Guesstimate questions (with answers)

Clarify and choose an approach. What you say: "I'll estimate all UPI transactions on an average day, both person-to-person and person-to-merchant. I'll go top-down from adults who use UPI, then check from the merchant side."

Structure: adults × share who use UPI × average transactions per user per day.

Key assumptions:

• Adults: about 100 crore, roughly two-thirds of India's 148 crore people.

Explanation: India’s population is about 148 crore. Roughly two-thirds of people are adults, because India has a young population with a large share under 18. 148 x two-thirds is about 99, which rounds to 100, an easy number to multiply.

• People who use UPI regularly: 50%, or 50 crore. Smartphone ownership is high, but many older and rural adults still rely on cash.

Explanation: This is the most judgement-heavy number. The reasoning: most urban adults with a smartphone use UPI, but large groups don’t use it regularly, such as older adults, many rural adults, and people without their own smartphone or bank-linked UPI account.

• Heavy users, 30% of users: Minimum of three payments a day. Urban professionals paying for food, travel and small purchases.
• Regular users, 40%: One payment a day.
• Light users, 30%: about two a week, or 0.3 a day.

Explanation:

Calculation:

• Average per user per day: (30% × 3) + (40% × 1) + (30% × 0.3) = 0.9 + 0.4 + 0.09 = about 1.4.
• Daily transactions: 50 crore × 1.4 = about 70 crore.

Sanity check from the merchant side. What you say: "Suppose about 4 crore shops, vendors, and businesses accept UPI, and each takes 12 payments a day. That's about 48 crore merchant payments. If person-to-person transfers are roughly a third of all volume, the total is about 72 crore. That's close to my first estimate."

Answer: about 70 crore transactions a day, likely between 50 and 90 crore. The most sensitive assumption is how often heavy users pay.

Reality check. NPCI data shows UPI processed 24.07 billion transactions in September 2026, an average of about 80 crore a day. The estimate above lands about 12% low. The likely gap: heavy users make more small payments, such as tea, auto rides and parking, than 3 a day suggests.

Follow-up interviewers often add: How would the number change during the festive season? How much of this is person-to-person versus merchant payments? What would happen to volume if merchants were charged a fee on some payments?

Clarify and choose an approach. What you say: "I'll estimate new electric scooters and motorcycles sold to customers in a year, excluding e-rickshaws. I'll first estimate all two-wheeler sales, then apply an EV share."

Structure: (replacement purchases + first-time purchases) × EV share.

Key assumptions:

• Households: about 33 crore (148 crore people ÷ about 4.4 per household).
• Households that own a two-wheeler: about half, or 16.5 crore. Two-wheelers are the default family vehicle across most of India.
• Replacement cycle: about 10 years, so about 1.65 crore replacements a year.
• First-time buyers: about 1.5% of all households a year, or about 50 lakh.
• EV share of new sales: about 6%. EVs are growing fast in cities, but most buyers outside metros still choose petrol.

Calculation:

• Total two-wheeler sales: 1.65 crore + 0.5 crore = about 2.1 crore a year.
• Electric two-wheelers: 2.1 crore × 6% = about 13 lakh.

Sanity check. What you say: "13 lakh a year is about 3,500 a day across the country. Spread across a few hundred cities and towns with dealers, that's a handful per showroom per day, which feels plausible."

Answer: about 13 lakh a year, likely between 8 and 18 lakh. The EV share is the swing factor: at 3% the answer halves, at 9% it rises by half.

Reality check. Vahan registration data shows about 14 lakh electric two-wheelers were sold in FY26, out of about 2.14 crore two-wheelers in total, an EV share of about 6.5%. The estimate is within 10%. Treat that as a pleasant surprise, not the goal. A sound structure that lands at 9 lakh would score just as well.

Follow-up interviewers often add: Which cities would you expect to have the highest EV share, and why? How would a cut in subsidies change your answer? What share of total two-wheeler sales would make charging infrastructure the bottleneck?

Clarify and choose an approach. What you say: "I'll count cups sold outside the home, at stalls, darshinis, cafés and office vendors, and exclude tea made at home. I'll go top-down from adults, then check from the number of places selling tea."

Structure: adults × share who buy tea outside on a typical day × cups per buyer.

Key assumptions:

• Metro population: about 1.4 crore.
• Adults: about 75%, or roughly 1 crore.
• Share who buy tea outside on a given day: 30%, or 30 lakh. Lower than in some northern cities, because many people here choose filter coffee instead.
• Cups per buyer: about 1.5, since office workers often have one in the morning and one in the afternoon.

