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Market Requirements Gathering AI for B2B SaaS | Clozure

Most product orgs ship the wrong things 40% of the time. Edison reads every support ticket, NPS comment, and sales-call transcript — then prioritizes the 3 features that will move retention the most. For Market Requirements Gathering, that means Edison doesn't just collect data; he synthesizes it into a ranked, defensible list of what to build next — so you never waste a sprint on guesswork again.

The Market Requirements Gathering problem most teams have

Manual market requirements gathering is bleeding your roadmap dry. Here are the numbers:

The core pain: your requirements document is a graveyard of conflicting opinions, buried under Slack threads and spreadsheets. By the time you ship, the market has moved.

How Edison owns Market Requirements Gathering end-to-end

Edison is an autonomous AI VP Product purpose-built for B2B SaaS. He doesn't just aggregate feedback — he owns the entire requirements lifecycle. Here's how he handles Market Requirements Gathering:

Edison works in the domain of product discovery and user research synthesis. He doesn't replace your PMs; he gives them a complete, data-backed requirements set every Monday morning.

A concrete Edison workflow

BEFORE: Acme SaaS (a $20M ARR B2B platform for HR teams) had a manual market requirements process. The PM, Sarah, spent 35 hours per week reading 2,100 support tickets and 14 NPS reports. Her last release — a "premium analytics dashboard" — was built from a single enterprise customer's request. It took 3 months to build, and only 8% of users adopted it. Retention dropped 2%.

Edison's actions:

  1. Week 1: Edison ingested 12 months of support tickets (18,000 records), 4,200 NPS comments, and 340 sales-call transcripts. He synthesized them into 27 distinct requirements, each with a feature impact score.
  2. Week 2: Edison identified a cluster of 1,400 tickets about "onboarding time" — users were taking 14 days to get value. He scored this requirement as a +11% retention impact with 3 weeks of dev work.
  3. Week 3: Edison auto-generated a market requirements document with a ranked list. The #1 requirement: an automated onboarding checklist. #2: integration with Slack for daily HR alerts.

AFTER: Sarah's team built the onboarding checklist in 2 weeks. Adoption of the new flow hit 73%. Retention for new customers improved by 9% in 60 days. Sarah now spends 3 hours per week reviewing Edison's requirements doc instead of 35 hours reading raw feedback.

Why Edison wins vs. hiring

Hiring a human VP of Product for market requirements costs $220,000–$350,000 per year in salary, plus 6–12 months to ramp. Even then, they take vacations, have cognitive biases, and might leave after 18 months (average VP Product tenure: 19 months).

Edison costs a fraction of that. He works 24/7, never takes a vacation, and synthesizes feedback with zero bias. He augments your human team — Sarah still makes the final call, but she makes it 10x faster with data she can trust.

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