Booking multiple rooms in a hotel
Booking multiple rooms in a hotel
Booking multiple rooms in a hotel
Company
Goibibo
Roles
Product Design & User research
Domain
Online travel
Duration
2021
💡Objective
Enhance the room booking experience for goibibo hotel travellers requiring multiple rooms. The business objective is to increase the conversion of multi-room searches by 10%.
E.g: If a user searched for five rooms and nine adults and we don’t have five rooms, we recommend three triple occupancy rooms, which results in a higher price, improper allocation
🕵🏼♀️ Challenge in Detail
Our selection and experience for multi-room and multi-pax (over two adults) searches are not optimised. Hotel sold-outs (listing page) where multiple rooms of the same type are not available.
Low price competitiveness - Even if some lower category rooms are available, we don’t consider it.
Fewer options for users–We don’t display room categories with less than the required room count (that can accommodate all pax)
The user is forced to book two rooms of the same type. We don’t allow the user to select one triple occupancy and three double-occupancy rooms.
The user is not aware of pax distribution in each room.
Currently, recommendations are generated as per pre-defined logic. We don’t consider user input at room level.
🕵🏼♀️ User research findings
Along with the above challenge, we have a few areas to improve based on our previous user research sessions. Some of them are addressed in this project
Users find it difficult to differentiate rate plan options
Users wanted to have the flexibility to select occupancy for each room instead of pre-defined occupancies
Setting expectations that the booking is different from the original search intent
Users prefer price transparency on all levels
Users not able to figure out more rooms options are available
🧑🏽🔬 Approach & Experiments
The direction was finalised on following structure by combining the learnings . We learned most users like personalised recommendations and wanted to explore more on those.
✏️ Design Principles
Along with the above challenge, we have a few areas to improve based on our previous user research sessions. Some of them are addressed in this project
Progressive information reveal - Only give necessary information to the user, and to no overwhelm with the data
Clean communication - At any part of the selection page, the user should know the state they are in
Transparent pricing across - Making sure the pricing information is shown clearly
The user has been facing difficulty with the pricing is shown in the older way as taxes and pricing is computed at the last stages. With the new approach, we moved to a price + tax approach. The rationale for not going all-inclusive pricing is to maintain parity with competitors and meta (affiliated sites like trivago, google, TripAdvisor) aggregators.
The new approach makes it easier for users to select from combos recommended to them or they can make their own if requirements are more specific.
We realised providing better combos is the first step towards solving complex cases. However, it shouldn't still take over the complete experience for the user. Hence after multiple iterations, we came to the current model of showing 1 combo and collapsing the remaining ones with hinting at what's inside.
Make your combo takes incremental steps to help users to select rooms then a rate plan and repeat the process until they finalise their requirement.
The filters have moved to the top in alignment with the previous pages and better context.
The filters have moved to the top in alignment with the previous pages and better context.
💻 Desktop Design
Keeping the principles the same, we have built a similar experience for our desktop platform for Multiroom Project, yet making use of nuances of the desktop.
✅ Impact
🚀 Reflections & way forward
"Solving for specific users can make all user’s experiences better"
In future,allowing users to split the booking on dates to optimise for the best price
If a search is for 5 days and we have a deluxe room available for 2 days and a super deluxe room for 5 days, we show a recommendation for users to book deluxe for 2 days and super deluxe for the next 3 days
Smarter Recommendations with the flexibility to make any selection with cart flow
Eg. If a user searches for 3 rooms and 6 adults and the cheapest combination is for 2 rooms with triple occupancy
should still also users to book 3 double occupancy rooms or Book 6 single occupancy rooms or 1 quad occupancy and 1 double occupancy rooms
💡Objective
Enhance the room booking experience for goibibo hotel travellers requiring multiple rooms. The business objective is to increase the conversion of multi-room searches by 10%.
E.g: If a user searched for five rooms and nine adults and we don’t have five rooms, we recommend three triple occupancy rooms, which results in a higher price, improper allocation
🕵🏼♀️ Challenge in Detail
Our selection and experience for multi-room and multi-pax (over two adults) searches are not optimised. Hotel sold-outs (listing page) where multiple rooms of the same type are not available.
Low price competitiveness - Even if some lower category rooms are available, we don’t consider it.
Fewer options for users–We don’t display room categories with less than the required room count (that can accommodate all pax)
The user is forced to book two rooms of the same type. We don’t allow the user to select one triple occupancy and three double-occupancy rooms.
The user is not aware of pax distribution in each room.
Currently, recommendations are generated as per pre-defined logic. We don’t consider user input at room level.
🕵🏼♀️ User research findings
Along with the above challenge, we have a few areas to improve based on our previous user research sessions. Some of them are addressed in this project
Users find it difficult to differentiate rate plan options
Users wanted to have the flexibility to select occupancy for each room instead of pre-defined occupancies
Setting expectations that the booking is different from the original search intent
Users prefer price transparency on all levels
Users not able to figure out more rooms options are available
🧑🏽🔬 Approach & Experiments
The direction was finalised on following structure by combining the learnings . We learned most users like personalised recommendations and wanted to explore more on those.