Calculation: 30 lakh × 1.5 = about 45 lakh cups a day.

Sanity check from the supply side. What you say: "Suppose there are about 30,000 places selling tea, including small stalls, darshinis, cafés and office vendors. If each sells about 150 cups a day, that's 45 lakh. Both routes agree."

Answer: about 45 lakh cups a day, likely between 30 and 70 lakh. So what: a tea chain with 100 outlets each selling 400 cups a day would still serve under 1% of the city's cups.

Follow-up interviewers often add: How would the answer differ in Delhi or Kolkata? How much would the number change during monsoon? What is the total daily spend on chai in the city?

Clarify and choose an approach. What you say: "I'll count individual riders who complete at least one food delivery on an average weekday, across all apps. A rider who works for two apps counts once. I'll estimate daily orders first, then divide by orders per rider, and check against dinner peak capacity."

Structure: daily orders ÷ orders per rider per day.

Key assumptions:

• Metro population: about 1.1 crore.
• Share aged 18 to 60: 60%, or 66 lakh.
• Share who order food online: 40%, or about 26 lakh.
• Orders per user: about 1 a week on average.
• Orders per rider: about 15 a day, at one to two orders an hour on a long shift.

Calculation:

• Weekly orders: 26 lakh × 1 = 26 lakh. Daily: 26 lakh ÷ 7 = about 3.7 lakh.
• Riders: 3.7 lakh ÷ 15 = about 25,000.

Sanity check from peak demand. What you say: "Fleets are sized for the dinner peak. If 35% of orders fall in a three-hour dinner window, that's about 1.3 lakh orders. A rider can do about 2 an hour, so 6 in that window. 1.3 lakh ÷ 6 is about 22,000 riders needed at peak. That's close to 25,000, which makes sense since not every rider works the peak."

Answer: about 25,000 active riders on a weekday, likely between 15,000 and 35,000.

Follow-up interviewers often add: How would rain change demand and supply differently? How many riders would a new entrant need to offer 30-minute delivery across the city? What happens to your answer if half of riders work for two apps?

Clarify and choose an approach. What you say: "I'll take one mature dark store in a dense area of a large city, open about 16 hours a day. I'll estimate demand from households in its delivery radius, then check it against how many orders the store can physically pick."

Structure: households in radius × share using quick commerce × orders per month × this store's share ÷ 30.

Key assumptions:

• Delivery radius: about 2.5 km, an area of roughly 20 sq km.
• Population density: about 20,000 people per sq km in a dense urban area, so 4 lakh people, or about 1 lakh households.
• Households using quick commerce at least monthly: 30%, or 30,000.
• Orders per using household: about 6 a month.
• This store's share, given competing apps nearby: about 30%.

Calculation:

• Monthly orders in the area: 30,000 × 6 = 1.8 lakh.
• This store: 1.8 lakh × 30% = 54,000 a month, or about 1,800 a day.

Sanity check from picking capacity. What you say: "Suppose 15 pickers are on the floor at any time, and each picks an order in about 3 minutes, so 20 an hour. Over 16 hours at about 40% average utilisation, with peaks and quiet spells, that's 15 × 20 × 16 × 40%, or about 1,900 orders. Demand and capacity line up."

Answer: about 1,800 to 2,000 orders a day, likely between 1,000 and 3,000.

Follow-ups interviewers often add: What limits the store first at peak hours, pickers or riders? How would the number change if the radius shrank to 1.5 km? At what daily volume would you open a second store nearby?

Clarify and choose an approach. What you say: "I'll count scheduled passenger and cargo departures from Indira Gandhi International Airport on a normal day, not arrivals. I'll start with how many departures the airport can handle per hour, then check against passenger numbers."

Structure: (busy hours × departures per busy hour) + (night hours × departures per night hour).

Key assumptions:

• Busy hours: about 18, from early morning to late evening.
• Departures per busy hour: about 35, roughly one every 100 seconds across multiple runways.
• Night hours: about 6, at around 10 departures an hour.

Calculation: (18 × 35) + (6 × 10) = 630 + 60 = about 700 departures.

Sanity check from passengers. What you say: "Suppose the airport handles about 2 lakh passengers a day, so about 1 lakh departing. If an average flight carries about 150 passengers, mixing narrow-body domestic flights with fuller wide-body international ones, that's about 670 departures. Close to 700."

Answer: about 700 departures a day, likely between 600 and 800.

Reality check. Delhi Airport handled its highest-ever single-day traffic on 20 February 2026, about 1,550 aircraft movements, with nearly 2.5 lakh passengers scheduled. Movements count arrivals and departures, so the record day had roughly 775 departures. A typical day sits below that record, which makes an estimate of about 700 reasonable.

