AP-ICE AI-Powered Hotel Booking Optimization
An AI-driven hotel booking system that analyzes weekly and montly booking trends using Gemini GenAI, generates marketing campaigns via AI, Bannerbear, and posts them automatically on Instagram.
Created on 28th September 2024
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AP-ICE AI-Powered Hotel Booking Optimization
An AI-driven hotel booking system that analyzes weekly and montly booking trends using Gemini GenAI, generates marketing campaigns via AI, Bannerbear, and posts them automatically on Instagram.
Describe your project
Overview:
The Hotel Booking Optimization System utilizes GenAI to analyze booking data and predict low occupancy rates, enabling hotel management to create automatic targeted marketing campaigns and optimize pricing strategies. The system is designed to improve occupancy rates and enhance overall revenue management through data-driven insights.
In-Scope Features:
Data Analysis: The system analyzes weekly booking data, comparing it to past weeks to detect trends and identify declines in occupancy rates of last minute room bookers.
It also analyzes next month booking data with past season data to detect trends and identify decline in occupancy rate of early or advanced room bookers.
AI Insights Generation: It leverages GenAI to generate actionable insights based on the analyzed data, providing recommendations for targeted marketing strategies.
Dynamic Offer Pricing: The solution automatically calculates offer prices using insights derived from GenAI, adjusting them based on booking trends to attract more customers.
Integration with Third-Party APIs: It utilizes the Bannerbear API for creating visually appealing promotional images based on the generated insights, and the Instagram API for automatic posting of these campaigns to enhance visibility.
User Dashboard: A comprehensive dashboard allows hotel staff to view real-time analytics, insights, and campaign performance metrics.
Out of Scope:
Customer Relationship Management (CRM): The system does not encompass CRM functionalities, such as customer communication or engagement tracking.
On-Site Operations: Features related to on-site hotel management, such as staff scheduling or guest services, are outside the project's scope.
Future Opportunities:
1.will also develop advanced algorithms for detecting low booking rate considering the external factors like climate and other local conditions in that area
2.Adding feedback loops in place to evaluate the effectiveness of campaigns
Challenges we ran into
1.The website i made for users to book rooms is not compatible for mobile phones,it is not responsive.my website looks good in desktop pcs.
2.Tuning the gen ai model for my use case was harder,mainly for accurate results,later with few quality prompts i was able to tune it.
3.currently for the low occupancy rate detection,we are only using current week,next month data and past booking data and send it to gemini gen ai ,in future we will add the external factors like climate and other local events and factors in that area.
4.I was not able to find a free service to host my web app initially ,later i found that i can use render to host my both database and backend code seperately.
5.Integrating with the Bannerbear and Instagram APIs presented authentication issues and rate limiting, causing delays in the automated posting of campaign images.,later i followed their official docs and integrated them
Tracks Applied (1)
11. Problem statement shared by RateGain
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