ixigo Revenue Analyst Interview: Rounds, Questions and Preparation

What the job involves

A Revenue Analyst in travel, hospitality, and food service helps a company like ixigo maximise income from every flight, train, hotel, or meal booking. Day to day you track booking curves, competitor prices, and demand patterns, then recommend price or inventory changes to hit revenue targets. You also build dashboards and reports that show how promotions, seasonality, and cancellations affect the bottom line.

Role and Technical Knowledge

1. 1

   What is the difference between ADR and RevPAR, and why would a hotel or travel platform track both?

   ADR is average daily rate (room revenue / rooms sold). RevPAR is revenue per available room (room revenue / total rooms available). RevPAR captures both price and occupancy, so it shows if discounting is actually growing total revenue.

2. 2

   How would you calculate the load factor for a train or flight, and what does a low load factor tell you?

   Load factor = passengers carried / seats available. A low load factor means unsold capacity, which may signal overcapacity, wrong pricing, or weak demand on that route. You would then check competitor prices and booking curves.

3. 3

   Explain booking window and why it matters for a travel company like ixigo.

   Booking window is the time between booking and travel date. A short window means late demand and higher risk of unsold inventory. A long window helps forecast revenue but may lock in lower prices. You would segment by route, season, and customer type.

4. 4

   What is net revenue versus gross booking value in a travel or food delivery context?

   Gross booking value is the total amount paid by the customer. Net revenue is what the company keeps after cancellations, refunds, payment gateway fees, and supplier costs. Revenue analysts focus on net revenue because it reflects actual earnings.

Practical Scenarios and Case Questions

1. 5

   A route is showing a 15 percent drop in bookings compared to last month. How would you investigate the cause?

   Start by checking seasonality, competitor price changes, and any recent fare hikes. Then look at booking window shifts, cancellation rates, and app or website traffic. Segment by customer type and device. End with a clear recommendation: price change, promotion, or inventory adjustment.

2. 6

   You have a hotel partner offering a 20 percent discount for weekend stays. How would you measure if it is working?

   Compare weekend RevPAR and net revenue before and after the discount, against a control group of similar hotels. Check if the discount brought new customers or just shifted existing bookings. Also watch cancellation rates and average length of stay.

3. 7

   A food delivery platform wants to increase revenue from late night orders. What data would you pull and what would you recommend?

   Pull order volume by hour, average order value, delivery cost, and restaurant availability. Look at peak vs off peak pricing, delivery fees, and promotions. Recommend targeted discounts or bundled offers only if the incremental margin is positive.

4. 8

   How would you build a simple dashboard in Excel or Power BI to track daily revenue for a travel platform?

   Include daily net revenue, bookings, average booking value, cancellation rate, and top routes or cities. Use a date filter and a comparison to last week and last year. Keep it to one screen with clear labels so a manager can act quickly.

Behavioural and Situational Questions

1. 9

   Tell me about a time you used data to solve a problem in a college project or internship.

   Use STAR format: situation, task, action, result. Focus on how you cleaned data, found a pattern, and what changed because of your analysis. Quantify the result if possible.

2. 10

   You find that a pricing change you recommended led to lower revenue. How do you handle it?

   Acknowledge the mistake quickly, show the data, and propose a reversal or test. Explain what you learned about demand elasticity or competitor response. Emphasise that you document the learning for the team.

3. 11

   Describe a time you had to explain a complex number to someone who was not from a technical background.

   Show that you avoided jargon, used a simple chart or analogy, and checked for understanding. The goal is to show you can influence decisions without confusing the audience.

4. 12

   How do you prioritise when you have multiple requests from sales, marketing, and product teams?

   Mention impact on revenue, urgency, and effort. Give an example of saying no or negotiating a deadline. Show you communicate trade offs clearly to stakeholders.

HR and Motivation Questions

1. 13

   Why do you want to work as a Revenue Analyst in the travel and hospitality sector?

   Connect your interest in data to the dynamic nature of travel demand. Mention seasonality, competition, and the visible impact of your work on bookings and revenue. Avoid generic answers about loving travel.

2. 14

   What do you know about ixigo as a company and how it makes money?

   Show you understand it is a travel booking platform for trains, flights, buses, and hotels. Revenue comes from commissions, advertising, and convenience fees. Mention its focus on tier 2 and tier 3 cities and mobile first users.

3. 15

   Where do you see yourself in three years in this role?

   Show a path from analyst to senior analyst or revenue manager. Mention deepening skills in forecasting, pricing, and SQL or Python. Keep it realistic and tied to the company's growth.

4. 16

   Are you comfortable working with large datasets and tight deadlines during peak travel seasons?

   Give a specific example of handling a high pressure deadline in college or an internship. Mention your process for checking work quickly and asking for help when needed. Show enthusiasm for the fast pace of travel.