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For Lodging Properties

For lodging properties in Furano: our request for your reservation data, and what you can see on your property pages once you share it.

Our request for your data

We are asking lodging properties in Furano to share their own reservation data. Once you do, you can use the property pages listed under “What you can see once you share your data” with your own figures.

The data we ask for

  • A list of reservations (a CSV or Excel file exported from your PMS or a similar system). We use the booking date, stay date, nights, room type, rooms, guests, rate and sales channel columns.
  • The number of rooms for each room type (entered on screen the first time you import).
  • Fresh exports from time to time (reservations change every day, so importing a new export updates the outlook).

Columns with personal information such as names, phone numbers and email addresses are removed in your browser before anything is sent. Imported data is displayed only on that property's pages, to the staff designated by the property corporation. It is shown to other property corporations, on the business pages and on public pages only as statistical information (how the operator and its contractors handle it is under “How your data flows” below).

FURANO LOOP is a tool for lodging properties: it uses your own reservation data to check the month-end outlook and booking pace, and to compare draft pricing and sales policies. The “Tourism & Lodging in Furano” and “District Tourism & Lodging” pages show the regional trends behind those decisions.

Decisions become more concrete when you set these trends against your own outlook and booking pace.

Go to property pages

Property pages are for invited users and require logging in.

What you can see once you share your data

On your property pages, you can check the following from your own reservation data. The examples below use synthetic figures.

  • Property home

    Check which step to start from (targets, outlook, day-by-day actions, look back) and which days need action this week (days where only you are behind, days to consider a price rise).

  • Outlook

    See the outlook for monthly revenue, occupancy and ADR (with a range and confidence) against your target, the room types that fall short, and the days short of target with their cause (your property or the area).

  • Sales calendar

    See rooms booked for each day and the cause marks on days short of target alongside local events. Choose a day to compare its bookings with last year and similar days, and decide what to do.

  • KPI report

    Review past months' results against last year and your targets.

  • Demand forecast

    Check the demand outlook for future dates, by day and by month.

  • Reviews & quality

    See your review scores and aspect scores month by month.

What you can see on property pages (examples)

The three cards below are examples made with synthetic figures. On property pages, the month-end outlook and the booking pattern come from your own reservation data. Review aspects come from review aggregates.

Within what range is this month's revenue likely to end up?

Example (synthetic figures, not a real property)

Monthly revenue outlook (synthetic property: 20 rooms, 30 days)

Medium confidence
Low
¥6,700,000
Expected
¥7,128,000
High
¥7,556,000

Source: Synthetic figures (a sample made by the code of this page, not a real property or real bookings)

The band runs from low to high, the solid vertical line is the expected value and the dashed vertical line is the target. Forecasts are shown with a range, a confidence level and their source.

What you can see on property pages: Property home, Outlook

How many days before the stay do bookings come in?

Example (synthetic figures, not a real property)

7 days before: this day 13 rooms, usual pattern expected 13 rooms, same day last year 11 rooms.

Horizontal axis: days before the stay date (farthest on the left; 0 on the right edge is the stay date). The ticks are evenly spaced, but the intervals in days are not equal (90, 60, 45, 30, 21, 14, 7, 3, 1, 0 days before).

Vertical axis: rooms booked for this night at that point (rooms). Starts at 0.

The usual pattern is a band made by multiplying your property's settled booking pattern (low, expected and high by season, day of week and days before the stay) by the final rooms sold on the same day last year.

