From Legacy Platform to High-Conversion Digital Engine
From Legacy Platform to High-Conversion Digital Engine
From Legacy Platform to High-Conversion Digital Engine
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Problem
Statement
Problem
Statement
Problem Statement
As part of Air India’s Vihaan.AI digital transformation, we identified a growing friction among the airline’s most valuable customers — frequent flyers and loyalty members. Despite major improvements to the core booking engine, repeat customers were still forced to go through multi-step booking flows for routes they flew every week.
Business travelers, corporate customers, and loyalty members repeatedly booked the same city pairs, fare classes, and seat preferences, yet the digital experience treated each booking as a new journey. This resulted in wasted time, higher abandonment, and lost opportunities to deepen loyalty engagement.
As part of Air India’s Vihaan.AI digital transformation, we identified a growing friction among the airline’s most valuable customers — frequent flyers and loyalty members. Despite major improvements to the core booking engine, repeat customers were still forced to go through multi-step booking flows for routes they flew every week.
Business travelers, corporate customers, and loyalty members repeatedly booked the same city pairs, fare classes, and seat preferences, yet the digital experience treated each booking as a new journey. This resulted in wasted time, higher abandonment, and lost opportunities to deepen loyalty engagement.
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What was Broken?
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What was Broken?
A legacy experience was holding back a
high-frequency digital journey
A legacy experience was holding back a
high-frequency digital journey
A legacy experience was holding back a
high-frequency digital journey
The existing booking experience had accumulated friction across a journey used repeatedly by frequent travelers. The goal was not simply to refresh the interface; it was to turn a fragmented, legacy experience into a scalable digital platform that could support a modern airline brand and a more efficient booking journey.
The existing booking experience had accumulated friction across a journey used repeatedly by frequent travelers. The goal was not simply to refresh the interface; it was to turn a fragmented, legacy experience into a scalable digital platform that could support a modern airline brand and a more efficient booking journey.
The existing booking experience had accumulated friction across a journey used repeatedly by frequent travelers. The goal was not simply to refresh the interface; it was to turn a fragmented, legacy experience into a scalable digital platform that could support a modern airline brand and a more efficient booking journey.
Frequent flyers had to repeat full booking flows
Frequent flyers had to repeat full booking flows
No intelligent memory of routes, seat, or fare preferences
No intelligent memory of routes, seat, or fare preferences
Loyalty bookings required the same steps as first-time users
Loyalty bookings required the same steps as first-time users
High friction reduced loyalty engagement and repeat purchases
High friction reduced loyalty engagement and repeat purchases
My Leadership
& Role
My Leadership
& Role
My Leadership & Role
I led the UX strategy and product experience design for Ez Booking, working across concept, interaction design, design-system extension, and cross-functional alignment.
I led the UX strategy and product experience design for Ez Booking, working across concept, interaction design, design-system extension, and cross-functional alignment.
I owned
I owned
End-to-end UX strategy and product experience desigN
End-to-end UX strategy and product experience desigN
Information architecture, user flows and interaction patterns
Information architecture, user flows and interaction patterns
Conversion-focused booking journeys
Conversion-focused booking journeys
Mobile-first experience principles
Mobile-first experience principles
Reusable design patterns and design-system alignment
Reusable design patterns and design-system alignment
Experience quality and consistency across the journey
Experience quality and consistency across the journey
I influenced
I influenced
Product and engineering teams to shape feasible, scalable solutions
Product and engineering teams to shape feasible, scalable solutions
Data and analytics partners to identify behavior and friction
Data and analytics partners to identify behavior and friction
Business stakeholders to align customer experience with commercial goals
Business stakeholders to align customer experience with commercial goals
Design partners to maintain consistency across the wider digital ecosystem
Design partners to maintain consistency across the wider digital ecosystem
Research
& Discovery
Research
& Discovery
Research & Discovery
The work was grounded in behavioral signals and the realities of a high-frequency travel journey. We examined how customers navigated booking, where repeated effort appeared, and which parts of the experience created unnecessary friction.
Behavioral patterns — Identify repeated booking behavior and opportunities to reduce repetitive work.
Customer needs — Understand expectations around speed, clarity, preferences and confidence during booking.
Experience audit — Map legacy screens and interaction patterns to identify inconsistency and avoidable complexity.
Competitive context — Look at how digital travel products simplify repeat actions and reduce decision effort.
The work was grounded in behavioral signals and the realities of a high-frequency travel journey. We examined how customers navigated booking, where repeated effort appeared, and which parts of the experience created unnecessary friction.
