Concert Market Intelligence
SeatNav analyzes the live ticket market daily across major cities. Each concert is scored using a deterministic model that measures pricing efficiency, inventory scarcity, and time pressure. We compute from real inventory snapshots — not guesses, not estimates, not AI-generated opinions.
The Model
Every event receives a SeatNav Market Score from 0 to 100, computed from up to four engines that each measure a different dimension of market dynamics. The composite score uses fixed weights — the same formula for every event, every city, every day.
Pricing Engine
40% (V1) / 25% (V2)Compares the event's mid-price against the city median. A concert priced well below the city baseline scores higher. Also measures price spread — tight spreads indicate efficient market pricing.
Scarcity Engine
35% (V1) / 25% (V2)Measures ticket availability relative to the city median inventory per event. Fewer tickets than typical means higher scarcity pressure. Sold-out events score 100.
Time Engine
25% (V1) / 15% (V2)Exponential time decay based on days until the event. Urgency increases sharply inside 7 days, with maximum pressure on event day. Events far out carry minimal time pressure.
Demand Velocity Engine
35% (V2 only)Measures the rate of inventory depletion and price movement over snapshot history. Activates after 3 days of tracked data. When active, all engine weights rebalance to V2: Demand 35%, Scarcity 25%, Pricing 25%, Time 15%.
Demand Velocity — Market Movement
Static pricing and scarcity tell you where the market is. Demand velocity tells you where it is going. By comparing daily snapshots, we detect acceleration in inventory depletion and price movement — turning data into actionable signals.
The demand score (0–100) combines inventory depletion (60% weight) and price movement (40% weight). This ensures that actual selling activity weighs more heavily than price speculation.
Market Signals
Each event receives a signal label derived from its composite score. These are not subjective ratings — they map directly to score ranges.
Data Confidence
We are transparent about what we know and what we don't. Every score includes a confidence level that reflects how much historical data supports it.
Early Signal
Day 1–2 — three engines active (pricing, scarcity, time). Demand velocity engine is off. Scores are directionally useful but based on limited snapshots.
Moderate
3–6 days of history. Demand velocity engine activates. Trend direction is emerging.
High
7+ days of daily snapshots. Full four-engine model with stable trend analysis.
City Baselines
Every city has a unique market profile. We compute median ticket price and median inventory per event for each city at every sync. This baseline anchors the scoring — a $50 ticket might be undervalued in New York but premium in Nashville.
Principles
Deterministic. Same input produces the same score. No randomness, no AI generation, no subjective weighting adjustments.
Reproducible. Every score can be broken down into its engine components. We show you the math, not a black box.
Explainable. Each score includes “why” bullets that trace directly to data comparisons — pricing vs median, inventory vs median, days until event.
Honest. We tell you when we don't have enough data. Early-signal means early-signal. We don't inflate confidence for marketing purposes.
Explore by City
SeatNav Market Intelligence. Daily snapshots from live ticket inventory. Powered by EVE.