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The core value proposition of Adani One is to provide a seamless travel booking experience to its users. Adani One currently delivers this proposition by offering:
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Currently, customers experience this value proposition repeatedly through various cross sell/up sell propositions & personalisation for repeat users. For example, upon booking a flight ticket on Adani One, a users get the opportunity to avail a free ride to the airport (worth INR 600). Similarly upon, when a user is trying to book a hotel (2nd time), he/she is shown hotels basis their previous booking history.
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Currently, below is the pattern of frequency observed among the platform users:
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An active user for Adani One is
Non-transacting Active Users:
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Transacting Active Users:
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Engagement Framework | Key Tracking Metric | Selected | Rationale |
Frequency | No.of time a user visits the platform to explore or making a booking (flight/hotel) | Secondary | As user returns to explore or avail a service multiple number of times, they get to experience personalisation, unlimited rewards etc. This helps engage further & experience the value proposition. |
Depth | No.of sessions per user or time spent per session to engage with the platform by searching for products, making bookings etc | NA | While this is a good engagement metric, the depth of options offers in a hotel/flight booking service are limited in nature and majority of the users do not utilise these options. Hence, depth doesn't help experience the core value prop to a great extent. |
Breadth | No.of travel options explored or booked/used by a user | Primary | The more the number of services a user explores or avail during a journey, the more they experience the core value prop of the platform. |
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We will segment our active users (Transacting & Non-transacting users) into casual, core & power users to understand their behaviour & usage of platform better.
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β | Casual Users | Core Users | Power Users |
How did they discover Adani One | Have randomly stumbled upon a marketing ad hook & signed-up on the website | Was referred by a friend/family member & signed up to get reward points. Then started exploring the platform. | Was interested in exploring a deal/discount on the platform basis suggestion from a friends/family and signed up for the same |
Frequency | Visits the platform or avails a service once in 3-6 months | Visits the platform or avails a service once in 1-3 months | Visits the platform or avails a service once in a month |
Breadth | Only checks or avails flight & hotel services | Uses it to check/avail different services beyond flight & hotel (like cabs, duty free, meet & greet etc) | Uses it to explore & avail wide range of services & ancillary options |
Depth | Searches for a flight/hotel & makes the purchase basis 1-2 parameters (Ex: Price, rating, location) | Makes a booking/purchase basis multiple parameters to get the best deals. | Makes a booking basis multiple parameters & search filters. Also, avails ancillary services from the platform |
Product/Features Used | a) Price comparison with competitors b) Ratings & reviews | a) Price comparison across multiple flights & hotels b) Loyalty points redemption | a) Loyalty program b) Travel credit card for better benefits |
Revenue Generated in a Year | INR 10-20 K | INR 20-40 K | INR 60K - 1 Lakh |
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a) Goal: Enhance user engagement on Adani One by introducing a personalised travel recommendation engine powered by a bot called 'TripGenie'. TripGenie should provide tailored travel suggestions basis a user preferences & behaviour on the platform.
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b) Success Metric: TripGenie should result in increased user engagement, thus ultimately resulting in increased booking. The primary metrics to track our DAU/MAU, average time spent, session duration, bounce rate and frequency of usage. The secondary metric to track would be conversion rate (sign up to booking) & repeat bookings.
c) Problem Statement: In today's world, travellers often find it difficult to explore, discover & plan their entire travel due to lack of time & overwhelming scheme of discounts/deals on multiple platforms. This often leads to frustration, decision fatigue and losing users to competitors sheerly due to slightly lower price.
d) Current Alternative: Currently, not just on Adani One, but on all travel websites (MakeMyTrip, EaseMyTrip, ClearTrip etc), users rely on basis search & filtering capabilities to find travel options of their choice. While these tools help narrow down the best options, more often than not, the user will have to put in the effort of inputting all their preferences every single time to find the best options. No platform proactively personalises travel options a good extend. Platforms currently only offer basic recommendations (show similar airline/hotel basis previous booking) and nothing more.
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e) Solution: Offer 'TripGenie' as a personalised travel recommendation engine on the platform. TripGenie will have to track every single movement/behavior of the user & also should take into account past searches, bookings & preferences to customise travel options right in the first go.
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For instance, the moment a user searches for flights from Delhi to Mumbai, Trip genie should provide tailored flight & hotel recommendations.
f) Metrics to be tracked:
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Currently on Adani One, the retention for Day 0 is 70%, day 7 is 20-25%, day 30 is 10-15%, day 90 is 2-5%. The curve seems to have flatted after 60 days.
Tops reasons for churn are:
Voluntary Reasons | Involuntary Reasons |
Price sensitivity | Change in travel plans |
Poor user experience (complex booking process, high load time, ads etc) | Moved to a different country |
Payment failure | β |
Lack of customer support | |
Inadequate travel options | β |
Negative actions I would look for are:
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