Upload Reservations Using CSV in Portfolio Analytics

Upload Reservations Using CSV in Portfolio Analytics

This feature allows you to upload historical reservations into PriceLabs when switching PMS systems, or when reservations exist in the PMS but cannot be automatically retrieved by PriceLabs. It can also be used to update booking dates if they are incorrect in the PMS or to upload reservation block information that PriceLabs has not received.

Before You Start

  • This feature is available on request. Please contact support@pricelabs.co to request access.
  • Only use this feature for reservations that do not exist in PriceLabs or if the booking date is incorrect.
  • Important: This feature should not be used for current or ongoing reservations already present in the PMS, as these will be automatically synced every 24–36 hours by PriceLabs.

Uses of Manual Reservation Upload

  • Upload old historical reservations when PMS switching occurs and data transfer options are unavailable.
  • Upload direct or offline bookings that PriceLabs cannot retrieve from the PMS API.
  • Update booking dates when they are incorrect in the PMS.
  • Upload reservation block information if the PMS does not send this data to PriceLabs.

How to Upload Reservations

  1. Navigate to Portfolio Analytics (KPIs and Historic Reports).
  2. Click on the three vertical dots in the top right corner.
  3. Download the sample CSV file.

  4. Fill in the necessary information and upload the file.

  5. After uploading, you will receive an email with success or failure details in an attachment.

Correcting Booking Dates for API Reservations

Some PMS sends the reservation creation date instead of the original booking date. The issue arises when users switch PMS and import historical data into their new PMS.

In such cases, the new PMS sends the date the reservation was imported as the booking date, leading to discrepancies in reporting and analysis. We now allow users to fix these incorrect booking dates. Simply follow these steps:

  1. Steps to Correct Booking Dates:

    1. Download the Sample CSV File

      • Navigate to Portfolio Analytics (KPIs and Historic Reports) in PriceLabs.
      • Click on the three vertical dots in the top-right corner.
      • Download the sample CSV file, which includes the format for correcting booking dates.

    2. Export Reservations Data

      • In the Trends by Booking Creation Date section, click the icon with three dots on the upper right corner.
      • Export all reservations to a CSV file.

      • The exported file will include the following details:
        • reservation_id - this has to be unique across a Property Management System
        • listing_id
        • pms_name
        • start_date
        • end_date
        • rental_revenue

    3. Identify and Map Incorrect Booking Dates

      • Open the exported file and identify rows with incorrect booking dates.
      • Map the data to the sample CSV format provided earlier. Ensure that:
        • reservation_id, listing_id, pms_name, start_date, end_date, and rental_revenue are filled from the export.

    4. Fill in Required Fields

      • total_cost: Copy the same values as rental_revenue.
      • currency: Use the currency in which the respective listing operates.
      • pl_status: Always use "booked".
      • Please note: These fields will not be updated in PriceLabs; only the booked_time will be updated for existing reservations.

    5. Upload the Corrected File

      • Refer to the article provided in the help documentation.
      • Upload the corrected reservations CSV with the updated booking dates into PriceLabs.

Please note that this will only update the booking date. No other values will be updated, as we do not allow users to modify API data other than the booking date.

Points to Note

  1. Listing ID: Ensure it matches the one in PriceLabs, or the upload will fail

  2. Make sure listing_id column is in text format.

  3. Mandatory Columns: listing_id, pms_name, start_date, end_date, total_cost (if status is booked), rental_revenue, currency (ISO3 format) & pl_status. 
    1. Reservation_ID is also a mandatory column. Please see number 5.
    2. Although other columns (non-mandatory) that are not listed here are optional in terms of data, their headers cannot be removed. The values within these columns may be left empty if not applicable.
  4. Listings must be unhidden in your PriceLabs account, and Portfolio Analytics should be enabled for the respective PMS.
  5. Reservation_ID: Mandatory. If not provided, the system will get an error: FAILED: reservation_id must be a String
  6. Total_cost and rental_revenue must not be less than or equal to 0 if the pl_status is booked. Please make sure total_cost, rental_revenue and all other revenue related fields should be in numeric form without any symbol or text in it. Example - $25, USD25 are both incorrect ways to provide values.
  7. booked_time cannot be left blank if the status is booked
  8. To modify or update any entry, please upload the revised data using the same reservation ID, or use the above-mentioned format if it was not provided earlier. Furthermore, you can download all reservations with reservation IDs from the 'Trends by Booking Creation Date' section by selecting 'Bookings' in the graph option and downloading the CSV.
  9. pl_status Options: booked, blocked, cancelled & available.
  10. Booking Source Options: airbnb, vrbo, bcom, manual & others.
  11. A maximum of 5000 entries can be updated at a time
  12. If pl_status is canceled, mention cancelled_time else the upload will fail
  13. Do not remove or tamper with mandatory columns. Users can re-order or delete optional columns during upload.
  14. Booked time cannot be greater than start date & end date. Please note booked time refers to booked date. Accepted date formats: YYYY-MM-DD, DD month YYYY, DD.MM.YYYY (e.g., 2019-01-19, 19 January 2019, 19.01.2019.
  15. Ensure the file type remains as CSV. Save as should be used to change the extension if needed (don't use rename to change file extension).
  16. Sometimes in case of large numbers, csv tend to convert them in scientific notation. Make sure you click on 'Don't convert' to keep the original non scientific format as shown in screenshot below.

If you have any questions or need further assistance, please don't hesitate to reach out to our support team at support@pricelabs.co.