Upload Reservations Using CSV in Portfolio Analytics

Upload Reservations Using CSV in Portfolio Analytics

Introduction

This feature is particularly useful:
  1. To upload old historical reservations when PMS is switched and there is no method available to transfer old PMS/OTA data to the new PMS.
Warning
In the event of a PMS switch, we recommend uploading old PMS reservation data directly into the new PMS rather than using this feature, unless the new PMS does not provide an upload option.
  1. To upload reservations that do not exist in PriceLabs and were created before 48 hours. This could include direct or offline bookings which cannot be uploaded in the PMS, or PriceLabs does not retrieve them through the PMS API.
  2. This allows updating the booking date and time if it’s incorrect in the PMS. Please note that the CSV will only update the booked_date; any other changes related to that reservation will be ignored.
  3. Additionally, the feature can be leveraged to upload reservation block information if PriceLabs does not receive that data from the PMS.
Warning
Under no circumstances should this feature be used to upload current or ongoing reservations which are already there in current PMS, as PriceLabs is supposed to fetch these from the PMS every 24/36 hours. If users upload them prematurely, there is a risk that, when PriceLabs retrieves the data from the PMS, revenue and occupancy metrics may be duplicated
Please contact support@pricelabs.co to request enabling this feature. This feature is available on a request basis to ensure users are well-informed about all important points before using it.

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, select the "Bookings" option from the graph dropdown.



      • Export all reservations to a CSV file.

      • The exported file will include the following details:
        • reservation_id
        • 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.

  4. Listings must be unhidden in your PriceLabs account, and Portfolio Analytics should be enabled for the respective PMS.

  5. Reservation_ID: Optional. If not provided, the system will generate it based on the format: Listing ID _ Start Date _ End Date

  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, canceled & 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 is actually is booked date in the below mentioned acceptable formats.

  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. Accepted date formats: YYYY-MM-DD, DD month YYYY, DD.MM.YYYY (e.g., 2019-01-19, 19 January 2019, 19.01.2019.

  17. 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

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