Quote & Bookings Summary Dashboard 2: Difference between revisions
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|| | ||i. CW booking | ||
<pre>CW_Booking = | <pre>CW_Booking = | ||
CALCULATE (SUM (quotations[chargeable_weight]), | CALCULATE (SUM (quotations[chargeable_weight]), | ||
NOT (ISBLANK (quotations[booked_at])), | NOT (ISBLANK (quotations[booked_at])), | ||
USERELATIONSHIP (DimDate [Date], quotations[booked_at]) )</pre> | USERELATIONSHIP (DimDate [Date], quotations[booked_at]) )</pre> | ||
|| | ii. GW Booking | ||
<pre>GW Booking = | |||
CALCULATE ( | |||
SUM (quotations[gross_weight]), | |||
NOT (ISBLANK (quotations[booked_at])), | |||
USERELATIONSHIP (DimDate [Date], quotations[booked_at])) </pre> | |||
iii. CW Quote | |||
<pre>CW_Quote = | |||
CALCULATE ( | |||
SUM (quotations[chargeable_weight]), | |||
NOT (ISBLANK (quotations[quoted_at])), | |||
USERELATIONSHIP (DimDate [Date], quotations[quoted_at])) </pre> | |||
iv. GW Quote | |||
<pre>GW Quote = | |||
CALCULATE ( | |||
SUM (quotations[gross_weight]), | |||
NOT (ISBLANK (quotations[quoted_at])), | |||
USERELATIONSHIP (DimDate [Date], quotations[quoted_at])) </pre> | |||
|| | |||
i.CW booking | |||
*Sum of chargeable weight: It sums the values from the chargeable_weight column in the quotations table, representing the total weight of items for bookings. | *Sum of chargeable weight: It sums the values from the chargeable_weight column in the quotations table, representing the total weight of items for bookings. | ||
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Purpose | Purpose | ||
This measure helps you track the total chargeable weight for all bookings within a specific date range. | This measure helps you track the total chargeable weight for all bookings within a specific date range. | ||
ii. GW Booking | |||
*Sum of gross weight: It sums the values from the gross_weight column in the quotations table, representing the total weight of items for bookings, including any packaging or additional weight. | *Sum of gross weight: It sums the values from the gross_weight column in the quotations table, representing the total weight of items for bookings, including any packaging or additional weight. | ||
*Checks for a valid booking: It ensures that only rows where the booked_at column is not blank are included. This means it only considers rows where a booking has been successfully made. | *Checks for a valid booking: It ensures that only rows where the booked_at column is not blank are included. This means it only considers rows where a booking has been successfully made. | ||
*Uses the date relationship: It activates the relationship between the DimDate table and the booked_at column, ensuring that the data is filtered according to the selected time range in the report. | *Uses the date relationship: It activates the relationship between the DimDate table and the booked_at column, ensuring that the data is filtered according to the selected time range in the report. | ||
Purpose | Purpose | ||
This measure helps track the total gross weight of all bookings within a specific date range. | This measure helps track the total gross weight of all bookings within a specific date range. | ||
iii. CW Quote | |||
*Sum of chargeable weight: It sums the values from the chargeable_weight column in the quotations table, representing the total chargeable weight for the items being quoted. | *Sum of chargeable weight: It sums the values from the chargeable_weight column in the quotations table, representing the total chargeable weight for the items being quoted. | ||
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Purpose | Purpose | ||
This measure helps you track the total chargeable weight for all quotations within a specific date range. | This measure helps you track the total chargeable weight for all quotations within a specific date range. | ||
iv. W Quote. | |||
*Sum of gross weight: It sums the values from the gross_weight column in the quotations table, representing the total weight of items in the quotations, including packaging and any additional weight. | *Sum of gross weight: It sums the values from the gross_weight column in the quotations table, representing the total weight of items in the quotations, including packaging and any additional weight. | ||
*Checks for a valid quote: It ensures that only rows where the quoted_at column is not blank are included. This means it only considers rows where a quotation has been provided | *Checks for a valid quote: It ensures that only rows where the quoted_at column is not blank are included. This means it only considers rows where a quotation has been provided | ||
