Trade fair hotel prices: measure the Messe surcharge city by city

Event and venue

Fair name, edition, opening and closing dates, venue. The anchor every other row hangs from.

Hotel and distance ring

Your own hotel ID plus travel time to the fairground, so overflow towns sit in the right ring.

Stay pattern

Single night, full fair period, or arrival the day before. Restrictions only show up when you shop the pattern guests actually book.

Point of sale

The exhibitor market the request came from. A German and an Italian visitor may see different rates and different tax display.

Rate and conditions

Total stay price, nightly average, refundable or prepaid, deposit, minimum stay. The fair premium is often in the conditions, not only the number.

Local levy

City tax or tourism contribution as shown, kept apart from the room rate.

Baseline reference

The matching observation from the reference weeks: same hotel, weekday, length of stay and market.

Observation date

Days before the fair opens. Plotting price against lead time is the chart every organiser asks for.

1. 01

   Build the fair calendar

   List the fairs and congresses you care about with their dates and venues. Add every other large event in the same city, so you can exclude contaminated weeks from the baseline.

2. 02

   Fix the hotel panel per city

   Pick the hotels within your travel-time rings and keep the panel stable across the season. Adding hotels halfway through changes the average for reasons that have nothing to do with the fair.

3. 03

   Shop fair and reference dates from exhibitor markets

   For each fair, shop the fair dates and the reference weeks with the same pattern, from the countries your exhibitors come from. Hold one session per hotel and date so search and room list come from one exit.

   Fair dates and reference dates, same hotel, same market21 linescopy

   import secrets, datetime as dt, requestsBASE = "USERNAME_pool-arcfast_country-de".split("_country-")[0]   # USERNAME_pool-arcfastdef proxy(country: str) -> dict:    user = f"{BASE}_country-{country}_session-{secrets.token_hex(4)}_sesstime-10"    url = f"http://{user}:PASSWORD@proxy.arcproxies.io:8000"    return {"http": url, "https": url}def stay_dates(fair_open: dt.date, nights: int, offsets=(-42, -35, 0, 35, 42)):    """Arrive the day before the fair; same weekday in the reference weeks."""    arrive = fair_open - dt.timedelta(days=1)    for off in offsets:        yield off, arrive + dt.timedelta(days=off), nightsdef shop(hotel_url: str, country: str, fair_open: dt.date, nights: int = 3):    for offset, checkin, n in stay_dates(fair_open, nights):        with requests.Session() as s:            s.proxies = proxy(country)          # e.g. "it", "fr", "us"            r = s.get(hotel_url, params={"checkin": checkin.isoformat(), "nights": n, "adults": 1}, timeout=30)            yield {"offset_days": offset, "checkin": checkin, "status": r.status_code, "html": r.text}

4. 04

   Classify, then normalise

   Every observation ends as available with a price, closed by restriction, sold out, or not retrieved. Normalise available rates to a total per stay in one currency, with the local levy and tax as separate columns.

5. 05

   Report the premium as a ratio

   Express the fair rate as a multiple of the matched baseline per hotel, then summarise by ring and star category. Ratios survive currency moves and year-on-year inflation better than absolute differences.

http://USERNAME_pool-arcfast_country-de_city-munich_session-k3f9a1x2_sesstime-10:PASSWORD@proxy.arcproxies.io:8000

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