Wardwise Prosperity Index 

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Provides intra-city variation in prosperity at ward level

Often, Ward level data is what the enterprise may be comfortable working with.

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

AInsight has created a Prosperity Index for each geography upto ward level. For the first time one can see the intracity variation in prosperity. AInsight’s Prosperity Index is derived from household ownership of assets and average penetration level of these assets.

The Ward Maps are geo-referenced using high resolution satellite imagery. Every attempt is made for high positional accuracy of map.

AInsight’s Prosperity Index is derived from household ownership of assets and average penetration level of these assets. Using household asset penetration numbers at ward-level provided by census bureau, AInsight has created a Prosperity Index at Ward granularity.

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. City name
  • 5. Ward No
  • 6. Total Household
  • 7. Total Population
  • 8. Total Male
  • 9. Total Female
  • 10. 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
Sr No City Name State District Population Census 2011 Wards
1 Greater Mumbai Maharashtra Mumbai 12442373 88
2 Delhi Delhi Delhi 11402709 272
3 Bengaluru Karnataka Bengaluru 8495492 198
4 Hyderabad Telangana Hyderabad 6993262 150
5 Ahmedabad Gujarat Ahmedabad 5633927 57
6 Chennai Tamil Nadu Chennai 4646732 155
7 Surat Gujarat Surat 4501610 101
8 Kolkata West Bengal Kolkata 4496694 141
9 Pune Maharashtra Pune 3196239 144
10 Jaipur Rajasthan Jaipur 3046163 77
11 Lucknow Uttar Pradesh Lucknow 2880108 110
12 Kanpur Uttar Pradesh Kanpur Nagar 2876591 110
13 Nagpur Maharashtra Nagpur 2405665 136
14 Indore Madhya Pradesh Indore 1994397 69
15 Thane Maharashtra Thane 1841488 116
16 Bhopal Madhya Pradesh Bhopal 1798218 70
17 Vadodara Gujarat Vadodara 1752371 13
18 Visakhapatnam Andhra Pradesh Visakhapatnam 1728128 72
19 Pimpri Chinchwad Maharashtra Pune 1727692 106
20 Patna Bihar Patna 1684297 72
21 Ghaziabad Uttar Pradesh Ghaziabad 1648643 80
22 Agra Uttar Pradesh Agra 1638757 90
23 Ludhiana Punjab Ludhiana 1618879 75
24 Nashik Maharashtra Nashik 1486053 108
25 Faridabad Haryana Faridabad 1414050 35
26 Meerut Uttar Pradesh Meerut 1398741 80
27 Rajkot Gujarat Rajkot 1323363 23
28 Kalyan-Dombivli Maharashtra Thane 1247327 107
29 Varanasi Uttar Pradesh Varanasi 1212610 90
30 Srinagar Jammu & Kashmir Srinagar 1206419 68
31 Allahabad Uttar Pradesh Allahabad 1195329 80
32 Aurangabad Maharashtra Aurangabad 1193167 99
33 Dhanbad Jharkhand Dhanbad 1162472 55
34 Amritsar Punjab Amritsar 1159227 65
35 Navi Mumbai Maharashtra Thane 1120547 89
36 Jabalpur Madhya Pradesh Jabalpur 1081677 70
37 Haora West Bengal Haora 1077075 50
38 Ranchi Jharkhand Ranchi 1073427 55
39 Gwalior Madhya Pradesh Gwalior 1069276 60
40 Vijayawada Andhra Pradesh Krishna 1057285 77
41 Jodhpur Rajasthan Jodhpur 1056191 65
42 Coimbatore Tamil Nadu Coimbatore 1050721 72
43 Raipur Chhattisgarh Raipur 1027264 70
44 Madurai Tamil Nadu Madurai 1017865 72
45 Kota Rajasthan Kota 1001694 60
46 Chandigarh Chandigarh Chandigarh 970602 26
47 Guwahati Assam Kamrup Metropolitan 962334 60
48 Solapur Maharashtra Solapur 951558 98
49 Hubli-Dharwad Karnataka Dharwad 943788 67
50 Bareilly Uttar Pradesh Bareilly 934800 70
51 Mysuru Karnataka Mysore 920550 65
52 Moradabad Uttar Pradesh Moradabad 887871 70
53 Gurgaon Haryana Gurgaon 886519 33
54 Bhubaneswar Orissa Khordha 885363 60
55 Aligarh Uttar Pradesh Aligarh 874408 70
56 Tiruchirappalli Tamil Nadu Tiruchirappalli 847387 60
57 Salem Tamil Nadu Salem 829267 60
58 Mira-Bhayandar Maharashtra Thane 809378 79
59 Thiruvananthapuram Kerala Thiruvananthapuram 788271 86
60 Bhiwandi Nizampur Maharashtra Thane 709665 84
61 Gorakhpur Uttar Pradesh Gorakhpur 673446 70
62 Amravati Maharashtra Amravati 647057 81
63 Bikaner Rajasthan Bikaner 644406 60
64 Bhilai Nagar Chhattisgarh Durg 627734 67
65 Dehradun Uttarakhand Dehradun 627556 60
66 Kochi Kerala Ernakulam 625201 73
67 Cuttack Orissa Cuttack 610189 54
68 Bhavnagar Gujarat Bhavnagar 605882 17
69 Jammu Jammu & Kashmir Jammu 604594 71
70 Jamnagar Gujarat Jamnagar 600943 19
71 Durgapur West Bengal Barddhaman 566517 43
72 Asansol West Bengal Barddhaman 563917 50
73 Kozhikode Kerala Kozhkode 550440 55
74 Kolhapur Maharashtra Kolhapur 549236 77
75 Nellore Andhra Pradesh Sri Potti Sriramulu Nellore 547621 50
76 Gulbarga Karnataka Gulbarga 543147 55
77 Ajmer Rajasthan Ajmer 542321 55
78 Raurkela Orissa Sundargarh 536450 52
79 Jhansi Uttar Pradesh Jhansi 534036 60
80 Loni Uttar Pradesh Ghaziabad 516082 45
81 Ujjain Madhya Pradesh Ujjain 515215 54
82 Siliguri West Bengal Darjiling 513264 47
83 Sangli Miraj Kupwad Maharashtra Sangli 502793 74
84 Mangaluru Karnataka Dakshina Kannada 499487 60
85 Belgaum Karnataka Belgaum 490045 58
86 Malegaon Maharashtra Nashik 481228 72
87 Gaya Bihar Gaya 474093 53
88 Tirunelveli Tamil Nadu Tirunelveli 473637 55
89 Jalgaon Maharashtra Jalgaon 460228 69
90 Udaipur Rajasthan Udaipur 451100 55
91 Maheshtala West Bengal South Twenty Four Parganas 448317 35
92 Patiala Punjab Patiala 446246 50
93 Davanagere Karnataka Davanagere 434971 41
94 Akola Maharashtra Akola 425817 71
95 Rajpur Sonarpur West Bengal South Twenty Four Parganas 424368 35
96 Bellary Karnataka Bellary 410445 35
97 Bally West Bengal Haora 406750 35
98 South DumDum West Bengal North Twenty Four Parganas 403316 35
99 Rajarhat Gopalpur West Bengal North Twenty Four Parganas 402844 35
100 Bhagalpur Bihar Bhagalpur 400146 51
101 Agartala Tripura West Tripura 400004 35
102 Bhatpara West Bengal North Twenty Four Parganas 386019 35
103 Latur Maharashtra Latur 382940 62
104 Panihati West Bengal North Twenty Four Parganas 377347 35
105 Rohtak Haryana Rohtak 374292 31
106 Kollam Kerala Kollam 367107 52
107 Bilaspur Chhattisgarh Bilaspur 365579 55
108 Korba Chhattisgarh Korba 365253 58
109 Brahmapur Orissa Ganjam 356598 37
110 Muzaffarpur Bihar Muzaffarpur 354462 49
111 Tirupati Andhra Pradesh Chittoor 333291 20
112 Kamarhati West Bengal North Twenty Four Parganas 330211 35
113 Bijapur Karnataka Bijapur 327427 35
114 Shimoga Karnataka Shimoga 322650 35
115 Junagadh Gujarat Junagadh 319462 18
116 Thrissur Kerala Thrissur 315957 52
117 Barddhaman West Bengal Barddhaman 314265 35
118 Parbhani Maharashtra Parbhani 307170 57
119 Hisar Haryana Hisar 307024 31
120 Tumkur Karnataka Tumkur 302143 35
121 Ozhukarai Puducherry Puducherry 300104 37

