Prompt to choose the first Indian city to launch in

You are an operator who has launched products city by city in India. Pick my first city.

Product: [PRODUCT]
Cities I am considering: [CITIES]
What I need from the city: [NEEDS]

Give:
1. A scoring table: each city against reachable users, ability to pay, competition, cost to operate, hiring
2. The figures behind each score (use the ones below; mark the rest as assumptions)
3. The pick and the runner-up, with reasons
4. What would make me change the pick
5. A 60-day launch checklist for the chosen city

Rules:
- Use the India figures listed below and name the source and month next to each one you use.
- If you need a figure that is not listed, write "Assumption:" and give your reasoning instead of a number you cannot source.
- Plain words. Short sections with headings. No filler.

India figures to use (from productgrowth.in/numbers):
- Maharashtra has the most startups in India, with 41,440 DPIIT-recognised startups as on 30 June 2026 out of 2,40,092 nationally, according to DPIIT's reply in the Lok Sabha on 28 July 2026. Source: https://productgrowth.in/numbers/startups-by-state-india/
- Uttar Pradesh has the most internet subscriptions of any Indian state, 155.39 million at the end of June 2026, followed by Maharashtra with 130.11 million, out of 1,114.17 million in India (TRAI). Source: https://productgrowth.in/numbers/internet-subscribers-by-state-india/
- India had 55.49 crore users onboarded on UPI in June 2026 (Ministry of Finance, in a written reply to the Lok Sabha). Source: https://productgrowth.in/numbers/upi-users-india/

Pick: Pune. Runner-up: Hyderabad.

None of the three listed figures is city-level, so most of the table below rests on my operator judgement. Only Pune's score gets real support from your data, and that is state-level.

Scoring (1–5, 5 = best for you)

Competition and cost score higher when the city is easier on you. The totals are close, so treat them as a tiebreaker. Test the top two before committing.

Figures behind the scores

Listed figures (all state-level):

• Maharashtra has 41,440 of 2,40,092 DPIIT-recognised startups (30 June 2026, DPIIT reply in Lok Sabha, 28 July 2026). Pune is a big part of that, which suggests many salaried, online-paying households. The state figure doesn't prove it for Pune. source
• Maharashtra has 130.11 million internet subscriptions of 1,114.17 million nationally (TRAI, June 2026). Good for the state's digital reach, but it says nothing about apartment density. source
• 55.49 crore users onboarded on UPI nationally (Ministry of Finance, Lok Sabha reply, June 2026). This is why online payment is a low risk everywhere, so ability to pay is scored mostly on income. source

Assumptions (verify before committing):

• Assumption: Pune and Hyderabad have the most dense apartment clusters, from IT-corridor housing (Hinjewadi, Wakad, Baner; Gachibowli, Kondapur). Check listings on a property portal.
• Assumption: Hyderabad has the most existing home-service competition, so it gets a 2 on competition. Verify by counting providers on the app stores and Google Maps.
• Assumption: Jaipur and Ahmedabad have lower wages and rents, hence better cost scores. Get actual cleaner pay quotes in each city.
• Assumption: all four cities have enough part-time cleaners, though hiring is easier where large informal settlements sit near apartment clusters.

Why Pune, why Hyderabad second

• Pune: the best match on paying customers. Salaried IT households book online, and apartment societies are easy to approach in clusters.
• Hyderabad: the biggest user pool, but more crowded. It wins if you can show that competitors have poor ratings or unreliable cleaners.

What would change the pick

• If cleaner pay quotes in Pune are 20–30% above Hyderabad's, swap them. Kriyā's estimate
• If three or more established apps already run 4.5-star service in Pune's IT corridor, move to Ahmedabad or Jaipur, where competition is lighter.
• If societies in Pune refuse outside vendors, the dense-apartment advantage disappears.

60-day launch checklist (Pune)

Days 1–15: validate

• Pick two micro-markets (for example Baner-Balewadi and Wakad-Hinjewadi). Stay inside them.
• Talk to 20 society secretaries or RWA members, and 30 cleaners.
• Get real pay quotes and note what residents pay today.

Days 16–30: supply first

• Recruit and verify 25–30 cleaners (ID, police verification, a trial job).
• Set a pay floor and a rating threshold before you sign anyone.
• Run trial cleans for free in 5 societies to fix quality.

Days 31–45: soft launch

• Open bookings in the two micro-markets only. Take payment via UPI.
• Put a poster and a WhatsApp group in each society. Track repeat bookings, not downloads.
• Review every complaint within 24 hours.

Days 46–60: prove the loop

• Check that repeat rate and cleaner utilisation are healthy (set your own targets from days 31–45).
• Fix the weakest step (no-shows, pricing, or ratings).
• Decide go or no-go on a third micro-market.

Next action: this week, find 20 society contacts in Baner and Wakad, and ask what they pay for cleaning now.