Follow-up interviewers often add: How many more flights could the airport add before hitting capacity? How does fog in winter change the answer? How many airline staff are needed to run these departures?

Clarify and choose an approach. What you say: "I'll estimate fuel sales revenue for one busy pump on an urban highway, open 24 hours, excluding any shop or service income. I'll go bottom-up from vehicles served and average spend."

Structure: vehicles per day × average spend per vehicle.

Key assumptions:

• Dispensing points: 8.
• Capacity per point: about 20 vehicles an hour, at about 3 minutes per fill.
• Average utilisation over 24 hours: about 35%, busy by day and quiet at night.
• Vehicle mix and spend: two-wheelers 60% at about ₹200; cars 30% at about ₹1,500; trucks and buses 10% at about ₹5,000.

Calculation:

• Vehicles per day: 8 × 20 × 24 × 35% = about 1,300.
• Average spend: (60% × ₹200) + (30% × ₹1,500) + (10% × ₹5,000) = ₹120 + ₹450 + ₹500 = about ₹1,000.
• Daily revenue: 1,300 × ₹1,000 = about ₹13 lakh.

Sanity check in litres. What you say: "At roughly ₹100 a litre as a round average across petrol and diesel, ₹13 lakh is about 13,000 litres a day. That's in the range of one tanker delivery a day, which feels right for a busy highway pump."

Answer: about ₹13 lakh a day, likely between ₹8 and ₹20 lakh. So what: revenue is large, but if the dealer keeps only a few rupees per litre, gross margin is closer to ₹40,000 to ₹50,000 a day. Volume is everything in this business.

Follow-up interviewers often add: How much extra could a convenience store add? How would the answer change for a rural highway pump? How would a rise in EV adoption affect this pump over five years?

Clarify and choose an approach. What you say: "I'll take a 300-seat centre in a Bengaluru business district and include desk memberships, meeting rooms, day passes and small extras like food and parking. I'll build revenue by product line."

Structure: fixed seats + flexible memberships + meeting rooms and day passes + extras.

Key assumptions:

• Fixed seats and private cabins: 70% of seats, or 210, at 80% occupancy and about ₹12,000 a seat per month.
• Hot desks: 20% of seats, or 60. Sold at about 1.5 members per seat because not everyone comes in daily, with about 70 memberships sold at ₹7,000.
• Meeting rooms and day passes: the remaining 10% of space, earning about ₹3 lakh a month.
• Extras such as food and parking: about ₹1 lakh a month.

Calculation:

• Fixed seats: 210 × 80% × ₹12,000 = about ₹20 lakh.
• Hot desks: 70 × ₹7,000 = about ₹5 lakh.
• Meeting rooms, day passes and extras: about ₹4 lakh.
• Total: about ₹29 lakh a month; call it ₹30 lakh.

Sanity check against costs. What you say: "At about 60 sq ft per seat, the space is about 18,000 sq ft. At around ₹100 per sq ft a month in rent, that's ₹18 lakh, about 60% of revenue. Tight, but plausible for a business that takes a lease and resells desks."

Answer: about ₹30 lakh a month, likely between ₹20 and ₹40 lakh. So what: if fixed-seat occupancy fell from 80% to 60%, revenue would drop by about ₹5 lakh a month, wiping out most of the margin. Occupancy is the number to watch.

Follow-up interviewers often add: Should the operator shift space from hot desks to private cabins? What would change in a Tier 2 city? How long would it take to recover the fit-out cost?

Clarify and choose an approach. What you say: "I'll take an independent gym in a residential area of a large city, about 3,000 sq ft. I'll estimate members from daily visits, then add personal training."

Structure: (paying members × average monthly fee) + personal training revenue.

Key assumptions:

• Peak hours: about 4 a day, morning and evening, with about 60 people per hour.
• Off-peak hours: about 10 a day, with about 15 people per hour.
• Visits per active member: about 4 a week.
• Paying but rarely visiting: about 20% of members, a well-known pattern in gyms.
• Average effective fee: about ₹1,200 a month, as most members buy discounted long-term plans.
• Personal training: about 40 clients at ₹6,000 a month.

Calculation:

• Daily visits: (4 × 60) + (10 × 15) = 240 + 150 = about 390.
• Active members: 390 × 7 ÷ 4 = about 680. Including rarely visiting members: about 850; call it 800 to be conservative.
• Membership revenue: 800 × ₹1,200 = about ₹9.6 lakh.
• Personal training: 40 × ₹6,000 = ₹2.4 lakh.
• Total: about ₹12 lakh a month.

