Pincodewise Prosperity Index 

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Provides pan-India variation in prosperity at pincode level

Pincode is one of the most popular geographical entities in day to day business. Most enterprises have their customers tagged with an address pincode. They would like to benchmark their customer density against demographic and prosperity data parameters. AInsights Pincode Prosperity Index is ideal for such analysis.

Which are the most prosperous pincodes of the country? How fast are they are growing? Who are the prospective customers? These are basic questions that every marketer wants to answer. Until now, most of the analyses used to be limited to state, district or town level. AInsight is now providing dataset to answer these questions at next level of granularity i.e. pincode. Pincode maps with attributes as listed below are available in most of the industry standard formats.

Customer databases can now easily be linked with a pincode and will reveal a spatial pattern in current businesses, pinpointing growth areas. Current revenues can be compared against demographic and prosperity data. This allows enterprises to gain insight, derive business trends and formulate strategy. For eg. hotspots similar to the high revenue / sales pincodes can be located across the country.

AInsight’s Prosperity Index is derived from household ownership of assets and average penetration level of these assets. Household asset penetration numbers at city, village and ward-level are made available by the census bureau. Using landuse maps and city/village/ward/pincode boundaries these asset ownership numbers are correlated to pincode.

Prosperity Index uses penetration of following assets in households:

  • 1. Percentage Households Using Electricity
  • 2. Percentage Households Using LPG/PNG fuel for Cooking
  • 3. Percentage Households Using Banking Services
  • 4. Percentage Households Using Television
  • 5. Percentage Teledensity
  • 6. Percentage Households Using Computer/Laptop
  • 7. Percentage Households Using Computer/Laptop with internet
  • 8. Percentage Households Using Scooter/Motorcycle/Moped
  • 9. Percentage Households Using Car/Jeep/Van
  • 10. Percentage Households with TV, Computer/Laptop, Landline/Mobile Phone and Scooter/Car

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.

  • 1. State name
  • 2. District name
  • 3. Tehsil name
  • 4. Pincode
  • 5. Post Office Name
  • 6. Total Households
  • 7. Total Population
  • 8. Total Male Population
  • 9. Total Female Population
  • 10. Total Literacy
  • 11. Male Literacy
  • 12. Female Literacy
  • 13. Sex ratio
  • 14. Percentage Households Using Electricity
  • 15. Percentage Households Using LPG/PNG fuel for Cooking
  • 16. Percentage Households Using Banking Services
  • 17. Percentage Households Using Radio/Transistor
  • 18. Percentage Households Using Television
  • 19. Percentage Households Using Computer/Laptop
  • 20. Percentage Households Using Computer/Laptop with internet
  • 21. Percentage Teledensity
  • 22. Percentage Households Using Scooter/Motorcycle/Moped
  • 23. Percentage Households Using Car/Jeep/Van
  • 24. Percentage Households with TV, Computer/Laptop, Landline/Mobile Phone and Scooter/Car
  • 25. Percentage Households with None of the assets
  • 26. Prosperity Index

Market Segmentation ▴

Pincodes 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. target 80% market by only covering 20% areas. One can easily decide target market segments for effective marketing e.g. eg. for microfinance operations, the ideal target segment is pincodes, just above sustenance but not effectively covered by banking.

Prosperity Class No of Pincodes % Households Prosperity Range % Car Ownership % Car Market % Bike Ownership % Bike Market % TV Ownership % TV Market % Comp. Ownership % Comp. Market
1 2695 18.45 0 - 417 1.03 4.03 6.35 5.54 12.22 4.74 4.48 8.67
2 3711 19.79 418 - 599 1.64 6.90 11.38 10.65 25.77 10.73 4.94 10.25
3 3581 15.78 600 - 776 2.21 7.40 16.41 12.25 42.83 14.21 5.36 8.86
4 2560 10.70 777 - 974 3.03 6.90 22.11 11.19 57.53 12.95 6.19 6.94
5 2067 8.50 975 - 1216 4.42 7.99 26.33 10.59 66.22 11.84 8.20 7.30
6 1689 8.31 1217 - 1539 6.23 10.99 32.75 12.86 74.18 12.96 11.37 9.89
7 1508 8.04 1540 - 1997 8.59 14.67 37.47 14.26 80.31 13.59 16.15 13.61
8 892 5.19 1998 - 2717 12.78 14.08 42.58 10.44 84.78 9.25 24.17 13.14
9 678 4.11 2718 - 3840 21.21 18.53 48.46 9.43 87.91 7.61 35.94 15.50
10 219 1.12 3854 - 8066 35.68 8.51 52.74 2.80 90.40 2.13 49.59 5.83

Intra-City Prosperity Estimates ▴

Based on the above methodology we have calculated prosperity index for pincodes of entire India. Chart below shows pincodewise intra-city prosperity variation for top ten cities.