Ski pass price monitoring: dynamic lift-ticket pricing by resort and date

Resort and ski area coverage

Which lifts and linked areas the pass includes.

Ski date

Peak weeks, weekends and holidays price differently.

Purchase date and days ahead

The axis of the advance-purchase curve.

Pass length and age category

Each combination is its own price series.

Price and currency

CHF, EUR or other local currency, as displayed.

Pricing model

Dynamic, tiered by purchase time or fixed, per resort and season.

Channel

Online shop, ticket office or partner, where the shop states it.

Season pass price and deadline

Early-bird season passes have dated price steps.

1. 01

   List resorts, products and the season grid

   For each resort, record its shop, pricing model and the products you track. Choose ski dates across the season: opening, school holidays, regular weekdays and weekends, late season.

2. 02

   Query the selected-product price daily

   Ticket shops typically expose a price endpoint per date, product and age. Query it for every ski date on each collection day; the daily snapshots form the advance-purchase curve.

   Daily snapshot of a resort's price calendar19 linescopy

   from datetime import date, timedeltaimport httpxPROXY = "http://USERNAME_pool-arcfast_country-de:PASSWORD@proxy.arcproxies.io:8000"   # rotating pool, country of the resortPRODUCTS = [("adult", 1), ("adult", 6), ("child", 6)]def snapshot(shop, season_start: date, season_end: date) -> list[dict]:    today = date.today()    rows = []    with httpx.Client(proxy=PROXY, timeout=20) as client:        d = max(season_start, today)        while d <= season_end:            for age, days in PRODUCTS:                price = shop.price(client, ski_date=d, age=age, days=days)                rows.append({"ski_date": d, "bought_on": today,                             "days_ahead": (d - today).days,                             "age": age, "days": days, "price": price})            d += timedelta(days=1)    return rows

3. 03

   Add covariates

   Store snow and weather forecasts, school holidays in the main source markets, and the day of week. Resorts that price on forecasts move with them, and a curve without covariates is hard to read.

4. 04

   Build curves and indices

   Per resort and product, plot price against days ahead for each ski date, and summarise the gap between the earliest and the day-of price. Storing price time series covers the schema.

Prices are list prices in EUR, excl. VAT. Volume discounts apply automatically at checkout — full ladder on the pricing page.