. The AI identifies that the #1 pain point across all feedback channels is onboarding complexity, not the feature request that's loudest on the forum.
What Stays
The customer empathy. Reading between the lines of what customers say they want to understand what they actually need requires spending time with customers and developing product intuition.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for customer & market research, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long customer & market research takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your board chair or lead independent director
“What are the top 5 reasons customers contact us, and which of those could be resolved without a human?”
They shape expectations for how AI appears in governance
your CTO or CIO
“How do we currently measure service quality, and would AI-assisted responses change that measurement?”
They own the technology infrastructure that enables AI adoption
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.