AI-Based Booking engine increased booking efficiency by 30%

27 February 2020
#AI #BookingEngine #Hospitality #MachineLearning #SocialMedia #email

About Client

The client is one of the top clients in India. The company has over hundreds of luxury hotels and resorts across the world. It is also constructing various other properties into different locations.

Problem statement

The client, with so many customers, had to tackle problems that would result in the following pain points:

  1. Customer Drop-offs while booking for Hotel rooms
  2. Hotel selection and room selection was incorrect, resulting in the cancellation of bookings


SignOn demonstrated technology that used automation to overcome the issues, following were the key points that merged to get an effective result:

  1. Implemented machine learning algorithm to analyse and correct drop-offs at each stage of customer journey using predictive modelling and identifying the correct room based on customer profile

  2. . Customer profile and journey mapped using history, likes, page views

  3. Presenting the right room features depending on the customer profile. Eg. Business travellers wanted a cab to be part of the package, vacationers wanted sightseeing etc

  4. Customer email was collected at the appropriate stage to retarget them for booking closure with a timer on the rate.

Configuration and Deployment timeline - 2 Months Study, 4 Months Deployment, 2 Months Transition Time to Go Live - 6 Months from Contract


  • 30% Increase in booking efficiency
  • This resulted in a substantial uplift in site visitors with 24%
  • High on-site spend and brand awareness
  • Web and social media activity had also increased dramatically

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