Myntra Business Analytics Interview Questions & Answers
Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Myntra hiring for Business Analytics roles
Myntra is an Indian fashion and lifestyle e-commerce platform and part of the Flipkart group. Its technology and analytics teams work on search, personalisation, size recommendations, pricing, supply chain and marketing. It hires for software engineers, SDETs, business analysts, data analysts and data scientists. Fashion-specific data such as sizing matters a lot.
For Business Analytics roles, this Myntra practice set focuses most on Case Studies and Guesstimates (7), Business Metrics and KPIs (6), SQL for Business Analysis (5), Excel for Business Analysts (5). It has 3 easy, 30 medium, 7 hard questions, so you can start easy and work up to the harder ones.
Company type
E-commerce & consumer tech
Headquarters
Bengaluru, India
Main India offices
Bengaluru
Myntra Business Analytics interview process
Online assessment (coding or SQL)
Technical or machine coding round
Problem solving or case round
Hiring manager round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
Solved for MyntraStart practicing
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A short requirement written as 'As a user, I want X so that Y', backed by acceptance criteria. Good stories follow INVEST: independent, negotiable, valuable, estimable, small and testable.
Events are circles that show something happening. A start event (thin border) triggers the process, such as a form submitted or a timer firing on the first of the month. An intermediate event (double border) happens during the process, such as waiting for a payment message or a 48-hour timer. An end event (thick border) marks where a path finishes and can carry a result such as a message, an error or termination of all paths.
07
Write an Excel formula for the NPV of a project with an initial investment today and five yearly cash inflows.
# B1 = discount rate (for example 12%)
# B2 = initial investment entered as a negative number
# B3:B7 = cash inflows for years 1 to 5
=NPV(B1, B3:B7) + B2
# NPV() assumes the first value comes at the end of year 1,
# so the year-0 investment is added outside the function.
08
A query using NOT IN to find customers without orders returns zero rows, although you know such customers exist. Why?
The subquery probably returns at least one NULL, for example SELECT customer_id FROM orders where some orders have a NULL customer_id. With NOT IN, comparing any value to NULL gives UNKNOWN, so no row passes the condition. Fix it by using NOT EXISTS with a correlated subquery, or a LEFT JOIN with WHERE o.customer_id IS NULL, or by adding WHERE customer_id IS NOT NULL inside the subquery. NOT EXISTS is the safest habit.
09
Describe a time your analysis found a cost-saving opportunity.
Situation: monthly cloud and software subscription costs had grown 35 percent in a year without anyone tracking why. Task: my manager asked me to review them. Action: I combined invoices with user login data in Excel and found 140 licences unused for over 90 days and two tools doing the same job. Result: we cancelled unused licences and consolidated tools, saving about 18 lakh rupees a year, and I set up a quarterly licence review report.
10
What is an issue tree and how does a hypothesis-driven approach work?
An issue tree breaks the main question into smaller, MECE sub-questions until each can be answered with data, such as 'why are profits down?' into revenue and cost branches. A hypothesis-driven approach starts with a likely answer, for example 'profit fell because delivery costs rose', and uses the tree to decide which data proves or disproves it first. It focuses effort and keeps the case structured and fast.
11
What is the difference between a Tableau extract and a live connection?
A live connection queries the source database every time the view changes, so data is current but speed depends on the database. An extract (.hyper file) is a compressed snapshot stored by Tableau that is fast to query and can be refreshed on a schedule, but it is only as fresh as the last refresh. Extracts suit large, slow or remote sources; live suits fast warehouses and real-time needs.
12
Write a SQL query for a signup to purchase funnel from an events table.
WITH steps AS (
SELECT user_id,
MAX(CASE WHEN event = 'signup' THEN 1 ELSE 0 END) AS s1,
MAX(CASE WHEN event = 'add_to_cart' THEN 1 ELSE 0 END) AS s2,
MAX(CASE WHEN event = 'purchase' THEN 1 ELSE 0 END) AS s3
FROM events
WHERE event_date >= '2026-10-01'
GROUP BY user_id
)
SELECT SUM(s1) AS signups,
SUM(s1 * s2) AS carts,
SUM(s1 * s2 * s3) AS purchases,
ROUND(100.0 * SUM(s1 * s2 * s3) / NULLIF(SUM(s1), 0), 2) AS conv_pct
FROM steps;
13
What is the profit equation and how do you use it in cases?
