Pricing-intelligence dashboard for a MATT moving tenant: KPIs, price-competitiveness and expected-revenue curves, conversion funnel, agent and lane performance, and optional comfort-call and DSP panels.

As of Jun 2026
Currency

Price competitiveness (elasticity) modeled

Win rate by price position — how a quote's rate compares to the median for that kind of move. The line falling as price rises is your elasticity.

Expected revenue per quote modeled

Avg rate × win probability, by price position. The peak is the revenue-maximizing price band — where to aim.

Quote volume vs won inbound jobs real

Real quote opportunities per month (green) vs real won inbound jobs (blue). Note the 2025 quoting ramp — it distorts year-over-year. Quotes are destination-service quotes; won-jobs count all inbound won moves, so the two are not yet joined per quote.

Conversion funnel modeled

Where deals leak, from opportunity to booking.

Win rate by shipment mode win % modeled

Mode volumes are real (66/18/16 FCL/LCL/Air); win % is modeled.

Comfort-call lift optional module modeled

Win rate with vs without the comfort call — a non-price lever. Proof you can hold price instead of discounting.

Destination services (DSP) optional module modeled

Leads shared → RMC-excluded → eligible → converted.

Lane performance real

Top origin markets by real quote volume (origin inferred from email domain + agent name; global RMCs shown as International; win % modeled).

LaneOppsWin %Avg rate

Agent leaderboard real

Real quote volume and average rate by agent; win % and price position modeled.

AgentOppsWin %Avg ratePrice pos

Salesperson performance real

By the quote's "Prepared by" field — real quotes, average rate, and total quoted value.

SalespersonQuotesAvg rateValue

Monthly performance analysis auto-generated

Written each cycle by an LLM from the data above: most recent month vs same month last year, and current quarter vs same quarter last year.