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| 9 - Total ||Formula: | | 9 - Total ||Formula: | ||
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) </pre> || The clustered bar chart breakdown total booking by Service | ) </pre> || The clustered bar chart breakdown total booking by Service | ||
|- | |- | ||
| 13 || || This clustered bar chart provides a breakdown of key booking and quotation metrics by year and month. It helps track trends over time and analyze seasonal fluctuations in bookings and conversions. | | 13 ||<pre>Converted_Bookings = | ||
CALCULATE ( | |||
COUNTROWS (quotations), | |||
USERELATIONSHIP (DimDate [Date], quotations[booked_at]), // Temporarily activate the relationship with booked_at | |||
(NOT (ISBLANK (quotations[quoted_at])) || NOT (ISBLANK (quotations[pre_quoted_at]))) && | |||
NOT (ISBLANK (quotations[booked_at])) | |||
) </pre> || This clustered bar chart provides a breakdown of key booking and quotation metrics by year and month. It helps track trends over time and analyze seasonal fluctuations in bookings and conversions. | |||
|- | |- | ||
| 14 || || This clustered column chart provides a detailed breakdown of total quotes categorized by loss reasons. Identify the most frequent reasons for losing potential bookings. | | 14 || <pre>Total Quotes = | ||
CALCULATE ( | |||
COUNTROWS (quotations), | |||
USERELATIONSHIP (DimDate [Date], quotations [quoted at]), | |||
NOT (ISBLANK (quotations[quoted_at]))) </pre> || This clustered column chart provides a detailed breakdown of total quotes categorized by loss reasons. Identify the most frequent reasons for losing potential bookings. | |||
|- | |- | ||
| 15 || || The clustered bar chart provides a detailed breakdown of Total Bookings categorized by Customer. | | 15 ||<pre>Total Bookings = | ||
CALCULATE ( | |||
COUNTROWS (quotations), | |||
NOT (ISBLANK (quotations [booked_at])), | |||
USERELATIONSHIP (quotations [booked_at], DimDate [Date]) | |||
) </pre> || The clustered bar chart provides a detailed breakdown of Total Bookings categorized by Customer. | |||
|} | |} | ||
Latest revision as of 09:18, 17 June 2025
Summary
This page provides a detailed overview of all pre-quotes, quotes, bookings, and direct bookings made within the specified date range. However, instead of focusing on weight breaks, this report breaks down these categories into monthly totals. It also includes a breakdown of customers associated with the bookings and the service types used, as well as insights into the reasons for lost bookings.
Filters
| Filter | Description |
|---|---|
| Database | If you have access to multiple entity databases, you can filter and select specific ones. |
| Hide Lost/Deleted | Hides lost or deleted jobs from the report. |
| Site | Allows you to filter and focus on specific sites within your entity access. |
| Carrier | Enables filtering by carriers associated with the sites you have access to. |
| Users | Filters quotes/bookings by specific users. Users will be listed if they have access to the sites you can access. |
| Origin | Filters jobs based on their origin location. |
| Destination | Filters jobs based on their destination location. |
| Date Filter | Displays only jobs created within the specified date range. |
Calculations

| Reference | Calculation | Description |
|---|---|---|
| 1 - Total Pre-quotes. | Total Prequotes = CALCULATE ( COUNTROWS (quotations), USERELATIONSHIP (DimDate [Date], quotations[pre_quoted_at]), NOT (ISBLANK (quotations[pre_quoted_at])) ) + 0 |
This measure counts the total number of prequotes (draft quotations) created. It works by:
a. Checking if a date exists in the pre_quoted_at column (i.e., the quote was created). b. Using the relationship between the DimDate table and the pre_quoted_at column to filter data for the selected time. c. Counting the rows that meet these conditions. d. It ensures only valid prequotes with a date are included |
| 2- Total Quotes. | Total Quotes = CALCULATE ( COUNTROWS (quotations), USERELATIONSHIP (DimDate [Date], quotations [quoted at]), NOT (ISBLANK (quotations[quoted_at]))) |
This measure counts the total number of finalized quotes created. Here's how it works:
|
| 3 - Total Bookings | Total Bookings = CALCULATE ( COUNTROWS (quotations), NOT (ISBLANK (quotations [booked_at])), USERELATIONSHIP (quotations [booked_at], DimDate [Date]) ) |
This measure counts the total number of bookings made. Here's how it works:
|