=FILTER(Orders[[OrderID]:[Amount]],
(Orders[Region]="North") * (Orders[Amount]>50000),
"No matching orders")
# Multiplying the two conditions acts as AND.
# Use + instead of * for OR logic.
# Wrap with SORT(..., 3, -1) to sort by the third column descending.
A balanced scorecard is a strategic performance framework that tracks objectives and KPIs across four perspectives: financial (revenue growth, margin), customer (NPS, retention), internal processes (cycle time, defect rate) and learning and growth (training hours, employee engagement). The idea is that financial results are lagging, so leaders also need leading measures of what drives future performance. A strategy map links the objectives with cause-and-effect arrows from people to processes to customers to financial outcomes.
Start from the test cases and list the data each needs: customer types, product variants, edge values and historical records. Decide whether to use masked copies of production data, synthetic data or both, because real personal data must be anonymised under data protection rules such as the DPDP Act. Prepare data for negative and boundary cases, keep a refresh plan for repeated cycles, and assign owners. Poor test data is one of the most common causes of blocked UAT days.
17
Managers want to click a region on a summary report page and jump to a detail page for only that region. How do you build it in Power BI?
Use drill-through. Create a detail page, add the Region field to the page's drill-through filter well, and design visuals for orders, products and trends. Power BI adds a back button automatically. On the summary page, users right-click a region and choose Drill through. Keep all filters on so date selections carry over. For guided navigation, you can also add buttons with bookmarks, but drill-through is the cleanest way to pass the selected region.
The cash conversion cycle measures how many days cash is tied up in operations. It equals days inventory outstanding plus days sales outstanding minus days payables outstanding. Example: inventory sits 40 days, customers pay in 30 days and suppliers are paid in 45 days, so the cycle is 40 + 30 - 45 = 25 days. A shorter cycle means less working capital is needed. Some marketplaces have a negative cycle because they collect from customers before paying sellers.
-- late = delivered after the promised date
SELECT
city,
COUNT(*) AS total_orders,
SUM(CASE WHEN delivered_at > promised_at THEN 1 ELSE 0 END) AS late_orders,
ROUND(100.0 * SUM(CASE WHEN delivered_at > promised_at THEN 1 ELSE 0 END)
/ COUNT(*), 2) AS late_pct
FROM orders
WHERE status = 'DELIVERED'
GROUP BY city
ORDER BY late_pct DESC;
21
What is an index in a database and when can it hurt performance?
An index is a sorted lookup structure on one or more columns that lets the database find rows without scanning the whole table, much like a book index. It speeds up WHERE filters, joins and ORDER BY on those columns. It hurts when there are too many indexes, because every insert and update must maintain them, and it may not help on low-selectivity columns or when functions are applied to the indexed column.
22
A bank's mobile app logins increased, but digital transactions fell. What could explain this?
Users are coming but not completing transactions, so look at the gap. Possible causes: a release that broke a payment flow, new security steps like extra OTPs adding friction, logins driven by balance checks or offers, or transactions shifting to another channel. Compare the funnel from login to transaction by app version and device, check failure and error rates, and review support complaints before recommending fixes.
23
An A/B test shows a 5 percent higher conversion rate, but revenue per user is lower. Should you ship it?
Not automatically. Find out why: the variant may push cheaper products, bigger discounts or smaller orders, so more people buy but each spends less. Check average order value, margin and long-term metrics like repeat purchase. Decide based on the metric tied to the business goal, usually revenue or contribution per user, which should have been the primary metric or a guardrail. Consider iterating to keep the conversion gain without lowering order value.
24
The totals in your Excel report differ from the finance system by a few rupees. What could cause this?
Usually rounding. Excel may display rounded values while summing the full-precision numbers, or line items were rounded individually in the source system and the total was computed differently. Check whether finance rounds each invoice line before summing, and apply ROUND at the same level in Excel. Other causes include floating-point artifacts, values stored as text being skipped by SUM, or hidden filtered rows. Agree and document one rounding rule with finance.
25
Why do Agile teams estimate in story points rather than hours?
Story points measure relative effort, complexity and uncertainty compared with a reference story, using a scale like 1, 2, 3, 5, 8. People are better at comparing sizes than predicting exact hours, and points do not depend on who does the work. Over a few sprints the team's velocity, points completed per sprint, makes forecasting reliable. Points should never be used to compare productivity across teams.
26
How would you improve a company's low app conversion rate?
Go back to the requirement and acceptance criteria. If the system matches the agreed requirement, the developer is right, and the business need is a change request. If the requirement is unclear or the design misread it, it is a defect, and the requirement wording should be fixed. Discuss it in triage with both parties, using examples. Either way, close the loop with the tester so they understand the outcome and keep trusting the process.
29
How do you handle NULL values when calculating averages?
Confirm the impact and reproduce it quickly. Work with development to estimate a fix and its regression effort. Then present options to the business owner with risks: fix and do targeted retesting before go-live, go live with a temporary workaround or manual process, go live with the affected feature switched off, or delay. The decision belongs to the business, documented at the go or no-go meeting. Never hide a critical defect to protect a date.
