area_id | p2023 | p_06 | p_7_ | p_sc | p_st | p_s_ | p_lit | p_ill | mainwork_p | mgwk_0_3_p | mgwk_3_6_p | non_work_p | main_cl_p | main_al_p | main_hh_p | main_ot_p |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3983148 | 234 | 25 | 206 | 50 | 4 | 177 | 160 | 67 | 19 | 3 | 15 | 130 | 9 | 15 | 6 | 48 |
3983197 | 461 | 49 | 408 | 98 | 8 | 351 | 317 | 134 | 38 | 6 | 31 | 256 | 18 | 30 | 12 | 95 |
3983198 | 687 | 71 | 610 | 118 | 1 | 562 | 513 | 158 | 22 | 4 | 18 | 417 | 6 | 7 | 16 | 201 |
3983241 | 1153 | 124 | 1019 | 247 | 21 | 875 | 793 | 335 | 95 | 16 | 78 | 642 | 45 | 75 | 30 | 239 |
3983242 | 512 | 55 | 452 | 109 | 9 | 389 | 352 | 148 | 42 | 7 | 34 | 285 | 20 | 33 | 13 | 106 |
3983258 | 212 | 22 | 188 | 45 | 3 | 162 | 146 | 61 | 17 | 3 | 14 | 118 | 8 | 13 | 5 | 44 |
3983259 | 112 | 12 | 98 | 23 | 2 | 85 | 76 | 32 | 9 | 1 | 7 | 62 | 4 | 7 | 2 | 23 |
3983262 | 412 | 44 | 364 | 88 | 7 | 313 | 283 | 119 | 34 | 6 | 28 | 229 | 16 | 26 | 10 | 85 |
3983263 | 37 | 3 | 33 | 7 | 0 | 29 | 25 | 10 | 3 | 0 | 2 | 20 | 1 | 2 | 0 | 7 |
3983264 | 677 | 67 | 556 | 134 | 11 | 478 | 432 | 182 | 52 | 9 | 42 | 350 | 24 | 41 | 16 | 130 |
area_id | w2022 | uc2022 | mc2022 | nc2022 | p5_2022 | p4_2022 | p3_2022 | p2_2022 | p1_2022 | sfb356 | sg356 | sap356 | sonf356 | s356 | sfb356pc | sg356pc | sap356pc | sonf356pc | s356pc |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1801913 | 0.0 | 44.0 | 59.0 | 453.0 | 44.0 | 59.0 | 106.0 | 201.0 | 146.0 | 13181648.0 | 28838533.0 | 4686003.0 | 12171617.0 | 58877801.0 | 42.64208633093525 | 93.2931654676259 | 15.160071942446043 | 39.37589928057554 | 190.46942446043167 |
1801914 | 0.0 | 49.0 | 66.0 | 499.0 | 49.0 | 66.0 | 117.0 | 221.0 | 161.0 | 14552143.0 | 31836873.0 | 5173207.0 | 13437100.0 | 64999323.0 | 38.61400651465798 | 84.48045602605863 | 13.72801302931596 | 35.656351791530945 | 172.47719869706842 |
1801916 | 0.0 | 17.0 | 29.0 | 227.0 | 17.0 | 29.0 | 58.0 | 100.0 | 69.0 | 6078482.0 | 13397909.0 | 2121885.0 | 5443679.0 | 27041955.0 | 81.57142857142857 | 179.7985347985348 | 28.476190476190474 | 73.05494505494505 | 362.8974358974359 |
1801917 | 0.0 | 56.0 | 96.0 | 739.0 | 56.0 | 96.0 | 189.0 | 328.0 | 222.0 | 19848667.0 | 43749514.0 | 6928802.0 | 17775781.0 | 88302764.0 | 24.993265993265993 | 55.08978675645342 | 8.725028058361392 | 22.383838383838384 | 111.19079685746352 |
1801920 | 0.0 | 40.0 | 54.0 | 408.0 | 40.0 | 54.0 | 96.0 | 181.0 | 131.0 | 11913114.0 | 26063260.0 | 4235046.0 | 11000283.0 | 53211703.0 | 47.22908366533864 | 103.32868525896414 | 16.790836653386453 | 43.61155378486056 | 210.9581673306773 |
1801921 | 0.0 | 66.0 | 112.0 | 867.0 | 66.0 | 112.0 | 222.0 | 385.0 | 260.0 | 23276622.0 | 51305253.0 | 8125437.0 | 20845739.0 | 103553051.0 | 21.31004784688995 | 46.97129186602871 | 7.439234449760765 | 19.085167464114832 | 94.80478468899521 |
1801959 | 0.0 | 93.0 | 152.0 | 929.0 | 93.0 | 152.0 | 256.0 | 420.0 | 253.0 | 29968024.0 | 64944218.0 | 10902549.0 | 28749379.0 | 134564170.0 | 21.7427597955707 | 47.120102214650764 | 7.910562180579216 | 20.858603066439525 | 97.63202725724021 |
1801960 | 0.0 | 26.0 | 43.0 | 268.0 | 26.0 | 43.0 | 73.0 | 120.0 | 75.0 | 8598924.0 | 18634876.0 | 3128340.0 | 8249250.0 | 38611390.0 | 75.74480712166172 | 164.1513353115727 | 27.55786350148368 | 72.66468842729971 | 340.1186943620178 |
