Improving Bookings
For Better Travel Agent Experience

“Anant Travels” is an online travel platform that allows users to effortlessly search, compare and book flights, hotels & visas.

Role

Research, Information Architecture, Visual Design, Prototyping

Status

Development in progress

Tools

Figma, Whimsical

Introduction

My Bookings allows travel agents to manage, modify and service bookings. “Anant Travels” caters to 3 different travel segments, this case study focuses solely on B2B.
How might we increase travel agent productivity and help better service bookings.

B2B

4600+ Travel Agents / Affiliates

B2E

650+ Registered Companies

B2C

4000+ Registered Retail Customers

Understanding Complexity

A travel agent has 3 stages in his workflow, making, managing and servicing bookings. We’ll focus on managing and servicing bookings only.

OLD FLOWS

Managing and servicing phases are broadly divided in two flows. Managing consists of a business use case where travel agent has to follow up with multiple bookings, whereas servicing flow requires travel agent to identify and modify a specific booking.

Travel agents value communication with clients, they want to organize and identify bookings promptly. Deriving insights from my research, which included usability testing and interviews with 5 travel agents. I discovered the following complexities.

COMPLEXITIES

on avg

4.5 min

per service / query

on avg

8 min

per hotel modification

Low discoverability of bookings due to high volume

Due to unavailability of filters it became tedious for travel agents to sift through bookings.

Difficulty in identifying specific bookings
Search experience was broken, search was only indexing traveler name and there was no other way of identifying a booking.
Exhaustive on call time to modify hotel booking
Modification to hotel bookings was handled offline by travel agents. This lead to long call times, resulting in a poor experience.

GOALS

Improve discoverability to identify bookings.
Reduce time taken to modify bookings.

Solutions

SOLVING COMPLEXITY 1

Low discoverability of bookings due to high volume

Designing Navigation & Viewing
The redesigned bookings drop-down is now categorized by booking and product type. This enables travel agents to sift through various product categories and observe different kinds of bookings. Options to sort by date and booking cost have been incorporated.

Before — Poor viewing and filtering experience

After — Simplifying booking organization with product filter

Designing Booking Cards To Display Crucial Data
Displayed data points to help travel agents view and act faster, reducing their grunt work and improving efficiency. Added product specific information like sectors for flights, check in-out dates for hotels and validity dates for visa along with booking cost for each.
Before — Poor Visuals & Incomplete Information

After — Informative & Visual.

SOLVING COMPLEXITY 2

Difficulty in identifying specific bookings
Designing Search & Filter
Older design had a search function that only indexed the name of the booking. Redesigned search now allows travel agents to search by PNR , the most common use case. It also allows search by traveler name, location, hotel and airline. Filtering bookings between a date-range is the most common use case that comes up for a travel agent, adding a date filter was vital for this reason.
Before — Broken search experience
After — Redesigned search and date filter

SOLVING COMPLEXITY 3

Exhaustive on call time to modify hotel booking

Designing Top Drawer & Carousel
Earlier, this room change request was processed offline via our customer support, but it’s presently shifting to a complete online procedure. When a customer submits this request, it facilitates the travel agent to promptly explore room alternatives.
Offline to Online — Room change flow
Impact & Learnings

Metrics

on avg

30% time reduction

per service / query

on avg

40% time reduction

per hotel modification

Set scope upfront to reduce ambiguity in project, initially even B2C & B2E was a consideration which was dropped after the first month.

Customer Support requests are a goldmine for qualitative data and sometimes quantitative too.
Designing using systems will go a long way. Categorizing type of booking, product and modifications to booking allowed to better segregate flows.