Sanity check from the neighbourhood. What you say: "Within a 1.5 km radius, about 7 sq km, a dense area might have 1.4 lakh people, or about 1 lakh adults. If 5% are gym members, that's 5,000, shared across perhaps six gyms. About 830 members each, which matches."

Answer: about ₹12 lakh a month, likely between ₹8 and ₹18 lakh.

Follow-up interviewers often add: How would you grow revenue without adding floor space? What happens to revenue in January versus June? Is personal training worth expanding?

Clarify and choose an approach. What you say: "I'll estimate GST-registered businesses that would pay for dedicated accounting or bookkeeping software, whether or not they use it today. I'll start from the GST base because those businesses already have compliance needs that create demand."

Structure: GST-registered businesses × share that manage their own books with meaningful invoice volume × share willing to pay.

Key assumptions:

• GST-registered businesses: about 1.7 crore, per GSTN's August 2026 count.
• Share that manage their own books rather than handing everything to an accountant: about 40%, or 68 lakh. Most registrations are very small proprietorships.
• Share of those willing to pay for software: about 50%, or 34 lakh.

Calculation: 1.7 crore × 40% × 50% = about 34 lakh businesses.

Sanity check. What you say: "GSTN reports that about 8.6 lakh businesses generated e-invoices in June 2026. Those are larger firms, and almost all will use software. My estimate is about four times that, which makes sense if many smaller firms also pay for simpler tools."

Answer: About 30 to 35 lakh businesses, likely between 20 and 50 lakh. So what: at an average of ₹6,000 a year, that is a market of roughly ₹2,000 crore a year. For a full TAM, SAM and SOM breakdown, seeMarket sizing.

Follow-up interviewers often add: Which segment would you target first, and why? How would you reach businesses that rely on their accountant? What price would maximise revenue rather than users?

Clarify and choose an approach. What you say: "I'll count new laptops sold in a year to individuals, businesses and government, excluding desktops, tablets and refurbished devices. I'll segment by buyer and use replacement cycles."

Structure: for each segment, laptops in use ÷ replacement cycle in years.

Key assumptions:

• Students: About 4 crore in higher education. About 30% own a laptop, replaced every 4 years.
• Individuals and households, excluding students: About 1.5 crore personal laptops in use, replaced every 5 years.
• Businesses and government: About 2 crore work laptops in use, replaced every 4 years.

Calculation:

• Students: 4 crore × 30% ÷ 4 = 30 lakh.
• Individuals: 1.5 crore ÷ 5 = 30 lakh.
• Businesses and government: 2 crore ÷ 4 = 50 lakh.
• Total: about 1.1 crore laptops a year.

Sanity check. What you say: "That's about one laptop for every 30 households each year. Ownership is concentrated in cities and among working professionals, so that feels plausible rather than high."

Answer: about 1 crore a year, likely between 70 lakh and 1.5 crore. Industry trackers publish quarterly PC shipment figures, which are worth checking your answer against.

Follow-up interviewers often add: How would the answer change if companies moved to five-year replacement cycles? Which segment is growing fastest? How big is the market in rupees?

Clarify and choose an approach. What you say: "I'll take a standard 12-metre city bus, empty of passengers, with seats left in place. I'll estimate the usable volume, then divide by the space each ball takes, and check with a second method."

Structure: usable interior volume × packing efficiency ÷ volume of one ball.

Key assumptions:

• Interior: about 12 m long, 2.5 m wide and 2 m high, so 60 cubic metres.
• Space lost to seats, poles and the driver's cabin: about 20%, leaving 48 cubic metres.
• Tennis ball diameter: about 6.5 cm, so each ball's volume is about 144 cubic cm.
• Packing efficiency: randomly poured spheres fill roughly 60% to 65% of a space. Use 64%.

Calculation:

• Usable volume: 48 cubic metres = 4.8 crore cubic cm.
• Space filled by balls: 4.8 crore × 64% = about 3.1 crore cubic cm.
• Balls: 3.1 crore ÷ 144 = about 2.1 lakh.

Sanity check with cubes. What you say: "If I treat each ball as a 6.5 cm cube, about 275 cubic cm, then 4.8 crore ÷ 275 is about 1.75 lakh. That method ignores the gaps balls can nest into, so it should come out a little lower, and it does."

Answer: about 2 lakh tennis balls, likely between 1.5 and 2.5 lakh.

Follow-up interviewers often add: How would you estimate this without knowing the packing figure? How much would the balls weigh? How long would it take to fill the bus by hand?