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Travel Analysis column headers and filters
Travel Analysis column headers and filters

Look up the data fields that the Travel Analysis report template uses

Hayley Marsden avatar
Written by Hayley Marsden
Updated over 4 years ago

How Click Travel uses data fields in Reporting

The Travel Analysis report template uses a standard set of data fields that provide: 

  • Filters You can set up filters on most of the data fields to limit the data that a report outputs. For example, you can add a filter to the travel_type data field to limit the report to one travel type. 

  • Raw data The reports that you download to Excel provide a column of raw data for each data field.

Labels

Each data field has a label (e.g. booking_id) and we list these below with their definitions.

All labels are case sensitive. The standard data field labels that we provide use lowercase only.

Custom data fields

Custom fields that you set up to collect custom data on bookings become data fields automatically. Like the standard data fields, you can use custom data fields as filters. The custom data also gets included in the report’s raw data.

Labels for custom fields use the following format: cust_data.ID, where ID is the custom field's ID in Team Admin. It just so happens that ID can be uppercase or lowercase. For example, when ID is set to Cost-code, the data field label becomes cust_data.Cost-code.
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Travel Analysis data fields

The Travel Analysis report template uses the data fields in the list below. Each data field has a label and a definition.

Note Lead time and Short/Long Haul, which show in the raw data, are not data fields and are calculated instead.

  • booking_id The email address of the booker who made the booking.

  • team_name The name of the team that made the booking.

  • travel_type The type of travel booked (e.g. Train, Hotel).

  • status Status of booking (e.g. CONFIRMED, FULFILLED)

  • booking_date The date that the booking was confirmed.

  • service_date The start date of the booked travel (e.g. check-in date).

  • booker_name The name of the booker who made the booking.

  • booker_email The Click Travel email of the booker who made the booking.

  • booker_id The unique Click Travel identifier of the user who made the booking.

  • traveller_name The name of the traveller who is booked on the service.

  • traveller_email The Click Travel email of the traveller.

  • traveller_id The unique identifier of the traveller profile.

  • booking_method Indicates whether the booking is an online or offline booking.

  • duration Number of nights booked (hotels only).

  • international Indicates whether the booking is international or domestic.

  • total The total cost of the product purchased (e.g. for a hotel, this is rate * number of nights).

  • net The net cost of the booking.

  • tax The tax cost of the booking

  • form_of_payment Form of payment used for the booking.

  • rate The rate at which the product was booked (e.g. hotel room for one night, outbound train ticket).

  • bench_rate The rate that provides a benchmark to measure the low rate, high rate and exposure rate against. For all travel apart from trains, the bench_rate is equivalent to the rate. But since return train journeys can be a mix of 2 single tickets, we calculate the bench_rate for trains as follows: bench_rate = (outbound rate + inbound rate) / 2.

  • low_rate The lowest policy-compliant rate available.

  • high_rate The highest rate allowed within the travel policy.

  • exposure_rate The difference between the booked rate (rate) and the highest rate (high_rate) in the search results. This gives you an indication of your exposure if you chose not to apply a travel policy at all. To find out more, read our savings methodology.

  • service_fees The cost to make the booking.

  • billback_fees An additional cost for using billback.

  • fulfillment_fees The cost of sending out train tickets (e.g. postal charges, SMS charges).

  • realised_savings The difference between the highest rate your travel policy allows (high_rate) and the booked rate (rate). Shows that a higher rate was available that was policy-compliant, but the booker chose to take a lower rate and save the company money. To find out more, read our savings methodology.

  • potential_savings The difference between the booked rate (rate) and the lowest rate your travel policy allows (low_rate). Indicates where your staff have chosen consciously to take a higher rate than others available in the market. But this higher rate is still within the limitations of your travel policy. To find out more, read our savings methodology.

  • authorised_spend The amount that a traveller is authorised to spend per night on a hotel. Calculated as total billback allowed + room rate. (Hotels only)

  • service_cost The cost of the booking excluding additional extras, .

  • additions Any additions booked that are not part of the product (e.g. breakfast or additional baggage, if not included already).

  • co2_emission Carbon footprint monitoring and reporting are integrated into Click Travel. For each booking made, the distance travelled and C02 emitted as a result are calculated in accordance with DEFRA guidelines and stored with the booking. (https://www.gov.uk/measuring-and-reporting-environmental-impacts-guidance-for-businesses)

  • policy_compliance_state Indicates whether or not the booking is compliant with your team’s travel policy.

  • product Summary details of the product (e.g. for a hotel booking: hotel name and location, date and number of nights).

  • supplier The supplier that the booking has gone through.

  • location The location of the hotel booked.

  • payment_option The type of payment (e.g. Pre-pay, Elements, All costs). (Hotels only)

  • billback_type Shows what billback includes for this booking, e.g. room rate, breakfast, parking, meal supplement. (Hotels only)

  • ticket_type The type of train ticket booked (e.g. Advance Single, Off-Peak Return). (Trains only)

  • service_class The class at which the ticket was purchased (eg STANDARD for trains, TT - TT for flights).

  • delivery_method The method of ticket collection chosen for the booking. (Trains only)

  • alliance_code The alliance(s) that the airline(s) booked is/are part of (e.g. British Airways is part of One World). (Flights only)

  • ticket_number The ticket reference supplied by the airline. (Flights only)

  • route The route booked (e.g. Birmingham New Street  - Birmingham International).

  • route_key The route booked in a code format (e.g. BHM-BHI-SGL).

  • trip_type The type of ticket purchased (e.g. Single, Return, Multi-city).

  • trip_distance When travel type is a form of transport, shows distance between start point and end point.

  • channel The channel through which the product was purchased (e.g. OpenRail, Premier Inn, Booking.com)

  • carriers The name of the operator booked (e.g. XC, VT). (Trains only)

Calculated data fields

The following report values are calculated at run-time:

  • lead time

  • long-haul

  • short-haul

  • realised savings

  • missed savings

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