Our AI-Powered Customer Scoring Model's Assistance in Predicting 60% of Ticket Cancellations

Artificial intelligence

Executive Summary

One of the oldest established travel companies in the world, the client’s roots go back to British rule. From weekend gateways to the month-long expedites, the client has gained recognition for their meticulous tour planning and delightful tour experience. With an abundance of awards, the travel leader is planning to start offices in Africa and Asia.

Client Challenges

  • Since the client has included all the major tourist destinations in the world in their offerings, it had to manage a huge number of bookings.
  • Along with its growing footprints in multiple geographies, the number of bookings also saw exponential growth.
  • Though bigger order values boost the profit considerably, they also bring with them order management problems.
  • With increasing bookings, the client also saw an increased number of planned or last-minute cancellations. This included both individual and group bookings.
  • Considering that it’s very difficult to transfer the last minute canceled booking to other customers, especially of the long tours, those bookings went unsold. Consequently, it affected the bottom line of the client.
  • To avoid the revenue leakage, the client was in need of a reliable, easy-to-use and flexible model which can identify the customers who are likely to cancel the tickets.
  • Its absence robs the client of data-backed prediction of high-risk ticket cancellations and thereby the accurate demand forecasting.

Our Solutions

In the preliminary examination of our client’s problem, we found that they had no reference data to predict the cancellation. They didn’t gather the analytics insights like what people with which age group, demographics, and income group have canceled the tickets more in the past. Also, they were without any analysis about which season and which destination saw more cancellations. Resultantly, this made it impossible for the client to create the “most-probable-cancellation-scenario”.

To overcome it, we began with data preparation and data analysis and created a phased customer scoring model including Profiling, Modeling, and Measurement which were tailed by data analysis phase.

Data Preparation

  • Created data dictionary
  • Investigated the variable fill rate and overall quality check
  • Worked on the sampling strategy
  • Included master dataset creation validation


  • Created Variable Prioritization through scientific correlation and CART variable ranking
  • Made customer profiling stronger through missing Imputation, outlier Treatment and deriving variable creation


  • Founded a logistic model based on raw variables and CART’s multiple iterations
  • Checked the model stability & robustness
  • Used Gains Curve and Lift Curve to measure the performance of the logistic model


  • Quantified the performance of the model in terms of lift, gains on Out-of-Sample Validation

Technology Stacks

  • Cloud Design: AWS, Azure, Apache Tomcat
  • Server Implementation: Java, MySQL, MongoDB based implementation
  • Software: Java, J2EE, JS Query

Quantifiable Benefits

  • With a scientifically distilled data at its disposal, the client was able to individually profile each and every customer
  • Due to the analysis of the past pre-cancelation behavioral and communication, the client identified 60% of the cancellations
  • 22% rise in conversions, as data analytics allowed the client to send personalized and targeted travel offers to their customers

About Futurism Technologies

Futurism Technologies is a global business leader, that bringing 360-degree Digital Transformation for business enterprises of various sizes, as well as technology providers by delivering assured business efficiency through a set of new-age technologies. We provide end-to-end high quality and cost-effective IT services to a variety of industries. With state of the art offices in India, US, UK, Australia, and UAE, we have become a global trusted partner of our clients by delivering age-defining and convention-defying digital transformation solutions.

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