Delhivery Business Analytics Interview Questions & Answers
Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Delhivery hiring for Business Analytics roles
Delhivery is an Indian logistics and supply chain company that provides parcel delivery, freight, warehousing and fulfilment services for e-commerce and enterprise clients. It runs a large network of hubs and uses technology for route planning, tracking and automation. It hires software engineers, data scientists, data analysts and operations professionals.
For Business Analytics roles, this Delhivery practice set focuses most on Case Studies and Guesstimates (7), Business Metrics and KPIs (5), Power BI and Tableau (4), Excel for Business Analysts (4). It has 29 medium, 11 hard questions, so you can start easy and work up to the harder ones.
Company type
E-commerce & consumer tech
Headquarters
Gurugram, India
Main India offices
Gurugram, Bengaluru
Delhivery Business Analytics interview process
Online coding or analytics assessment
Technical round 1
Technical round 2 (design or case)
Hiring manager round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
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01
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.
02
A business head wants 25 charts on one dashboard page. How do you respond?
Ask what decisions they make weekly and which three to five KPIs drive them. Propose a summary page with those KPIs, trends and one breakdown, then drill-through or separate pages for detail. Show a quick mock-up of both versions so they see the clutter and the load time. Use bookmarks or a field parameter to let them switch views without adding charts. Agree on the layout before building.
A condition on the right table was probably placed in the WHERE clause, for example WHERE o.order_date >= '2026-01-01'. For customers with no orders, o.order_date is NULL, so WHERE removes them and the query behaves like an INNER JOIN. Move the condition into the ON clause, as in LEFT JOIN orders o ON o.customer_id = c.id AND o.order_date >= '2026-01-01', or explicitly allow NULLs.
07
Finance and sales blame each other for wrong numbers in a monthly report. How do you resolve it as the analyst?
Stay neutral and move the discussion from blame to facts. Trace the number end to end: source system, extraction, transformation and report logic, and find exactly where the values diverge. Share the findings with both teams together, agree on the fix and on a single owner for the definition. Then add automated reconciliation checks and a data dictionary, so the process, not people, prevents the next issue.
ROI (return on investment) is the gain from a specific investment divided by its cost and is used to judge projects or campaigns. ROE (return on equity) is net profit divided by shareholders' equity and shows the return to owners; high debt can inflate it. ROCE (return on capital employed) is EBIT divided by equity plus long-term debt and shows how efficiently all long-term capital is used. ROCE is better for comparing companies with different debt levels.
09
Write a SQL query for Day-7 retention by weekly sign-up cohort.
WITH cohort AS (
SELECT user_id, signup_date,
DATE_TRUNC('week', signup_date) AS cohort_week
FROM users
),
ret AS (
SELECT DISTINCT c.user_id
FROM cohort c
JOIN events e ON e.user_id = c.user_id
AND e.event_date = c.signup_date + INTERVAL '7 day'
)
SELECT c.cohort_week, COUNT(*) AS users,
ROUND(100.0 * COUNT(r.user_id) / COUNT(*), 1) AS d7_retention_pct
FROM cohort c
LEFT JOIN ret r ON r.user_id = c.user_id
GROUP BY c.cohort_week
ORDER BY c.cohort_week;
10
After many sprints, project documentation is out of date and new team members are confused. What do you do?
Identify which documents are actually used: usually a product overview, process maps, business rules, data dictionary and integration details. Update those first rather than everything. Make documentation part of the Definition of Done, so a story is not complete until related docs are updated. Keep living documents in a shared wiki with owners and last-reviewed dates, and archive outdated files clearly. Test the result by having a new joiner use it during onboarding.
11
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.
12
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.
13
Your measure shows the same value on every row of a matrix. Why might that happen?
The filter from the row field is not reaching the fact table. Usually there is no relationship between that dimension and the fact, the relationship is inactive, or it filters in the wrong direction. It can also happen when the measure uses ALL or REMOVEFILTERS on that column, or when the row field comes from the fact table of a different grain. Check the model view and test the measure with a simple SUM.
14
A lender is launching a new personal loan product. What KPIs would you set up?
Cover the full funnel and risk. Acquisition: applications, approval rate, cost per disbursed loan and time to disbursal. Value: disbursed amount, average ticket size and net interest margin. Risk: delinquency rates at 30 and 90 days past due by cohort, and early default rate. Customer: drop-off by application step, complaint rate and repeat borrowing. Track risk by monthly disbursal cohort, because defaults show up months later.
15
How do you handle NULL values when calculating averages?
