Overview on Negotiated Rates and Multi-Property Negotiated Rates

Overview on Negotiated Rates and Multi-Property Negotiated Rates

Learning Objectives:

  1. What are Negotiated Rates
  2. What is the difference between Multi-Property Negotiated Rates and Negotiated Rates
  3. What is the Thynk Standard flow for Multi-Property Negotiated Rates and Negotiated Rates 

What are Negotiated Rates

Negotiated rates are special pricing arrangements made between hotels and specific organizations, companies, or groups. These rates are typically lower than the standard public rates and are agreed upon through direct negotiation. Negotiated rates can be beneficial for both the hotel and the client, providing a stable flow of business for the hotel and cost savings for the client. 


What is the difference between Multi-Property Negotiated Rates and Negotiated Rates?


Multi-Property Negotiated Rates (MPNR) are designed for situations where multiple properties are included in a single negotiated agreement. This process automatically creates the corresponding property Negotiated Rate (NR), which streamlines data entry and reduces manual work for your team.

With MPNR, you can work directly on the multi-property negotiated rate or make specific adjustments for the individual properties' negotiated rates.

In contrast, if you only need a single Negotiated Rate for one property, there’s no need to use MPNR—you can simply create the negotiated rate manually.

Regardless of whether you’re using MPNR or NR, you can define key details, including:
  1. Contract start and end dates
  2. Contract type (e.g. local agreement)
  3. Rate type (Static, Dynamic, or Custom)

An example of a standard flow using both Multi-Property Negotiated Rates and Negotiated Rates 

Amanda, a diligent sales representative at a chain of hotels across the United States, receives a request from AppleBook, a major corporate account looking to establish a negotiated rate across all properties in the US. Excited about the opportunity, Amanda decides to streamline the process using the Multi-Property Negotiated Rates (MPNR) feature in Thynk.

  1. Initiating the MPNR Process: Amanda logs into Thynk and navigates to the App Launcher, where she searches for 'Multi-Property Negotiated Rates'. She selects 'New' to create a new MPNR record.

  2. Filling Out Details: In the MPNR record, Amanda fills out the required fields such as the corporate account name (AppleBook) and selects all properties in the US that AppleBook is interested in. She chooses the rate type as 'Dynamic' because AppleBook prefers a percentage discount off the Best Available Rate (BAR).

  3. Defining Rate Details: After saving the MPNR with a status of 'Received', Amanda proceeds to define the specifics of the negotiated rate. Since it's 'Dynamic', she specifies the percentage discount that AppleBook will receive off the BAR rate.

  4. Automated Creation of NRs: Amanda changes the status of the MPNR to 'In-Progress', which triggers the system to automatically create individual Negotiated Rates (NR) for each property selected in the MPNR. Each NR is pre-populated with the rate details defined in the MPNR, ensuring consistency and reducing manual input.

  5. Adjustments and Approval: If any property requires specific adjustments (like different discount percentages or terms), she makes those changes directly in the property's NR. Once satisfied, she moves the NRs to 'Submitted for Approval' according to company procedures.

  6. Offering and Closing: After obtaining managerial approval, Amanda uses MPNR or property NR to create the necessary documents for AppleBook. She sends the negotiated rate offer and updates the NR status to 'Offer Sent'. Depending on AppleBook's response, she updates the status to reflect the negotiation outcome ('Requested Renegotiation', 'Closed - Won', 'Closed - Lost', or 'Closed - Refused').


This streamlined process using MPNR helps Amanda efficiently manage negotiated rates across multiple properties, ensuring accurate rate application and seamless communication with corporate clients like AppleBook.




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