Methodology
A 0 to 100 composite. 12 factors. 8 sources. 435 neighborhoods scored across 5 metros. Every number traces back to a verifiable source. No advertiser money. No agent rankings.
Factors
Data sources
Neighborhoods
Metros
Every factor on every neighborhood page works exactly like this. Numbers, sources, traceable.
The scoring model
Government feeds, satellite imagery, and live APIs flow in per neighborhood. Every data point is timestamped and source-tagged.
Each factor scored 0 to 100. Within each factor, 4 to 6 sub-metrics roll up. City-relative calibration keeps comparisons honest within a metro.
Composite is a weighted average of all 12 factors. Default weights match a family-with-kids buyer. Switch to any of 5 persona lenses, or build your own.
Scores map to letter grades. 90+ is A plus. 80+ is A range. 70+ is B range. Below 55 is D. Single number, but the nuance stays visible.
The composite is a tool, not a verdict. A neighborhood scoring 72 might be 95 on schools and 48 on air. The point of HouseIQ is showing you both numbers so you can decide which trade-offs you can live with.
The 12 factors, unpacked
School density within walking radius, distribution of CBSE, ICSE, IB, and state board options, presence of top ranked institutions, quality tier mix.
Sub-metrics rolled up
5 inputsIndian Penal Code crime rates, five year trend, distribution across property crime, violent crime, and offences against women. Street lighting coverage and late-night activity signals.
Sub-metrics rolled up
5 inputsHospital and clinic density, tertiary care hospital reach, ambulance response time estimates, diagnostic center distribution, pharmacy coverage.
Sub-metrics rolled up
5 inputsAnnual PM2.5 and PM10 averages, seasonal variation, exceedance days above WHO thresholds, distance to nearest industrial cluster, traffic pollution corridor proximity.
Sub-metrics rolled up
5 inputsMetro, bus, and rail access, average drive time to primary employment clusters, road connectivity grade, last-mile transit availability, peak-hour congestion impact.
Sub-metrics rolled up
5 inputsPer square foot price for 2 and 3 BHK apartments, monthly rent levels, price-to-income ratio against city median, value-for-money calibrated against amenity score. Higher score means more affordable.
Sub-metrics rolled up
5 inputsRestaurant and cafe density, retail and mall access, recreation and entertainment options, parks and open spaces, supermarket coverage, cultural venues.
Sub-metrics rolled up
5 inputsRoad surface quality, sewerage coverage, street lighting, footpath availability, garbage collection coverage, civic maintenance signals.
Sub-metrics rolled up
5 inputsNormalized Difference Vegetation Index from satellite imagery, tree canopy cover percentage, park area per capita, distance to nearest major park, green ratio.
Sub-metrics rolled up
5 inputsMunicipal water supply consistency, hours of supply per day, groundwater quality indicators, tanker dependency signals, piped water coverage.
Sub-metrics rolled up
5 inputsDiscom outage frequency, average outage duration, peak season stability, under-voltage incidence, backup power requirement signal.
Sub-metrics rolled up
5 inputsHistorical flood incidence, elevation relative to nearest water body, drainage gradient, monsoon waterlogging reports, topographical vulnerability.
Sub-metrics rolled up
5 inputsThe 5 persona lenses
A 65-year-old retired couple and a 27-year-old DINK couple want completely different things from a neighborhood. Same 12 factors, different weights. Here is how each persona sees the data.
Parents buying or renting with school-age kids. Weights schools, safety, and healthcare heavily. Cares about air quality for long-term health. Less sensitive to commute if career is settled.
Factor weights
Single or DINK moving for career growth. Weights commute, amenities, and housing affordability heavily. Less concerned with schools, more with nightlife and restaurant access.
Factor weights
Retirement years. Weights healthcare, safety, and infrastructure heavily. Air quality and green cover critical. Low commute need. Sensitive to walkability and civic maintenance.
Factor weights
Non-resident Indian buying for investment, future return, or family. Weights premium neighborhoods, appreciation potential, healthcare quality (for elderly parents), and overall composite health of the area.
Factor weights
College student, fresh graduate, or early career renter. Weights housing affordability and commute most heavily. Amenities and lifestyle matter. Less sensitive to infrastructure nuance.
Factor weights
Build your own lens · Coming soon
The 5 default personas cover most buyers. But nobody's life fits a template perfectly. You might be a remote-working family who doesn't care about commute. Or a senior citizen who still drinks at the pub. Or an NRI buying a flat for your aging parents who will never set foot on the metro.
Soon, you will be able to move 12 sliders and HouseIQ will re-rank every neighborhood by your specific weighting. Your lens will be shareable via a URL you can send to a spouse or a parent for a gut-check.
Until then, the 5 persona lenses give you a strong starting point, and the individual factor sort on every city page lets you rank by whatever single thing matters most right now.
Your lens · preview
Example: weighted for a work-from-home family that values air quality and schools.
The 8 data sources
Statutory environmental body under the Ministry of Environment, Forest and Climate Change. Operates 1,450 active air quality monitoring stations across India.
Feeds into: Air quality factor, industrial pollution overlay
The largest collaborative geographic database in the world. Open, auditable, and continuously updated by millions of contributors.
Feeds into: Schools, hospitals, amenities, roads, parks, institutional POIs
Bhuvan portal provides satellite imagery and remote sensing data for Indian territory. Used for vegetation indices, elevation, and land use classification.
Feeds into: Green cover, tree canopy, elevation, flood vulnerability mapping
Statutory body under the Ministry of Home Affairs. Publishes annual Crime in India reports with ward-level data.
Feeds into: Safety and crime factor, five-year trend analysis
Commercial traffic and transit API. Provides live commute times, peak-hour congestion, and transit route availability.
Feeds into: Commute and connectivity factor, drive time benchmarking
Aggregated listing data from major Indian residential property platforms. Used to compute per square foot benchmarks and rent levels.
Feeds into: Housing affordability factor, price and rent trends
National meteorological service under the Ministry of Earth Sciences. Tracks rainfall, temperature, and extreme weather events at granular station level.
Feeds into: Flooding risk, monsoon waterlogging history, climate risk
Conducts the decennial Census of India. The most authoritative demographic dataset available for Indian localities.
Feeds into: Demographic context, population density, household composition
Coverage
Phase 1 covers the 5 largest Indian metros by urban population. The next phase adds Tier 2 cities and pin-code level granularity within existing metros.
78 neighborhoods
Explore ›73 neighborhoods
Explore ›121 neighborhoods
Explore ›69 neighborhoods
Explore ›94 neighborhoods
Explore ›Next up. Pune, Hyderabad, Ahmedabad, and Jaipur are in data ingestion. Pin-code level expansion within the 5 current metros is running in parallel. Target: 1,500 neighborhoods by end of year.
Honest limitations
We do not have specific flats or apartments for sale. We tell you which neighborhoods are worth looking at. Once you pick a shortlist of 3 or 4, go to any listing platform to find actual units.
Our scores update weekly at the fastest, monthly or quarterly for many factors. For a buy decision spanning months, that granularity is right. For a "what is the air like this Tuesday" query, go to a live AQI source.
Data captures patterns. It does not capture how a street feels at 10pm, whether your future neighbor plays loud music, or if the local market vendor is friendly. Visit the shortlist. Walk around at different times. Trust the signal beyond the scorecard.
Livability score is not price forecast. A neighborhood with a great composite score may still see flat or declining prices. For investment thesis, use our coming Price Intelligence layer (weeks 3 to 4).
Any single score is a compression of messy reality. We publish sub-metrics so you can dig past the number. We maintain a feedback page so users can flag calibration misses. We update scores as sources improve.
Update cadence
Corrections
Every locality page has a Suggest fix button. Every piece of feedback lands in a queue reviewed weekly. When a correction triggers a regeneration, the page is updated and the contributor is acknowledged.
Share feedback ›Who built HouseIQ
HouseIQ is built by an independent founder team, funded from operating revenue, not venture capital. We take no money from property developers, no affiliate commissions from brokers, and no sponsored placements of any kind. The only way HouseIQ is useful is if it is trustworthy. The only way it stays trustworthy is if we stay independent.