View as table
90 days before
This day 1 rooms, Typical pickup Expected 1 rooms (low 1 rooms – high 1 rooms), Same day last year 1 rooms
60 days before
This day 4 rooms, Typical pickup Expected 4 rooms (low 4 rooms – high 4 rooms), Same day last year 4 rooms
45 days before
This day 6 rooms, Typical pickup Expected 6 rooms (low 5 rooms – high 6 rooms), Same day last year 5 rooms
30 days before
This day 8 rooms, Typical pickup Expected 8 rooms (low 7 rooms – high 9 rooms), Same day last year 7 rooms
21 days before
This day 10 rooms, Typical pickup Expected 10 rooms (low 9 rooms – high 11 rooms), Same day last year 8 rooms
14 days before
This day 11 rooms, Typical pickup Expected 11 rooms (low 10 rooms – high 12 rooms), Same day last year 10 rooms
7 days before
This day 13 rooms, Typical pickup Expected 13 rooms (low 12 rooms – high 14 rooms), Same day last year 11 rooms
3 days before
This day —, Typical pickup Expected 14 rooms (low 13 rooms – high 15 rooms), Same day last year 12 rooms
1 days before
This day —, Typical pickup Expected 15 rooms (low 14 rooms – high 16 rooms), Same day last year 14 rooms
Stay date
This day —, Typical pickup Expected 16 rooms (low 14 rooms – high 17 rooms), Same day last year 15 rooms

Source: Synthetic figures (a sample made by the code of this page, not a real property or real bookings)

What you can see on property pages: Sales calendar

How does each review aspect score?

Example (synthetic figures, not a real property)

For each aspect, the average of the scores (1–10) of the reviews that mention it. Reviews that do not mention the aspect are not counted.

The review aspects on property pages come from review aggregates, not from reservation data. They appear only for properties whose own review aggregates have been imported.

View as table
Staff, service & hospitality
6.0
Cleanliness & hygiene
7.7
Room, bed & comfort
6.3
Bathroom, toilet & shower
8.0
Hot spring, large bath & sauna
6.6
Food, breakfast, dinner & restaurant
8.3
Facilities, amenities & common areas
6.9
Location, surroundings & views
8.6
Access, transfers & parking
7.2
Quietness, noise & sleep
8.9
Wi-Fi & connectivity
7.5
Price & value for money
6.1

Source: Synthetic figures (a sample made by the code of this page, not a real property or real bookings)

What you can see on property pages: Reviews & quality

After checking these three on property pages, you can see why some days fall short of target in the Sales calendar and record day-by-day actions in the day diagnosis.

What you can see on property pages: Sales calendar

Try the demo

You can view the property pages of a demo property built with synthetic data, without signing in. All figures are synthetic and unrelated to any real property. The demo is view-only: you cannot change settings or save plans.

If you are signed in, you will be switched to the demo account. Sign out when you are done with the demo.

How your data flows (Draft)

How data is handled after import, based on what the property page user terms and the privacy policy say.

  1. Register from an invitation

    The property pages are by invitation only. You register your own name and password through an invitation from the property corporation or the operator.

    Basis: Property page user terms, “Article 3 (Registration and Accounts)”

  2. Import reservation data

    Guest information such as names, phone numbers, email addresses and addresses is removed inside the property's device. Reservation numbers are replaced with values that cannot be reversed before being stored.

    Basis: Property page user terms, “Article 5 (Importing Property Data)”Basis: Privacy policy, “Article 6 (Handling of Property Data)”

  3. View it on your property's pages

    Property data is displayed only on that property's pages, to the staff designated by the property corporation. It is shown to other property corporations, on the business pages and on public pages only as statistical information.

    Basis: Privacy policy, “Article 6 (Handling of Property Data)”

  4. How the operator and its contractor handle data

    The operator handles property data only within the scope of the outsourcing agreement with the property corporation and the items, granularity and methods of provision agreed under it. The development, operation and maintenance of the service and the handling of inquiries are outsourced to a contractor, which the operator supervises as necessary and appropriate.

    Basis: Privacy policy, “Article 6 (Handling of Property Data)”Basis: Privacy policy, “Article 11 (Outsourcing)”

  5. Pricing and sales decisions are made by the property

    The landing outlook, demand forecasts, recommended selling prices and the like are projections and reference information and do not promise future results. Selling prices, inventory, targets and other management decisions are made by the property corporation and its users.

    Basis: Property page user terms, “Article 6 (Nature of the Displayed Information)”