Every diagram has clear start and end events and a title with version and owner. Activities use verb-noun names such as Approve invoice. Each gateway is labelled with a question and its outgoing flows with answers. Splits and joins use matching gateway types. Message flows only connect separate pools. No dangling or crossing arrows where avoidable. The happy path reads left to right. Exceptions are handled, and complex rules are referenced to decision tables rather than drawn as gateways.
17
Describe a BPMN model for a purchase order process where credit check and stock check happen at the same time.
Start event: purchase order received. Task: validate order details. A parallel gateway then splits into two paths: Finance lane runs Check customer credit, Warehouse lane runs Check stock. A second parallel gateway joins them, waiting for both to complete. An exclusive gateway then decides: credit OK and stock available goes to Confirm order and Schedule dispatch; otherwise go to Notify customer with reason. Using a parallel join here is correct because both results are always needed.
18
Revenue grew 20 percent this quarter but the number of active customers stayed flat. How do you interpret it?
Growth came from more value per customer, not more customers. Break revenue into customers times orders per customer times average order value to see which moved. It could be price increases, larger baskets, a shift to premium products or a few large accounts. Then check risks: is new customer acquisition stalling, is churn being masked, and is growth concentrated in a small segment that could leave?
19
Write a SQL query that shows revenue, cost and gross margin percent by product category.
SELECT
p.category,
SUM(oi.quantity * oi.unit_price) AS revenue,
SUM(oi.quantity * p.unit_cost) AS cost,
ROUND(100.0 * (SUM(oi.quantity * oi.unit_price)
- SUM(oi.quantity * p.unit_cost))
/ NULLIF(SUM(oi.quantity * oi.unit_price), 0), 2) AS gross_margin_pct
FROM order_items oi
JOIN products p ON p.product_id = oi.product_id
GROUP BY p.category
ORDER BY gross_margin_pct DESC;
20
Guesstimate: how many weddings take place in India in a year?
Assume a population of about 144 crore and an average life expectancy of about 70 years, so roughly 2 crore people reach a typical marriage age each year. If about 95 percent of them marry at some point, that is around 1.9 crore people, or about 95 lakh weddings, since each wedding involves two people. A reasonable estimate is around 1 crore weddings per year, concentrated in the winter wedding season.
21
Daily active users dropped 10 percent week over week. How do you investigate?
Rule out data issues first: tracking changes, app release bugs, pipeline delays or bot filters. Check whether the drop is seasonal by comparing with the same week last year or a festival calendar. Then segment by platform, app version, country or city, acquisition channel and new versus returning users to locate it. Look at the funnel for the core action. Connect findings to releases, outages or marketing changes, then recommend fixes.
WITH m AS (SELECT month, SUM(amount) AS rev FROM orders GROUP BY month)
SELECT month, rev,
ROUND(100.0 * (rev - LAG(rev) OVER (ORDER BY month))
/ LAG(rev) OVER (ORDER BY month), 1) AS mom_pct
FROM m;
23
What is AS-IS and TO-BE process modelling, and where does BPMN fit in?
AS-IS modelling documents how a process works today, including pain points, delays and handoffs. TO-BE modelling shows the improved future process after changes or a new system. Comparing the two reveals the gaps and requirements. BPMN, Business Process Model and Notation, is the standard notation, using events, tasks, gateways for decisions and swimlanes for roles, so both business and IT read the diagrams the same way.
24
Tell me about a time your analysis changed a product decision.
Situation: the team planned to add more filters to the search page to fix low conversion. Task: I was asked to size the opportunity. Action: funnel analysis showed most drop-off happened after users opened a product page with no delivery date shown, not in search. I shared the data with session recordings. Result: the team prioritised showing delivery dates on the product page, conversion rose about 8 percent, and the filter work was deprioritised.
25
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.
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.
27
What is the profit equation and how do you use it in cases?
Import copies data into the compressed in-memory model, giving the fastest visuals and full DAX, but data is only as fresh as the last refresh and size is limited. DirectQuery sends queries to the source at view time, so data is near real time but visuals are slower and some DAX is restricted. Live Connection points to an existing published semantic model or Analysis Services model without its own model. Composite models mix Import and DirectQuery.
29
Stakeholders give conflicting requirements. What do you do?
Clarify the goal behind each request, map them to business objectives, prioritise with MoSCoW, run a joint session, then document the decision and get sign-off.
30
What is the difference between bookings, billings and revenue?