1801962 | 250.0 | 149.0 | 244.0 | 1490.0 | 149.0 | 244.0 | 411.0 | 674.0 | 405.0 | 48058582.0 | 104148576.0 | 17484004.0 | 46104287.0 | 215795449.0 | 13.556027615507169 | 29.378120021242697 | 4.932023366967605 | 13.004779607010091 | 60.87095061072756 |
1801963 | 2246.0 | 120.0 | 196.0 | 1196.0 | 120.0 | 196.0 | 330.0 | 541.0 | 325.0 | 38587414.0 | 83623447.0 | 14038336.0 | 37018263.0 | 173267460.0 | 16.882275132275133 | 36.58664021164021 | 6.142195767195767 | 16.195767195767196 | 75.8068783068783 |
file | column_id | classification_label | label | Base / Premium |
---|---|---|---|---|
india_base | p2022 | Population Summary | Resident Population 2022 | Base |
india_premium | w2022 | Population Summary | Workers 2022 (working within catchment, major cities only) | Premium |
india_premium | uc2022 | Consuming Class (2022, No of Residents) | Premium Consuming Class (SEC A) | Premium |
india_premium | mc2022 | Consuming Class (2022, No of Residents) | Other Consuming Class (SEC B) | Premium |
india_premium | nc2022 | Consuming Class (2022, No of Residents) | Non Consuming Class (SEC C/D/E) | Premium |
india_premium | p5_2022 | Prosperity Index (2022, No of Residents) | A. High (% of residents) | Premium |
india_premium | p4_2022 | Prosperity Index (2022, No of Residents) | B. Mid-High (% of residents) | Premium |
india_premium | p3_2022 | Prosperity Index (2022, No of Residents) | C. Mid (% of residents) | Premium |
india_premium | p2_2022 | Prosperity Index (2022, No of Residents) | D. Low-Mid (% of residents) | Premium |
india_premium | p1_2022 | Prosperity Index (2022, No of Residents) | E. Low (% of residents) | Premium |
category | business_name | uuid | title | address | suburb | postcode | latitude | longitude | location_status | country | state | location_updated_date | location_validated_date |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cafe | Bask Bear Coffee | 7aa99f3d-9b29-11ed-89a2-040300000000 | Bask Bear Coffee Supreme, Pavilion Bukit Jalil | Pusat Bandar, Pavilion, Lot 1.79.01, Level 1, 2, Persiaran Jalil Utama, Bukit Jalil, 57000 Kuala Lumpur, Federal Territory of Kuala Lumpur | Kuala Lumpur | NULL | 3.0507085 | 101.6707302 | Open | Malaysia | Kuala Lumpur | 28-Sep-2023 | 11-Mar-2024 |
Cafe | Black Canyon Coffee | ec10c827-3597-11ec-9dfd-0627e559a1f8 | Palm Mall, Seremban | Lot G 37, Palm Mall Seremban | Seremban | NULL | 2.71942629999999 | 101.9222099 | Open | Malaysia | Negeri Sembilan | 30-Aug-2023 | 06-Apr-2024 |
Cafe | Boost Juice | b67fa472-d260-11ec-a628-0627e559a1f8 | Jakel Mall | Lot No. SC.04 (StreetCafe) Jakel Mall Signature APB Jalan Munshi Abdullah Wilayah Persekutuan Kuala Lumpur | Kuala Lumpur | NULL | 3.153694 | 101.699081 | Open | Malaysia | Kuala Lumpur | 25-May-2023 | 22-Jan-2024 |
Cafe | Cafe Mesra | e8044a99-d5fd-11ee-aefe-02dcee84255c | Alam Damai | Alam Damai, 56000 Kuala Lumpur, Federal Territory of Kuala Lumpur | Kuala Lumpur | NULL | 3.060074 | 101.7406559 | Open | Malaysia | Kuala Lumpur | 28-Feb-2024 | 28-Feb-2024 |
Cafe | Chagee | 29c0b46b-dd3c-11ee-aefe-02dcee84255c | CHAGEE 霸王茶姬 Aman Jaya, Kedah | Block E-5, PT 60651, Jalan Jati 1/1 Pusat Perniagaan Amanjaya 08000 Sungai Petani, Kedah. | Sungai Petani | NULL | 5.675249 | 100.5080591 | Open | Malaysia | Kedah | 08-Mar-2024 | 08-Mar-2024 |
