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Train tickets sold out? These new MakeMyTrip hacks could get you a seat fast

Train tickets sold out? These new MakeMyTrip hacks could get you a seat fast

Time of India2 days ago

MakeMyTrip
has introduced two new features aimed at improving the
train ticket booking experience
for
Indian travellers
:
Seat Availability Forecast
and
Sold-out Alerts
. These tools are designed to help users navigate unpredictable booking patterns and secure confirmed tickets more efficiently.
Though, Indian railway rules allow passengers to book their tickets 60 days before their intended day of travel. MakeMyTrip's booking data indicates that nearly 40% of users complete their bookings across multiple sessions, often spread over several days. Among this group, close to 70% end up booking waitlisted tickets due to the non-availability of confirmed seats by the time their travel plans are finalized.
Booking patterns vary significantly depending on demand. In April, most high-speed trains were sold out around 13 days prior to departure. By May, due to increased demand, tickets were sold out for at least 20 days in advance. This fluctuation has made it challenging for travellers to accurately gauge when to book.
To address this issue, MakeMyTrip's new Seat Availability Forecast uses predictive models based on historical booking data and real-time demand. The feature estimates when seats on a selected train are likely to sell out, providing greater clarity to users during the planning phase. The feature is now available on both the MakeMyTrip mobile application and website, integrated into the train booking process.
'We are focused on our mission to anticipate and address the nuanced needs of Indian rail passengers,' said
Rajesh Magow
, Co-founder and Group CEO of MakeMyTrip. 'Seat Availability Forecast is a result of that effort, rooted in data science, built to be seamless, and designed to solve a real planning challenge for millions of users.'
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In addition, the platform has launched Sold-out Alerts, which notify users when ticket availability on a selected train falls below a specified threshold. This feature aims to prompt timely bookings, reducing the risk of missing out on confirmed seats.

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