The last flat price in your park is the one under the windshield.
Every ticket, every season pass, every funnel-cake dollar is already yield-managed. Parking still runs a fixed daily rate all season — on demand that is anything but flat. PVS Parks prices the lot the way you price the gate: forecast-and-mix on the ~250 ordinary days, scarcity yield on the handful of peak days the lot actually fills.
You yield-manage everything but the parking lot.
Regional operators have gotten sharp on admission — advance-purchase, day-type pricing, pass tiers, dynamic upsells. Parking got left behind: for most operators, still one flat daily rate set at the start of the season, on near-inelastic captive demand. Advance online sales are spreading — but that pre-sells the same flat rate, it doesn't price to the day.
That's fine for ~250 days. But on the ~10 peak days a year when even the general lot fills, flat pricing quietly turns cars away from revenue — and the rest of the season, the product ladder (Preferred, Front-Gate, Valet) sits under-optimized. PVS Parks is built for exactly that split.
A park year is two problems, not one.
Stadiums are pure scarcity — every event sells out, so you yield-price the sellout. Parks are the opposite most of the year, then flip. PVS Parks models both regimes off one demand forecast.
Forecast & mix · the ordinary day
Capacity doesn't bind. Pricing is about a demand-indexed base and moving cars up the ladder — Preferred, Front-Gate, Valet — against pass-entitlement that eats into paid inventory. Small gains, 250 times.
Capacity-binding · the peak day
Attendance is high enough that the general lot actually caps out and overflow opens. Now it's a stadium: supply is the constraint, every space is spoken for, and scarcity pricing switches on. This is where flat pricing costs the most.
What the lot is worth when you price it like an asset.
One representative regional park, modeled across a full May–October season — a 32,000-guest-capacity park with 9,370 priced spaces and a season-pass program. Price points grounded in public Six Flags, Cedar Point and SeaWorld rates.
$7.35 per-cap
captured on 9 peak days
now visible & planned for
the lot binds
Read it straight: the uplift is the money flat pricing leaves on the table on the ~9 days the lot binds — before touching the mix optimization that runs the other ~250. It's a model on fictional-but-grounded data, not a client result. The point isn't the exact figure; it's that the figure is knowable, sizable, and recurring — and today it's invisible.
Forecast the day. Price the lot. Push the rate.
A closed loop on your own data — the same substrate that already powers Peregrine's stadium pricing, retuned for the park calendar.
Forecast
Day-type, day-of-week, school calendar, weather and event overlays roll into a per-day attendance and cars-on-lot forecast — the demand index every price reads from.
Price
One engine sets the per-tier ladder: demand-indexed base, pass-entitlement drag, spread and advance levers, and graduated scarcity yield the moment the general lot binds.
Push
Recommended rates flow to the gate and storefront through the existing price-push path — JustPark (formerly ParkHub) and direct sales — with floors, ceilings and a full activity log.
The whole operating calendar at a glance — every day color-graded by demand, peak days flagged, weather baked in.
Forecast-and-mix on the calm days, graduated scarcity yield on the binding days. One model, priced to the cent.
Day-of arrivals, projected scan pacing by channel, overflow triggers, bus / RV coordination.
What each parking space is worth — cost basis to recommended optimal, per space, rolled up to the venue.
Season revenue under every sky, and the dollars at risk on each peak day if it rains out.
Dynamic-pricing uplift, tier utilization, master finance — one click to CSV or PDF for the revenue meeting.
Bring your season. We'll show you the money on the lot.
Request a demo and we'll walk you through the live model on numbers that look like yours — a full operating season, every tier, tuned to your park.