Market Segmentation ▴

Wards have been segregated into ten classes using 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. You can also decide your market segments for effective targeting e.g. microfinance ideal target is people just above sustenance but not effectively covered by banking.

Prosperity Class No of Wards % Households Prosperity Range % Car Ownership % Car Market % Bike Ownership % Bike Market % TV Ownership % TV Market % Comp. Ownership % Comp. Market
1 7299 3.77 0 - 551 0.85 0.33 7.16 0.77 27.14 1.33 3.37 0.68
2 12554 8.15 552 - 821 1.66 1.39 14.21 3.29 52.44 5.58 4.90 2.14
3 12764 10.43 822 - 1047 2.43 2.60 20.14 5.96 65.49 8.91 6.80 3.79
4 11603 11.71 1048 - 1267 3.50 4.21 25.91 8.61 72.90 11.14 8.90 5.58
5 10455 12.63 1268 - 1513 4.91 6.37 31.92 11.45 77.75 12.82 11.62 7.86
6 9247 13.47 1514 - 1827 6.75 9.33 36.24 13.85 81.75 14.37 15.46 11.14
7 7595 12.52 1828 - 2275 9.71 12.48 42.89 15.24 85.15 13.91 20.71 13.87
8 5787 13.19 2276 - 2996 14.55 19.70 48.33 18.10 87.85 15.12 28.62 20.21
9 3305 9.93 2997 - 4305 24.09 24.56 55.26 15.58 90.34 11.71 40.65 21.61
10 1143 4.21 4306 - 9724 44.10 19.04 59.85 7.15 92.91 5.10 58.27 13.12

Intra-City Prosperity Estimates ▴

Based on the above methodology we have calculated prosperity index for all wards of top cities. Chart below shows wardwise intra-city prosperity variation for top ten cities.