| 4 - Confirmed Bookings | Confirmed Bookings = CALCULATE ( COUNTROWS (quotations), NOT (ISBLANK (quotations [confirmed at])), USERELATIONSHIP (DimDate [Date], quotations [confirmed at]) ) |
This measure counts the total number of bookings that have been confirmed. Here's how it works:
|
| 5 - Converted Bookings | Converted_Bookings = CALCULATE ( COUNTROWS (quotations), USERELATIONSHIP (DimDate [Date], quotations[booked_at]), // Temporarily activate the relationship with booked_at (NOT (ISBLANK (quotations[quoted_at])) || NOT (ISBLANK (quotations[pre_quoted_at]))) && NOT (ISBLANK (quotations[booked_at])) ) |
The Converted Bookings formula calculates the total number of quotations that successfully converted into bookings:
|
| 6 - Direct Booking | Direct_Booking = CALCULATE ( COUNTROWS (quotations), USERELATIONSHIP (DimDate [Date], quotations[booked_at]), ISBLANK (quotations[quoted_at]), ISBLANK (quotations[pre_quoted_at]), NOT (ISBLANK (quotations[booked_at])) ) |
This measure counts the total number of bookings that were made without going through a quote or prequote process. Here's how it works:
|
| 7 - Conversion Rate | Conversion Rate = DIVIDE([Converted_Bookings], [Total_Quotes],0) |
This measure calculates the conversion rate, which shows the percentage of quotes that were successfully converted into bookings. Here's how it works:
Purpose This measure helps track how effectively quotes are being turned into actual bookings. A higher conversion rate indicates a better success rate in converting quotes into bookings. |
| 8 | i. CW booking
CW_Booking = CALCULATE (SUM (quotations[chargeable_weight]), NOT (ISBLANK (quotations[booked_at])), USERELATIONSHIP (DimDate [Date], quotations[booked_at]) ) ii. GW Booking GW Booking = CALCULATE ( SUM (quotations[gross_weight]), NOT (ISBLANK (quotations[booked_at])), USERELATIONSHIP (DimDate [Date], quotations[booked_at])) iii. CW Quote CW_Quote = CALCULATE ( SUM (quotations[chargeable_weight]), NOT (ISBLANK (quotations[quoted_at])), USERELATIONSHIP (DimDate [Date], quotations[quoted_at])) iv. GW Quote GW Quote = CALCULATE ( SUM (quotations[gross_weight]), NOT (ISBLANK (quotations[quoted_at])), USERELATIONSHIP (DimDate [Date], quotations[quoted_at])) |
i.CW booking
Purpose This measure helps you track the total chargeable weight for all bookings within a specific date range. ii. GW Booking
Purpose This measure helps track the total gross weight of all bookings within a specific date range. iii. CW Quote
Purpose This measure helps you track the total chargeable weight for all quotations within a specific date range. iv. W Quote.
|
| 9 - Total | Formula:
Total = [Won] + [Lost] + [Pending] |
The Total measure calculates the total count of quotations based on the sum of Won, Lost, and Pending quotations. |
| 10 - Won | Won = CALCULATE ( COUNTROWS (quotations), quotations[spotrate] = 1 && quotations [Booking_categories] = "Direct Booking" ) |
This measure counts the number of "Direct Bookings" where the SpotRate is 1, indicating a successful booking conversion. |
| 11 - Conversion Rate. | Conversion Rate(spotrate) = DIVIDE([Won], [Total],0) |
This measure calculates the conversion rate for SpotRate, which is the ratio of Won bookings to Total quotations. |
| 12. Total Bookings By Service | Total Bookings = CALCULATE ( COUNTROWS (quotations), NOT (ISBLANK (quotations [booked_at])), USERELATIONSHIP (quotations [booked_at], DimDate [Date]) ) |
The clustered bar chart breakdown total booking by Service |
| 13 | Converted_Bookings = CALCULATE ( COUNTROWS (quotations), USERELATIONSHIP (DimDate [Date], quotations[booked_at]), // Temporarily activate the relationship with booked_at (NOT (ISBLANK (quotations[quoted_at])) || NOT (ISBLANK (quotations[pre_quoted_at]))) && NOT (ISBLANK (quotations[booked_at])) ) |
This clustered bar chart provides a breakdown of key booking and quotation metrics by year and month. It helps track trends over time and analyze seasonal fluctuations in bookings and conversions. |
| 14 | Total Quotes = CALCULATE ( COUNTROWS (quotations), USERELATIONSHIP (DimDate [Date], quotations [quoted at]), NOT (ISBLANK (quotations[quoted_at]))) |
This clustered column chart provides a detailed breakdown of total quotes categorized by loss reasons. Identify the most frequent reasons for losing potential bookings. |
| 15 | Total Bookings = CALCULATE ( COUNTROWS (quotations), NOT (ISBLANK (quotations [booked_at])), USERELATIONSHIP (quotations [booked_at], DimDate [Date]) ) |
The clustered bar chart provides a detailed breakdown of Total Bookings categorized by Customer. |