Cafe | Coffea Coffee | 2699238e-237f-11ed-92ec-0627e559a1f8 | Taman Desa | 1/109F, Kuala Lumpur, Malaysia | Kuala Lumpur | NULL | 3.0983465 | 101.6869688 | Open | Malaysia | Kuala Lumpur | 24-Aug-2022 | 22-Jan-2024 |
Cafe | Coffee Academics | 8174d225-39a0-11ed-b6e1-0627e559a1f8 | Pavilion Kuala Lumpur | Lot C3.02.00, Connection, Level 3 Jalan Bukit Bintang, 55100 Kuala Lumpur | Kuala Lumpur | NULL | 3.148858342 | 101.7132507 | Open | Malaysia | Kuala Lumpur | 21-Sep-2022 | 16-Jan-2024 |
Cafe | Costa Coffee | a89d70ac-3596-11ec-9dfd-0627e559a1f8 | Q Sentral | Level M1, 2A, Jalan Stesen Sentral 2,Kuala Lumpur Sentral, 50470 Kuala Lumpur | Kuala Lumpur | NULL | 3.1367269078202 | 101.687882809727 | Open | Malaysia | Kuala Lumpur | 22-May-2023 | 09-Jan-2024 |
Cafe | Cotti Coffee | 2487b205-c983-11ee-8293-02dcee84255c | COTTI COFFEE- Zenith Store, Johor Bahru | G 05, 82C, Jalan Trus, Bandar Johor Bahru, 80000 Johor Bahru, Johor, Malaysia | Johor Bahru | NULL | 1.4631041 | 103.7617943 | Open | Malaysia | Johor | 12-Feb-2024 | 27-Feb-2024 |
Cafe | Doi Chaang | 8041a4c0-3597-11ec-9dfd-0627e559a1f8 | 28a, Jalan Medan Ipoh 9, Bandar Baru Medan Ipoh | Jalan Medan Ipoh 7, Ipoh, Malaysia | Ipoh | NULL | 4.6159723 | 101.1222086 | Open | Malaysia | Perak | 18-Jul-2022 | 31-Mar-2024 |
Description
Sourcing accurate and up-to-date GIS data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly. GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent GIS data across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities. With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to: - Better understand your customers - Identify optimal locations to expand your retail footprint - Define sales territories for franchisees - Run targeted marketing campaigns. GapMaps GIS data for Asia and MENA can be utilized in any GIS platform and includes the latest Demographic estimates (updated annually) including: 1. Population (how many people live in your local catchment) 2. Census Demographics (who lives within your local catchment) 3. Worker population (how many people work within your local catchment) 4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers) 5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category. GapMaps GIS Data also includes Point-Of-Interest (POI) Data updated monthly across a range of categories including Fast Food, Cafe, Health & Fitness and Supermarket/ Grocery Primary Use Cases for GapMaps GIS Data: 1. Retail Site Selection - identify optimal locations for future expansion and benchmark performance across existing locations. 2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential 3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics 4. Target Marketing: Develop effective marketing strategies to acquire more customers. 5. Integrate GapMaps GIS data with your existing GIS or BI platform to generate powerful visualizations.
Country Coverage
(6 countries)Data Categories
- Demographic Data
- Map Data
- GIS Data
- Geodemographic Data
- Spending Data
Pricing
One-off purchase |
Not available |
Monthly License |
Not available |
Yearly License |
Available |
Usage-based |
Not available |
Volumes
- Small Area regions assessed in India
- 3.7M
- Small Area Regions assessed in Singapore
- 46K
- Small Area Regions Assessed in Saudi Arabia
- 3.5M
- Small Area Regions Assessed in Indonesia
- 1.49M
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