UA, Town and Village wise Prosperity Index
Provides pan-India variation in affluence at town/village level
Often, a broad Pan India perspective is desired to enable deployment of effort and resources to high potential destinations. Sometimes, a macro picture enables incremental or ‘balancing’ expansion of network to increase sales with minimal addition of resources.
Which are the rich or wealthy cities, towns or village clusters of the country? How fast they are growing? Who are the prospective customers? These are the basic questions which every marketer wants to answer. Until now, most of the analyses used to be limited to state, district or tehsil level. Strategist is now providing dataset to answer these questions at next level of granularity i.e. town/village. Town/Village maps with attributes as listed below are available in most of the industry standard formats.
Customer databases can now easily be linked to towns / villages and showing up the spatial pattern of the current business, pinpointing growth areas. Current sales and revenues can be compared against demographic and prosperity data. This will allow insights, derive business trends and enable strategy formulation.
Town and village locations are corrected with high resolution satellite imagery so that they are within 10m of actual populated areas. Such high precision map datasets at a pan-India level were never available before and can be used in many demanding applications, including rural marketing.
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 2021 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.
Cities, towns and 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 Towns | % Households | Prosperity Range | % Car Ownership | % Car Market | % Bike Ownership | % Bike Market | % TV Ownership | % TV Market | % Comp. Ownership | % Comp. Market |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 713 | 2.06 | 0 - 616 | 1.37 | 0.29 | 8.28 | 0.49 | 27.81 | 0.75 | 4.92 | 0.55 |
| 2 | 1251 | 5.29 | 617 - 863 | 2.27 | 1.23 | 15.26 | 2.30 | 50.07 | 3.46 | 6.18 | 1.78 |
| 3 | 1327 | 8.44 | 864 - 1055 | 2.83 | 2.45 | 20.13 | 4.84 | 62.91 | 6.93 | 7.52 | 3.45 |
| 4 | 1145 | 8.39 | 1056 - 1232 | 3.85 | 3.31 | 25.54 | 6.10 | 69.44 | 7.60 | 9.28 | 4.23 |
| 5 | 942 | 8.34 | 1233 - 1417 | 4.99 | 4.27 | 30.24 | 7.18 | 73.93 | 8.04 | 11.19 | 5.08 |
| 6 | 922 | 13.20 | 1418 - 1662 | 6.14 | 8.31 | 33.73 | 12.68 | 77.67 | 13.39 | 14.04 | 10.09 |
| 7 | 736 | 17.77 | 1663 - 2027 | 8.70 | 15.86 | 37.91 | 19.18 | 80.24 | 18.61 | 17.85 | 17.26 |
| 8 | 537 | 20.82 | 2029 - 2613 | 12.88 | 27.51 | 42.08 | 24.95 | 84.90 | 23.08 | 24.46 | 27.72 |
| 9 | 242 | 14.99 | 2624 - 3852 | 22.04 | 33.89 | 49.63 | 21.18 | 88.56 | 17.33 | 34.28 | 27.95 |
| 10 | 55 | 0.71 | 3870 - 8477 | 39.60 | 2.88 | 55.20 | 1.11 | 87.93 | 0.81 | 48.98 | 1.89 |
| 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 towns/villages of entire India. Chart below shows town/villagewise pan-India prosperity variation for towns/villages above 5000 population for top ten states.
