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Daily and Weekly Client Report

This article will help you understand what each section in the Daily and Weekly Client Report indicates.

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Written by Michelle Normoyle
Updated over 2 weeks ago

Below are details that will help you understand the daily and weekly client report.

Management Dashboard Information

At the top of the report you will see the property name.

At the top of the report you will see the report name Client Weekly Report or Client Daily Report.

The date and time the report was generated.

The period means this report will show the data for that specific day or week.

  • Sessions - This is the total number of sessions on a property's web page for a given period.

  • Shoppers – The total number of website visitors who clicked on the booking engine rate choose page.

  • Availability – How many of the dates that were searched returned with availability.

  • Bookings – The number of completed bookings made on the booking engine.

  • Total Revenue – The total revenue associated with the bookings.

  • Website effectiveness – Sessions divided by Booking Engine visitors. It reflects the percentage of website visitors who converted into shoppers by visiting the website’s booking engine.

  • Active shoppers – The number of shoppers who entered a date and is still yet to complete their booking.

  • Overall CR (conversion rate) - This is the percentage of website visitor sessions that converted into bookers.

  • Booking Engine CR (conversion rate) – This is the percentage of Shoppers who converted into Bookers.


Website

Total Revenue

The total revenue associated with the bookings.

Total Room Nights

The number of room nights booked In that giving period. This could be the same or higher than the number of bookings, as this looks at the room nights associated with a booking. For example there could be one booking but the booking might be for a three night stay.

Number of Bookings

Number of booking booked in the given period.

Revenue per Room Night

This is calculated by dividing the total room nights by the revenue.

Website Effectiveness

This indicator is calculated in real time based on Google Analytics Sessions/Booking Engine visitors. It reflects the percentage of website visitors who converted into shoppers by visiting the website’s booking engine.

Booking Engine Conversion Rate

This is the percentage of Shoppers who converted into Bookers.

Rate Effectiveness

This represents how effective current rates are.

Availability Effectiveness

This figure represents how effective the room availability is.

Missed Opportunities

The number of searches that happened in the specific period that returned no rates or no availability.

Potential Lost Revenue

The average value of a booking based on estimated revenue.

Unique Shoppers

The total number of website visitors who clicked on the booking engine choose page.

Unique Bookers

The number of guests who made a reservation in a given period. This could be less or the same as the number of bookings, as a one booker could make one or more bookings in that period.

Number of Searches

The number of date searches made in the period.

Searches per Shopper

The average of dates searched by a shopper.

Rooms per Booking

Number of rooms per booking made.

Room Reservations per Day

The average number of bookings made per day on the booking engine based on the last 100 reservations.


Month To Date Booking Revenue By Channel

  • Channel Name – This will say OWNWEB referring to your booking engine. If you have an integration with other providers you may also see the name listed here.

  • Revenue – Revenue in the current month.

  • Revenue YoY - Revenue in same month from the previous year.

  • Diff – Difference in revenue.

  • Cancelled Revenue – The cancelled revenue in the current month.

  • Cancelled Revenue YoY – Cancelled revenue in same month from the previous year.

  • Diff – Difference in cancelled revenue.

  • Net Revenue – Revenue minus the cancelled revenue in the current month.

  • Net Revenue YoY - Revenue minus the cancelled revenue from the previous year.

  • Diff – Difference in revenue minus cancelled revenue.


Vouchers are also included if applicable to your site

  • Voucher Bookings – Number of vouchers that were booked in this period.

  • Vouchers Sold – Vouchers sold will be the same or more than voucher bookings as there could be multiple voucher sold on one voucher booking.

  • Total incl. Fees – Total voucher revenue including fees.

  • Nett Voucher Value – Total voucher revenue excluding fees.


Month to Date Voucher Revenue

  • This Month revenue

  • Last Month revenue

  • YoY revenue

  • Net Vouchers Value – The voucher cost after fees.

  • Average Voucher Sale – The average value of all voucher sold in this period.

  • Vouchers Sold – The number of vouchers sold in this period.

  • Daily Vouchers Sold – The average number of vouchers sold per day in this period.


Cancellations by Channel

  • Channel name – This will typically say website, as the cancellations are made via your booking engine.

  • Cancelled rooms – Number of rooms cancelled in this period.

  • Cancelled revenue – The total revenue associated with the cancelled rooms in this period.


Wait List

  • Revenue on Wait List – Revenue that is associated with a potential reservation currently on the waitlist.

  • Revenue of New Wait List – Revenue that is associated with a potential reservation currently on the waitlist that was made in the period range.

  • Booked Wait List Revenue – Revenue that was on the wait list that was booked.

  • Count of New Wait List – How many new wait list in that period.


Analysis of Active Wait List (last 20 requests only)

  • Information of the potential reservations on the waitlist.


Cancellations – website

The list of the cancelled reservations in the given period.


Last 100 Room Reservations

  • Rate Code - The rates that were booked in this period, represented by the rate code.

  • % - The percentage of the rate booked

  • Room Code – The list of rooms that were booked, represented by their code

  • % - The percentage of the rooms booked

  • Room Nights – The number of room nights associated with the room code and rate code

  • Avg. LOS – Average length of stay of a reservation by the rate and room

  • Avg. Leadin – The average leadin time of bookings made for the room and rate code

  • Avg. Revenue – The average revenue associated with the room and rate code

  • All of the above data is based on the last 100 reservations.


Closed Days

Dates that are closed or has no availability.


Lost Revenue Analysis

  • Opportunity, the list of opportunities.

  • The date of search is searches made on that specific date.

  • The estimated revenue is based on the average price of the last 100 reservations with the same length of stay.

  • Checkin refers to the date the customer choose for checkin.

  • LOS is length of stay of the reservation, 1 or two nights.

  • Comment will always say no rate/availability, this just means the customer didn't get availability for the specific date or for a specific rate.

  • Searches Considered: The amount of searches carried out on booking engine that returned availability.

  • Searches Skipped: The search was ignored, they searched for something not supported on the Booking Engine, for example Over 90 nights.

  • Failed searches: Where availability was not available for example no rooms or rates available.

  • Missed Opportunities: Where there was no availability carried out by on an individual search for example different people or new sessions.


Room Availability

This lists your room types by their code. The number of rooms available on a given date are listed under each room code alongside a specific date. The data is shown for the forty one days.


Demand Graph

This will give an overview of specific dates that had search performed and will highlight what dates have the highest searches. This data will show for the current month and for the next six months. Queries are highlighted by the dark green colour and any date with no availability will be highlighted in red.

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