31
Tell me about a time you solved an ambiguous problem with limited data.
Situation: my manager asked why customer complaints were rising, but complaints were stored as free text with no categories. Task: give an answer within a week. Action: I sampled 300 complaints, created categories, tagged them manually and used keyword rules in Excel to classify the rest, then validated with the support lead. Result: late refunds were 40 percent of complaints, the refund process was fixed, and categorised tagging was added to the support tool.
32
A KPI on your dashboard dropped 40 percent overnight. What are your first steps?
Assume a data problem until proven otherwise, because real businesses rarely move 40 percent in a day. Check whether the refresh completed, whether source row counts look normal, and whether any tracking, pipeline or definition changed. Compare with a raw source query and a related metric, such as orders versus payments. If the data is fine, segment by channel, region and platform to locate the drop, then alert the owners quickly.
33
What is Customer Acquisition Cost (CAC) and what is CAC payback period?
CAC is total sales and marketing spend in a period divided by new customers acquired in that period. If you spend 10 lakh and gain 2,000 customers, CAC is 500 rupees. CAC payback period is how many months of gross profit from a customer it takes to recover that CAC. A shorter payback means the business can reinvest faster; many subscription businesses aim for under 12 months.
34
Guesstimate: how many cups of tea are sold in Delhi per day?
Population about 20 million, adult tea drinkers about 50%, cups bought outside per person around 1 on average. This gives roughly 10 million cups, then adjust for offices and stalls.
35
What does the LTV to CAC ratio tell you and what is a healthy value?
LTV to CAC compares the lifetime gross profit from a customer with the cost of acquiring them. A ratio around 3 to 1 is commonly treated as healthy. Below 1 means you lose money on every customer. Far above 5 may mean you are underinvesting in growth. Always compute LTV on gross margin, not revenue, and check it by channel, because blended averages hide loss-making channels.
36
How would you forecast next quarter's sales in Excel?
Add a helper column for each customer's first order month using MINIFS on customer ID, and another for the order month. Compute the month index as the difference in months between them. Then build a PivotTable or COUNTIFS grid with cohort month as rows, month index as columns and distinct customers as values. Divide each cell by the month-zero count to get retention percentages and add a colour scale to show decay.
38
What is a North Star metric and how do you choose one?
A North Star metric is the single measure that best captures the value customers get from the product and predicts long-term revenue. Examples are weekly active learners for an ed-tech app or orders delivered on time for a delivery business. Choose one that reflects customer value, can be influenced by teams and leads revenue. Support it with input metrics such as activation, frequency and retention that teams can work on directly.
39
In UAT cycle 2, a feature that passed in cycle 1 is now broken after a defect fix. What does this tell you and what should change?
It is a regression: the fix for one defect broke existing functionality, which usually means changes were not impact-analysed and there is no regression suite. Log it as a new high-priority defect linked to the fix. Agree with the team that every UAT build comes with release notes listing the changes, and that QA runs an automated or core manual regression pack before handing the build to business testers. Also add the broken flow to the UAT regression checklist.
40
How do you calculate cycle time, touch time and process efficiency? Give an example.
Cycle time (lead time) is the total elapsed time from the start to the end of a case. Touch time is the time someone actually works on it. Process cycle efficiency is touch time divided by cycle time. Example: a refund takes 5 working days (40 working hours) end to end, but the agents spend only 2 hours in total working on it. Efficiency is 2 / 40 = 5 percent, so 95 percent of the time is waiting, and queues are the main target.
Tips to crack the Myntra Business Analytics interview
Prepare cases on fashion e-commerce issues like returns due to size, discount depth or End of Reason Sale planning.
Practise SQL and Python for analytics roles, including cohort and funnel analysis on order data.
Read about Myntra's use of data science in size recommendations and visual search.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; Myntra interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Myntra Business Analytics interview?
Candidates usually go through 4 stages: Online assessment (coding or SQL); Technical or machine coding round; Problem solving or case round; Hiring manager round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the Myntra Business Analytics interview?
This practice set leans on Case Studies and Guesstimates (7), Business Metrics and KPIs (6), SQL for Business Analysis (5), Excel for Business Analysts (5). Revise those first, then practise explaining one or two of your own projects end to end, because most Myntra interviewers ask you to walk through real work.
Are these the exact questions asked at Myntra?
No. These are curated practice questions that match the skills and difficulty usually tested in e-commerce & consumer tech interviews like Myntra's. They are not a leaked or verified list of past questions.
Where does Myntra hire Business Analytics professionals in India?
Myntra has large teams in Bengaluru. Openings and locations change often, so check the Myntra careers page and filter by city and experience.
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