Precium
Precium is a Hotel Revenue Management platform built for RedSky Hospitality Group in collaboration with RemoteState. This platform provides a one-stop solution for dynamic pricing of hotel rooms based on data analytics. Revenue managers get access to pricing recommendations and data analysis tools that increase net revenue and profits.
Issuer
RedSKY Hospitality, RemoteState
Team
RemoteState
Deliverables
UX research, screen layouts, typography, colours, components, prototype, user test
Roles
UX Designer, UI Designer, research, testing
Brief
Creating a Property Management System for hoteliers to get pricing recommendations and data analytics in real-time based on historical data, current trends and competitors' pricing.
Process followed
1
Primary Research
Preliminary research was conducted to understand the existing revenue management process. This process included interviews with users, stakeholders and clients, followed by an observation study of the workflow.
Preliminary research was conducted to understand the existing revenue management process. This process included interviews with users, stakeholders and clients, followed by an observation study of the workflow.
2
Defining Problems and Identifying Opportunities
In this phase, I defined problems the hoteliers and their revenue managers faced that needed to be solved. These problems formed the core features of the product. Further interview sessions with the client resulted in the identification of 'good to have' features that were designed and integrated into the product, helping it differentiate from the competitors.
In this phase, I defined problems the hoteliers and their revenue managers faced that needed to be solved. These problems formed the core features of the product. Further interview sessions with the client resulted in the identification of 'good to have' features that were designed and integrated into the product, helping it differentiate from the competitors.
3
Design and Development
In this phase, I created user flows in co-creation sessions with the clients and development team. Following this, I developed the wireframes of the product, validated them with the stakeholders and designed the user interfaces based on them. I collaborated with the developers to make scalable visual design guidelines for future design and development teams.
In this phase, I created user flows in co-creation sessions with the clients and development team. Following this, I developed the wireframes of the product, validated them with the stakeholders and designed the user interfaces based on them. I collaborated with the developers to make scalable visual design guidelines for future design and development teams.
4
Testing and Delivery
I was involved in the beta test of the product with some hotel chains in India. I modified existing features and developed new ones based on the test results, which were then developed and delivered to the client.
I was involved in the beta test of the product with some hotel chains in India. I modified existing features and developed new ones based on the test results, which were then developed and delivered to the client.
The challenge
The existing workflow for determining hotel room prices in India involved a manual and time-intensive process:
Data Collection: Hoteliers reviewed bookings for the upcoming two quarters and shared this data with revenue managers.
Analysis & Recommendations: Revenue managers analyzed booking trends and recommended prices based on factors like historical rates, upcoming events, competitor pricing, and the hotel’s financial targets.
Approval: The pricing data was sent back to hoteliers, who could either accept the recommendations or make adjustments.
This entire process relied heavily on Excel sheets, which posed several challenges. The use of complex formulas and macros made it difficult for non-experts to navigate, increasing onboarding time for new clients. Additionally, the manual nature of the process slowed down operations.
To streamline this workflow, we created a unified platform that automates calculations and enables real-time dynamic pricing recommendations. Revenue managers would focus on trend research , computation and calculation, while hoteliers could directly access and evaluate pricing updates, improving efficiency and user experience. Given the data-intensive nature of this operation, we designed the system with graphs and visual indicators to provide a quick overview, minimizing the time required for data analysis. Backend algorithms periodically update key metrics such as competitor pricing, room demand levels, occupancy rates, and pricing recommendations, ensuring users always have access to the most relevant and actionable information.
Some of the core features are -
Data Collection: Hoteliers reviewed bookings for the upcoming two quarters and shared this data with revenue managers.
Analysis & Recommendations: Revenue managers analyzed booking trends and recommended prices based on factors like historical rates, upcoming events, competitor pricing, and the hotel’s financial targets.
Approval: The pricing data was sent back to hoteliers, who could either accept the recommendations or make adjustments.
This entire process relied heavily on Excel sheets, which posed several challenges. The use of complex formulas and macros made it difficult for non-experts to navigate, increasing onboarding time for new clients. Additionally, the manual nature of the process slowed down operations.
To streamline this workflow, we created a unified platform that automates calculations and enables real-time dynamic pricing recommendations. Revenue managers would focus on trend research , computation and calculation, while hoteliers could directly access and evaluate pricing updates, improving efficiency and user experience. Given the data-intensive nature of this operation, we designed the system with graphs and visual indicators to provide a quick overview, minimizing the time required for data analysis. Backend algorithms periodically update key metrics such as competitor pricing, room demand levels, occupancy rates, and pricing recommendations, ensuring users always have access to the most relevant and actionable information.
Some of the core features are -
Dashboard
The dashboard provides hoteliers with a comprehensive overview of all key data needed to make informed decisions about room pricing. Visual graphs offer insights into business performance, highlighting trends and areas that may require adjustments. Additionally, it displays revenue comparisons against the same period last month and the same period last year, enabling hoteliers to track progress and identify opportunities for improvement.
Pricing Recommendation Feature
This page serves as a central hub for both hoteliers and revenue managers. It provides real-time updates on current room prices, occupancy rates, demand levels, and competitor pricing. The backend computes and periodically updates this data, ensuring users have accurate and timely insights. Hoteliers also have the flexibility to override automated recommendations, empowering them to make adjustments based on specific circumstances or strategic decisions.
A small look into how the tool was designed -