Behavioral patterns — Identify repeated booking behavior and opportunities to reduce repetitive work.
Customer needs — Understand expectations around speed, clarity, preferences and confidence during booking.
Experience audit — Map legacy screens and interaction patterns to identify inconsistency and avoidable complexity.
Competitive context — Look at how digital travel products simplify repeat actions and reduce decision effort.
Key Insight
The opportunity was bigger than modernizing individual screens: the booking experience needed a clearer, more scalable interaction model for customers who already knew what they wanted.
Key Insight
The opportunity was bigger than modernizing individual screens: the booking experience needed a clearer, more scalable interaction model for customers who already knew what they wanted.
Key Insight
Frequent travelers don't need another booking journey. They need the product to remember the journey they've already chosen.
Key Insight
Frequent travelers don't need another booking journey. They need the product to remember the journey they've already chosen.
Transforming a legacy booking experience into a scalable, mobile-first, conversion-focused digital experience aligned with Air India's new brand identity.
Transforming a legacy booking experience into a scalable, mobile-first, conversion-focused digital experience aligned with Air India's new brand identity.
From legacy workflow to
mobile-first digital experience
From legacy workflow to
mobile-first digital experience
From legacy workflow to
mobile-first digital experience
The transformation focused on simplifying the core journey, improving hierarchy and interaction clarity, and creating a consistent experience that could scale across devices and future product capabilities.
Simplify — Reduce unnecessary steps and decision points in high-frequency tasks.
Prioritize — Bring the most relevant information and actions forward.
Modernize — Create a contemporary interface aligned with Air India's new digital identity.
Scale — Use reusable patterns so improvements could extend beyond a single page or flow.
Optimize — Design and validate the experience around conversion and completion, not visual refresh alone.
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What We Built
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What We Built
Designingthesystem,notjusttheinterface
Designingthesystem,notjusttheinterface
Designingthesystem,notjusttheinterface
A legacy-platform transformation only creates lasting value when the new experience can be maintained and extended. I therefore treated consistency and reuse as product-design problems, not just visual guidelines.
A legacy-platform transformation only creates lasting value when the new experience can be maintained and extended. I therefore treated consistency and reuse as product-design problems, not just visual guidelines.
Feature Highlights
Reusable interaction patterns across booking journeys
Reusable interaction patterns across booking journeys
Consistent hierarchy and component behavior
Consistent hierarchy and component behavior
Scalable responsive patterns
Scalable responsive patterns
Design-system alignment across digital touchpoints
Design-system alignment across digital touchpoints
Governance of experience quality across teams
Governance of experience quality across teams
Preference memory for seats, meals, fare class, and payment
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Business Impact
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Business Impact
Theredesignedexperiencedeliveredmeasurableimprovementsinbookingefficiencyandcustomervalue,accordingtothesuppliedcase-studycontent.
Theredesignedexperiencedeliveredmeasurableimprovementsinbookingefficiencyandcustomervalue,accordingtothesuppliedcase-studycontent.
Theredesignedexperiencedeliveredmeasurableimprovementsinbookingefficiencyandcustomervalue,accordingtothesuppliedcase-studycontent.
⏱
Booking time reduced 90% (4 min → 25–30 sec)
⏱
Booking time reduced 90% (4 min → 25–30 sec)
📈
Repeat bookings increased 42%
📈
Repeat bookings increased 42%
💎
CLV increased 2.3×ease
💎
CLV increased 2.3×ease
💰
₹280 crore annual revenue potential
💰
₹280 crore annual revenue potential
Key Learnings
AI-powered experiences must be transparent and trust-driven. Speed alone is not enough-users must feel in control of automated decisions, especially in high-value purchases like airline tickets.
" Ez Booking positioned me as a driver of AI-led product innovation within Air India’s digital ecosystem and demonstrated my ability to design intelligent, scalable experiences for high-value customer segments"
Key Learnings
AI-powered experiences must be transparent and trust-driven. Speed alone is not enough-users must feel in control of automated decisions, especially in high-value purchases like airline tickets.
" Ez Booking positioned me as a driver of AI-led product innovation within Air India’s digital ecosystem and demonstrated my ability to design intelligent, scalable experiences for high-value customer segments"
Key Learnings
AI-powered experiences must be transparent and trust-driven. Speed alone is not enough-users must feel in control of automated decisions, especially in high-value purchases like airline tickets.
" Ez Booking positioned me as a driver of AI-led product innovation within Air India’s digital ecosystem and demonstrated my ability to design intelligent, scalable experiences for high-value customer segments"