✏️ Design Principles
Along with the above challenge, we have a few areas to improve based on our previous user research sessions. Some of them are addressed in this project
Progressive information reveal - Only give necessary information to the user, and to no overwhelm with the data
Clean communication - At any part of the selection page, the user should know the state they are in
Transparent pricing across - Making sure the pricing information is shown clearly
The user has been facing difficulty with the pricing is shown in the older way as taxes and pricing is computed at the last stages. With the new approach, we moved to a price + tax approach. The rationale for not going all-inclusive pricing is to maintain parity with competitors and meta (affiliated sites like trivago, google, TripAdvisor) aggregators.
The new approach makes it easier for users to select from combos recommended to them or they can make their own if requirements are more specific.
We realised providing better combos is the first step towards solving complex cases. However, it shouldn't still take over the complete experience for the user. Hence after multiple iterations, we came to the current model of showing 1 combo and collapsing the remaining ones with hinting at what's inside.
Make your combo takes incremental steps to help users to select rooms then a rate plan and repeat the process until they finalise their requirement.
The filters have moved to the top in alignment with the previous pages and better context.
The filters have moved to the top in alignment with the previous pages and better context.
💻 Desktop Design
Keeping the principles the same, we have built a similar experience for our desktop platform for Multiroom Project, yet making use of nuances of the desktop.
✅ Impact
🚀 Reflections & way forward
"Solving for specific users can make all user’s experiences better"
In future,allowing users to split the booking on dates to optimise for the best price
If a search is for 5 days and we have a deluxe room available for 2 days and a super deluxe room for 5 days, we show a recommendation for users to book deluxe for 2 days and super deluxe for the next 3 days
Smarter Recommendations with the flexibility to make any selection with cart flow
Eg. If a user searches for 3 rooms and 6 adults and the cheapest combination is for 2 rooms with triple occupancy
should still also users to book 3 double occupancy rooms or Book 6 single occupancy rooms or 1 quad occupancy and 1 double occupancy rooms
💡Objective
Enhance the room booking experience for goibibo hotel travellers requiring multiple rooms. The business objective is to increase the conversion of multi-room searches by 10%.
E.g: If a user searched for five rooms and nine adults and we don’t have five rooms, we recommend three triple occupancy rooms, which results in a higher price, improper allocation
🕵🏼♀️ Challenge in Detail
Our selection and experience for multi-room and multi-pax (over two adults) searches are not optimised. Hotel sold-outs (listing page) where multiple rooms of the same type are not available.
Low price competitiveness - Even if some lower category rooms are available, we don’t consider it.
Fewer options for users–We don’t display room categories with less than the required room count (that can accommodate all pax)
The user is forced to book two rooms of the same type. We don’t allow the user to select one triple occupancy and three double-occupancy rooms.
The user is not aware of pax distribution in each room.
Currently, recommendations are generated as per pre-defined logic. We don’t consider user input at room level.
🕵🏼♀️ User research findings
Along with the above challenge, we have a few areas to improve based on our previous user research sessions. Some of them are addressed in this project
Users find it difficult to differentiate rate plan options
Users wanted to have the flexibility to select occupancy for each room instead of pre-defined occupancies
Setting expectations that the booking is different from the original search intent
Users prefer price transparency on all levels
Users not able to figure out more rooms options are available
🧑🏽🔬 Approach & Experiments
The direction was finalised on following structure by combining the learnings . We learned most users like personalised recommendations and wanted to explore more on those.
✏️ Design Principles
Along with the above challenge, we have a few areas to improve based on our previous user research sessions. Some of them are addressed in this project
Progressive information reveal - Only give necessary information to the user, and to no overwhelm with the data
Clean communication - At any part of the selection page, the user should know the state they are in
Transparent pricing across - Making sure the pricing information is shown clearly
The user has been facing difficulty with the pricing is shown in the older way as taxes and pricing is computed at the last stages. With the new approach, we moved to a price + tax approach. The rationale for not going all-inclusive pricing is to maintain parity with competitors and meta (affiliated sites like trivago, google, TripAdvisor) aggregators.
The new approach makes it easier for users to select from combos recommended to them or they can make their own if requirements are more specific.
We realised providing better combos is the first step towards solving complex cases. However, it shouldn't still take over the complete experience for the user. Hence after multiple iterations, we came to the current model of showing 1 combo and collapsing the remaining ones with hinting at what's inside.
Make your combo takes incremental steps to help users to select rooms then a rate plan and repeat the process until they finalise their requirement.
The filters have moved to the top in alignment with the previous pages and better context.
The filters have moved to the top in alignment with the previous pages and better context.
💻 Desktop Design
Keeping the principles the same, we have built a similar experience for our desktop platform for Multiroom Project, yet making use of nuances of the desktop.
✅ Impact
🚀 Reflections & way forward
"Solving for specific users can make all user’s experiences better"
In future,allowing users to split the booking on dates to optimise for the best price
If a search is for 5 days and we have a deluxe room available for 2 days and a super deluxe room for 5 days, we show a recommendation for users to book deluxe for 2 days and super deluxe for the next 3 days
Smarter Recommendations with the flexibility to make any selection with cart flow
Eg. If a user searches for 3 rooms and 6 adults and the cheapest combination is for 2 rooms with triple occupancy
should still also users to book 3 double occupancy rooms or Book 6 single occupancy rooms or 1 quad occupancy and 1 double occupancy rooms
