AI-Powered Risk Prediction for Smarter Bookings and Higher Revenue
Improved Booking Platform Revenue By 20% With LSTM-Based Risk Prediction
Leveraging LSTM deep learning, we accurately predicted user cancellation risk on a booking platform, enabling proactive pricing and policy adjustments. This AI-driven approach boosted revenue predictability and increased platform bookings by 20%.
Industry
Sports & Fitness
Country
India
Project Duration
13 Months
Development Method
Agile
Team Size
6 Experts
Project Brief
The project was developed for an internal booking platform, "Book The Play," which was struggling with late-stage cancellations that negatively affected revenue predictability. The primary objective was to proactively identify users likely to cancel their bookings by analyzing their behavioral patterns.
This early detection enables the platform to take preemptive actions or adjust policies to minimize revenue loss and improve overall booking reliability.
Client Overview
Book The Play is a dynamic platform designed to connect sports enthusiasts with sports facilities, fitness centers, and recreational venues, simplifying the process of discovering and booking favorite activities.
Developed by Webelight Solutions, the Book The Play mobile application delivers a user-friendly and efficient experience featuring smooth onboarding, real-time booking capabilities, and secure payment integration to ensure a seamless journey from discovery to play.
Project Challenges
Challenges Our Client Faced
with Late-Stage Cancellations & Dynamic Pricing
Late-stage cancellations threatened revenue consistency, compounded by complex user behaviors. Developing an accurate AI model required overcoming data specificity, behavioral recognition, and dynamic pricing challenges.
Complex Behavioral Patterns
User cancellation behavior was influenced by multiple factors and sequential actions, requiring advanced modeling to accurately detect risks.
Data Specificity
Building a reliable model demanded custom training on platform-specific transactional and behavioral data, which posed challenges in data preparation and feature engineering.
Dynamic Pricing Decisions
Developing an intelligent system to recommend real-time price adjustments that balance demand and maximize bookings required integrating predictive insights with business rules.
Late-Stage Cancellations
Frequent last-minute cancellations disrupted revenue flow, making it difficult to forecast earnings and manage resources effectively.
Maintaining Prediction Accuracy
Ensuring the LSTM model's predictions remained precise over time, despite evolving user behavior and market conditions, required continuous monitoring and tuning.
Scalability and Adaptability
Ensuring that the AI model could scale effectively as the platform grew and adapt to new user behaviors, seasonal trends, and emerging market conditions without compromising performance.
Our Client's Project Solution
AI-Driven LSTM Model
Predictive Cancellation and Revenue Optimization
To tackle the challenge of unpredictable cancellations and fluctuating revenue, we implemented a sophisticated Long Short-Term Memory (LSTM) deep learning model, known for its ability to capture patterns in sequential data like user transactions and behaviors.
01
LSTM-Based Cancellation Prediction
The model utilizes advanced Long Short-Term Memory neural networks to analyze user booking behavior and accurately predict the likelihood of cancellations.
02
Behavioral Sequence Analysis
The model processes detailed sequences of user actions, including bookings, cancellations, and timing intervals, combined with historical transaction records.
03
Custom Training on Platform Data
Tailored specifically to the Book The Play platform, the model predicts the likelihood of a user cancelling future bookings with high accuracy.
04
Dynamic Pricing Recommendations
Complementing cancellation prediction, the system forecasts revenue flow and advises on real-time price adjustments—whether to increase or decrease pricing—to maximize bookings and revenue.
05
Real-Time Risk Scoring
The platform provides cancellation risk scores for individual users, enabling proactive intervention to reduce last-minute cancellations.
06
Seamless Integration
This system easily integrates with existing booking platform infrastructure for smooth deployment without disrupting operations.
Booking Platform Revenue By 20%?
Reduce cancellations by 30%
Increase bookings by 15%
Enhance revenue predictability by 20%
Optimize resources and efficiency
Our Client Project Success
AI At Work
Improved Bookings, Revenue, And Resource Allocation
The AI-powered solution significantly enhanced revenue predictability, reduced late-stage cancellations, boosted bookings, and optimized resource allocation.
20% Increase In Revenue Predictability
The AI-powered LSTM model enabled more accurate forecasting by proactively identifying cancellation risks.
15% Boost In Overall Bookings
Dynamic pricing recommendations optimized arena rates, attracting more users and increasing booking volume.
30% Reduction In Late-Stage Cancellations
Early detection of high-risk users allowed the platform to take preventive measures, significantly lowering last-minute booking cancellations.
10% Improved Resource Allocation
By understanding cancellation probabilities, the platform optimized staffing and inventory management, reducing operational inefficiencies.
Banking Industry Use Case
Expanding AI-Powered Risk
Detection Beyond Booking Platforms
The AI-powered risk detection & revenue optimization solution can be adapted to address challenges in the banking sector. At Webelight Solutions, we possess deep expertise in advanced AI models tailored to diverse industries.
Customer Segmentation
Utilizing behavioral and transactional data to create precise customer profiles for targeted marketing and personalized banking services—improving engagement and satisfaction.
Churn Prediction
Predicting customers likely to leave or reduce activity, enabling proactive retention campaigns to minimize attrition.
Fraud Detection
Identifying suspicious transaction patterns early to prevent financial fraud and protect assets.
Credit Risk Assessment
Enhancing credit decision accuracy by analyzing behavioral data alongside traditional credit scoring models.
Why Choose Us
Why Choose Webelight Solutions
For AI-Powered Risk Detection?
Proven Expertise In AI & Deep Learning
Our team specializes in developing advanced models like LSTM networks that excel at behavioral pattern recognition and predictive analytics.
Customized Solutions
We tailor AI models to your specific data and business goals, ensuring maximum relevance and accuracy.
Seamless Integration
Our AI tools are designed to fit smoothly into your existing platform infrastructure without disrupting operations.
Data Security & Compliance
We prioritize data privacy and adhere to industry standards to keep your information safe and secure.
End-To-End Support
From initial consultation and development to deployment and ongoing optimization, we provide comprehensive support.
Cross-Industry Capabilities
Beyond booking platforms, our AI solutions are adaptable for banking, retail, healthcare, and more.
FAQs
Common Questions
We've compiled a list of frequently asked questions with clear and concise answers.
Booking Platform with AI-Powered Precision
Transform your booking platform with cutting-edge AI that anticipates user behavior, reduces cancellations, and optimizes pricing strategies.
Our Work
Explore More Case Studies
10+
Years of Experience
25+
Countries Served
110+
Tech Specialists
4.9/5
Star Ratings on Clutch
500+
Successful Digital Products
15+
Industries Served