Bookings are the value of contracts signed in a period, showing future commitment. Billings are the amounts invoiced to customers in the period. Revenue is what is earned and recognised under accounting rules as the service is delivered. Example: a 3-year contract worth 36 lakh signed in April is 36 lakh in bookings, 12 lakh in billings if invoiced annually, and only 1 lakh in revenue for April. Confusing them is common when reporting sales performance.
31
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.
32
Write a SQL query to calculate monthly customer churn rate for a subscription business.
WITH monthly AS (
SELECT DISTINCT customer_id,
DATE_TRUNC('month', billing_date) AS month
FROM subscriptions_billed
)
SELECT
prev.month AS month,
COUNT(prev.customer_id) AS customers_at_start,
COUNT(prev.customer_id) - COUNT(nxt.customer_id) AS churned,
ROUND(100.0 * (COUNT(prev.customer_id) - COUNT(nxt.customer_id))
/ COUNT(prev.customer_id), 2) AS churn_pct
FROM monthly prev
LEFT JOIN monthly nxt
ON nxt.customer_id = prev.customer_id
AND nxt.month = prev.month + INTERVAL '1 month'
GROUP BY prev.month
ORDER BY prev.month;
33
Finance asks you to build a monthly cohort retention table in Excel from raw order data. How do you approach it?
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.
34
Write a SQL query to find requirements that have no linked UAT test case.
SELECT r.req_id, r.title, r.priority
FROM requirements r
LEFT JOIN test_case_links l ON l.req_id = r.req_id
WHERE l.req_id IS NULL
AND r.status = 'APPROVED'
ORDER BY r.priority;
-- Run this before UAT starts: every approved requirement
-- should trace to at least one test case.
35
Describe a time you explained a complex technical topic to a non-technical audience.
Situation: operations managers did not trust a new demand forecast that drove staffing. Task: explain it so they would use it. Action: I avoided model terms and showed how it used last year's same week, recent trend and festival calendar, with a chart of past forecasts against actuals. I compared the forecast range to a weather forecast. Result: managers started using it for rosters and gave feedback that improved it further.
36
A quick-commerce company wants to expand into Tier-2 cities. What would you analyse before recommending it?
Demand: population density, smartphone and digital payment penetration, average basket size and how often people buy groceries. Supply: dark store rent, rider availability and local sourcing. Unit economics: orders per store per day needed to break even, given lower average order values. Competition: local kirana delivery and other apps. Then propose a pilot in two or three cities with clear success metrics such as orders per day, contribution margin per order and repeat rate before scaling.
Check data accuracy, then segment by city, restaurant, time and user type; look at supply, delivery time, pricing, competitors and seasonality before proposing fixes.
39
A report query on a 200 million row table takes 15 minutes. How do you optimise it?
Read the execution plan to find full scans and expensive joins. Filter early on partitioned or indexed columns such as date, select only needed columns instead of SELECT *, and avoid functions on filter columns. Pre-aggregate in a CTE before joining, replace correlated subqueries with joins or window functions, and check join keys have matching types. For repeated use, build a summary table or materialised view refreshed daily.
Value chain analysis breaks a business into the activities that create value: primary activities such as inbound logistics, operations, outbound logistics, marketing and sales, and service, plus support activities like procurement, technology, HR and infrastructure. For each activity you look at cost and differentiation. In cases it helps locate where costs are rising or where a competitive advantage can be built, for example in last-mile delivery.
Tips to crack the Delhivery Business Analytics interview
Learn logistics basics such as first mile, last mile, hub operations and shipment tracking to discuss the domain.
Practise optimisation-style problems and graph algorithms, which connect well to routing and network planning work.
For analyst roles, revise SQL and Excel, and prepare to analyse delivery delays or cost per shipment in a case.
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; Delhivery interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Delhivery Business Analytics interview?
Candidates usually go through 4 stages: Online coding or analytics assessment; Technical round 1; Technical round 2 (design or case); 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 Delhivery Business Analytics interview?
This practice set leans on Case Studies and Guesstimates (7), Business Metrics and KPIs (5), Power BI and Tableau (4), Excel for Business Analysts (4). Revise those first, then practise explaining one or two of your own projects end to end, because most Delhivery interviewers ask you to walk through real work.
Are these the exact questions asked at Delhivery?
No. These are curated practice questions that match the skills and difficulty usually tested in e-commerce & consumer tech interviews like Delhivery's. They are not a leaked or verified list of past questions.
Where does Delhivery hire Business Analytics professionals in India?
Delhivery has large teams in Gurugram, Bengaluru. Openings and locations change often, so check the Delhivery careers page and filter by city and experience.
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