💡 Live Market Buzz Score for Real-Time Discovery Social Proof

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Summary

Add a dynamic "buzz" indicator to the customer discovery screen showing real-time market activity: checked-in vendor count, trending products, and how the market compares to its historical average. Think Google Maps "Popular Times" but vendor-specific — not just foot traffic, but what's actually available right now. This transforms discovery from static listing to live intelligence.

Market Signal

Farmish (40K+ farms) and LocalHarvest own static discovery listings. Google Maps shows generic foot traffic via "Popular Times" but charges for API access (BestTime.app is a $99/mo alternative). No competitor provides real-time VENDOR-LEVEL market intelligence. This is the competitive moat that a coordination platform can build that a static directory cannot — live operational data repackaged as customer-facing social proof.

User Signal

Customer persona Rachel needs to make confident go/no-go decisions before traveling. The PRD's north-star metric is failed-trip reduction. Existing ideas #371 (Pre-Trip Confidence Dashboard) and #395 (Vendor Attendance Track Record) address parts of this, but neither provides the real-time social proof signal that converts a browsing customer into a market visitor. The buzz score is the "Popular Times" equivalent that makes discovery screens feel alive and trustworthy.

Technical Opportunity

Markets already has vendor check-in data flowing through Firebase Realtime Database at /markets/{marketId}/vendors/{vendorId}/status. The buzz score is a read-only aggregation of existing data — no new write paths needed. The Go backend can compute historical averages from the audit log (which already records all check-in/checkout events with timestamps). Apollo Client cache means the score updates in real-time on the customer's discovery screen without polling.

Assessment

Dimension	Score	Rationale
Feasibility	high	Pure read-only aggregation of existing Firebase Realtime data. No new backend write paths. Historical baseline from audit log.
Impact	high	Core differentiator against static listing competitors. Directly serves the failed-trip reduction north-star metric.
Urgency	high	Should launch alongside or shortly after customer discovery (Epic 6) to make the discovery experience feel differentiated from day one.

Adversarial Review

Strongest objection: With low vendor adoption, a buzz score showing "1 of 20 vendors checked in" actively DISCOURAGES visits and makes the market look dead.

Rebuttal: The display adapts to adoption level. At low adoption, show absolute counts ("3 vendors confirmed") without the ratio. Only show comparative data ("busier than usual") when adoption exceeds 60% of the roster. The feature degrades gracefully — even "3 vendors confirmed for Saturday" is more information than customers currently have, which is zero. The algorithm can also suppress the score entirely below a minimum threshold.

Suggested Next Step

Define the buzz score algorithm (inputs: check-in count, product availability updates, time-of-day normalization, adoption-level display thresholds). Design the discovery card UI showing the score with adaptive display modes. Implement as a Firebase Realtime listener on the existing /markets/{marketId}/vendors path.