You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This feature request includes three primary analytics modules to address the specific challenges faced by the city hotel in managing cancellations, revenue optimization, and customer loyalty:
Lead Time Analysis Module
This module would analyze the impact of lead time on booking cancellations and revenue fluctuations. It would provide insights into patterns associated with different lead times and their corresponding cancellation probabilities and revenue impact.
Seasonality and Demand Module
This module would identify seasonal patterns, peak demand periods, and demand fluctuations to help optimize pricing strategies and resource allocation. This module could integrate visualizations of seasonal trends, allowing dynamic adjustments based on historical data.
Customer Segmentation and Personalization Module
This module would categorize customers by demographics, booking behaviors, and preferences, facilitating targeted marketing and personalized offers. Customer segments might include business travelers, leisure travelers, families, and other groups.
Use Case
Forecast Cancellation Rates: With lead time insights, the hotel can predict the likelihood of cancellations, enabling better capacity management and targeted retention efforts for guests likely to cancel.
Revenue Optimization: By understanding seasonal patterns and peak/off-peak periods, the hotel can optimize pricing, develop promotional campaigns, and ensure adequate staffing and resources during high-demand periods.
Enhanced Customer Experience: Through customer segmentation, the hotel can personalize guest experiences and tailor marketing campaigns for each segment, leading to increased satisfaction and loyalty.
Benefits
Reduced Cancellation Rates: This feature would help in developing strategies that reduce cancellation rates by understanding cancellation trends by lead time and customer type.
Higher Customer Retention: With targeted marketing and customized offerings based on customer segments, the hotel is likely to retain more bookings.
Optimized Revenue Generation: Seasonal trend analysis will allow the hotel to price rooms dynamically, capturing maximum revenue during high-demand periods and attracting guests during low-demand periods.
Add ScreenShots
Priority
High
Record
I have read the Contributing Guidelines
I'm a GSSOC'24 contributor
I want to work on this issue
The text was updated successfully, but these errors were encountered:
Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions reach out to LinkedIn. Your contributions are highly appreciated! 😊
Note: I Maintain the repo issue twice a day, or ideally 1 day, If your issue goes stale for more than one day you can tag and comment on this same issue.
You can also check our CONTRIBUTING.md for guidelines on contributing to this project. We are here to help you on this journey of opensource, any help feel free to tag me or book an appointment.
Is there an existing issue for this?
Feature Description
This feature request includes three primary analytics modules to address the specific challenges faced by the city hotel in managing cancellations, revenue optimization, and customer loyalty:
Lead Time Analysis Module
This module would analyze the impact of lead time on booking cancellations and revenue fluctuations. It would provide insights into patterns associated with different lead times and their corresponding cancellation probabilities and revenue impact.
Seasonality and Demand Module
This module would identify seasonal patterns, peak demand periods, and demand fluctuations to help optimize pricing strategies and resource allocation. This module could integrate visualizations of seasonal trends, allowing dynamic adjustments based on historical data.
Customer Segmentation and Personalization Module
This module would categorize customers by demographics, booking behaviors, and preferences, facilitating targeted marketing and personalized offers. Customer segments might include business travelers, leisure travelers, families, and other groups.
Use Case
Forecast Cancellation Rates: With lead time insights, the hotel can predict the likelihood of cancellations, enabling better capacity management and targeted retention efforts for guests likely to cancel.
Revenue Optimization: By understanding seasonal patterns and peak/off-peak periods, the hotel can optimize pricing, develop promotional campaigns, and ensure adequate staffing and resources during high-demand periods.
Enhanced Customer Experience: Through customer segmentation, the hotel can personalize guest experiences and tailor marketing campaigns for each segment, leading to increased satisfaction and loyalty.
Benefits
Reduced Cancellation Rates: This feature would help in developing strategies that reduce cancellation rates by understanding cancellation trends by lead time and customer type.
Higher Customer Retention: With targeted marketing and customized offerings based on customer segments, the hotel is likely to retain more bookings.
Optimized Revenue Generation: Seasonal trend analysis will allow the hotel to price rooms dynamically, capturing maximum revenue during high-demand periods and attracting guests during low-demand periods.
Add ScreenShots
Priority
High
Record
The text was updated successfully, but these errors were encountered: