Explore Prosperity Index by Geography
Move across geographic levels without changing the underlying prosperity, population and per-capita-income comparison framework.
Move across geographic levels without changing the underlying prosperity, population and per-capita-income comparison framework.
See rural India market by market — not as one average.
Reveal rural demand hidden inside district and tehsil averages, identify stronger village clusters and prioritise distribution, service and network expansion.
How are the 2025 population and per-capita-income estimates calculated and checked?
Developed and maintained by Strategist Technologies. See the methodology for source data, estimation approach and validation.
Methodology & Validation About StrategistVillage markets differ sharply.
Separate high-potential village clusters from weaker local markets instead of treating an entire district or tehsil as one rural opportunity.
Population + per-capita-income estimates.
Work with annually updated village-level market size and income estimates alongside structural prosperity.
Distribution, services and coverage.
Compare branches, dealers, service points or sales against village market potential to identify underpenetrated rural areas.
Rural India is highly heterogeneous. Villages that appear similar at district or tehsil level can differ substantially in population, prosperity, purchasing power and access to markets. A village-level view makes it possible to identify where rural demand is concentrated and how it varies within broader administrative areas.
Which villages are the most prosperous? Which village clusters have the strongest consumer potential? Where should rural distribution, banking, microfinance, healthcare, telecom or other services be expanded? Strategist provides this analysis at village level so that rural market decisions need not rely only on district or tehsil averages.
Customer, dealer, branch, service-point and sales databases can be linked to villages to reveal the spatial pattern of current rural business. Sales and revenues can then be compared with village-level population, prosperity and per-capita-income estimates to identify underpenetrated markets, service gaps and expansion opportunities.
Village locations are corrected using high-resolution satellite imagery so that they correspond closely to actual populated areas. This provides a consistent pan-India geographic framework for rural marketing, distribution planning, territory design and service-network expansion.
India missed its regular census in 2021, making the latest available census data more than a decade old (from 2011). Even the standard ten-year gap between censuses is too long given how rapidly the country is changing. To bridge this gap, we have developed predictive models using historical census data, yearly built-up area trends since 1991, and school enrollment figures from 2012 onward. This allows us to accurately estimate annual populations for states, districts, towns, villages, wards, and pincodes.
We have also created a model to predict per capita income by using district-level GDP data from 2012 onward, local bank credit growth trends since 2005, and monthly nightlight indices since 2012 derived from VIIRS nightlight imagery. These advanced models enable precise annual estimates of GDP and per capita income at multiple geographic levels, including states, districts, towns, villages, wards and pincodes.
Our models provide detailed annual estimates of population and per capita income from 2012 onward. Estimates for 2025 are now ready, with updates provided each year. Subscribe today for continuous access to the latest insights.
Strategist’s Prosperity Index is derived from household ownership of assets and average penetration level of these assets. Using household asset penetration numbers at city, village and ward-level provided by census bureau, combined with landuse maps and city / village / ward / pincode boundaries these asset ownership numbers are correlated to cities, towns and villages.
Our models generate annual population and per capita income estimates starting from 2012. The population model incorporates census data, built-up area trends since 1991, and recent school enrollment data. The GDP model combines district GDP data, local bank credit growth, and nightlight indices from satellite imagery to deliver accurate and timely insights.
Prosperity Index uses penetration of following assets in households:
Weightage for each asset is (100/national level household penetration of asset) i.e. if asset penetration is 20% then weightage for it is 5 while if asset penetration is 100% then weightage for it is 1.
Prosperity_index is the sum of all above 10 assets multiplied by their weightage factor.
Villages have been segregated into ten classes using a clustering algorithm. Table below shows asset penetration rates increasing consistently as prosperity increases. This can be used for Pareto 80-20 marketing i.e. targeting 80% market by only covering 20% areas. One can also decide market segments for effective targeting e.g. for microfinance, ideal target is people just above sustenance but not effectively covered by banking.
| Prosperity Class | No of Villages | % Households | Prosperity Range | % Car Ownership | % Car Market | % Bike Ownership | % Bike Market | % TV Ownership | % TV Market | % Comp. Ownership | % Comp. Market |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 43936 | 2.79 | 0 - 117 | 0.17 | 0.21 | 1.83 | 0.35 | 2.23 | 0.19 | 0.88 | 0.47 |
| 2 | 71533 | 9.23 | 118 - 233 | 0.45 | 1.85 | 3.75 | 2.40 | 5.76 | 1.59 | 2.00 | 3.58 |
| 3 | 81425 | 12.77 | 234 - 335 | 0.76 | 4.25 | 5.94 | 5.26 | 10.79 | 4.12 | 2.94 | 7.26 |
| 4 | 84420 | 13.89 | 336 - 434 | 1.06 | 6.51 | 8.55 | 8.24 | 17.71 | 7.35 | 3.50 | 9.41 |
| 5 | 81755 | 14.09 | 435 - 536 | 1.40 | 8.68 | 11.23 | 10.98 | 26.89 | 11.32 | 3.96 | 10.81 |
| 6 | 74266 | 13.70 | 537 - 653 | 1.78 | 10.76 | 14.53 | 13.82 | 37.94 | 15.53 | 4.64 | 12.31 |
| 7 | 66526 | 13.46 | 654 - 819 | 2.39 | 14.18 | 18.95 | 17.70 | 50.34 | 20.24 | 5.72 | 14.90 |
| 8 | 54321 | 12.13 | 820 - 1119 | 4.01 | 21.44 | 25.40 | 21.39 | 61.22 | 22.20 | 7.88 | 18.51 |
| 9 | 33007 | 6.93 | 1120 - 1845 | 8.00 | 24.41 | 34.36 | 16.53 | 72.39 | 14.99 | 13.15 | 17.64 |
| 10 | 6429 | 1.02 | 1846 - 10049 | 17.27 | 7.72 | 47.01 | 3.31 | 81.47 | 2.47 | 25.91 | 5.10 |
Based on the above methodology we have calculated prosperity index for villages of entire India. Chart below shows villagewise pan-India prosperity variation for villages above 5000 population for selected states.
Select a state:
Select year:
The map above lets you switch between states and compare villages directly on this page. For a dedicated state view with a focused village-level map, open any of the state pages below.
