GapMaps Demographic Data in India

Comprehensive and Granular Global Demographic Data

GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent demographic datasets across Australia, India, South East Asia, Saudi Arabia and North America.

Demographic datasets including the latest estimates on resident and worker populations, census metrics, consuming class and retail spend data are updated annually and available at small grid levels (eg. 150m x 150m) which is essential for location planning feasibility assessments in each region. 

Understand who lives in a catchment, where they work and their spending potential so you can make more informed location planning decisions and run targeted marketing campaigns globally.

Datasets trusted by some of the world’s biggest brands to make site selection decisions

Globally consistent demographic datasets

 

Access to global, high quality demographic datasets across Asia and the Middle East has historically been challenging for brands looking to make location decisions in these regions. GapMaps provides globally consistent demographic data at small area grid levels so you can assess the potential of a market, not only in the major cities, but in local suburbs and regions. 

Our demographic datasets include:

Census Estimates

 

GapMaps provides the latest estimates on Census demographic metrics such as population size, age profile, languages spoken at home, education status, occupation summary and other key statistics. See the table below for the full list of demographic attributes available in each country.

Worker (Daytime) Population Estimates

 

GapMaps uses mobile device data to determine daytime worker populations at small grid levels (excluding devices that have the same daytime and evening location such as home workers, stay at home parents, shops connected to dwellings).

Consuming Class Data

 

Consuming class data identifies those persons able to buy non-essential goods and services other than those that satisfy their basic needs. GapMaps provides consuming class estimates at a city or district level down to grid level which is shown to be highly correlated with store sales for the majority of brands we work with.

Retail Spending Data

 

GapMaps utilises available government data sources and mobile device data to provide retail spending estimates including total spend per capita and spend breakdown across a number of categories including Food & Beverage, Supermarket/Groceries, Apparel, and more.

GapMaps Data Shopfront

 

You can browse the complete range of GapMaps data products and pricing in our GapMaps Data Products Shopfront. Filter by country or category to quickly find the data you need.

Access directly in AWS

 

If you have an AWS account, you can access GapMaps Demographic data directly through the AWS Data Exchange, your one-stop-shop to securely find, subscribe to, and use third-party data in the cloud charged to your AWS bill.

Summary of global demographic datasets

Country
Geographic Area
Summary of Data / Variables
Summary of Data / Variables
Summary of Data / Variables
Summary of Data / Variables
Summary of Data / Variables
Country
Geographic Area
Population
Demographics
Worker (Daytime) Population
Consuming Class
Retail Spend Data
Indonesia

150m x 150m grids (Top 30 cities)

Outside of cities: 1km x 1km grids


2023
2023 Estimates (based on 2020 Census): Age Profile, Language spoken at home, Education Status, Occupation Summary, Highest Level of Education

2023

2023

2023
India

150m x 150m grids (Top 65 cities)

Outside of cities: 1km x 1km grids


2022
2011 Census Metrics: Age Profile (0-6, 7+), Scheduled Caste / Tribes, Literacy, Employment/
Education

2022
(Cities with 50k+ residents)

2022
(SEC A + B)

2022
Malaysia

150m x 150m grids (Tier 1, 2, 3 cities)

Outside of cities: 1km x 1km grids


2023
2023 Estimates (based on 2020 Census): Sex, Age Summary, Age Profile (5 year bands), Ethnicity

2023

2023

2023
Saudi Arabia

150m x 150m grids

Outside of cities: 1km x 1km grids


2023
2023 Estimates (based on 2020 Census): Population, Population by sex, Median age by sex, Household size, residential dwellings by type

2023
(Tier 1-3 cities)

2023
Australia
- SA1 Level

Population Estimates (2022)


Historic Population (2011-2022)


Forecast Population-SA2 Level
(2023-2036)


Age Projections-SA2 Level
(2023-2036)

2021 Census Metrics: Age, Income, Occupation, Place of Birth, Students, Household Size, Dwelling Tenure, Dwelling Structure, Family Composition, No. Motor Vehicles, Monthly Mortgage, Weekly Rental, Number of Bedrooms, SEIFA

2021
(Workers, Worker Occupation, Count of Businesses)
SA2 Level
USA


Population (2020 Census)


Population Estimates (Current Year)


Forecast Population
(5 years)

2020 Census Metrics/latest estimates on
Population* (eg. Age, Sex, Race, Marital Status), Labour Force*, Households*, Income*, Dwellings*, Non-resident population (overnight tourists), Consumer Expenditures*, Daytime Demographics, Retail Potential & Gap*, Environmental Risk, Crime Risk*, Panaroma Can Am segmentation.
Canada


2021
2021 Census Estimates on
Population (eg. age, sex, age by sex), Labour Force, Households, Income, Dwellings, Panorama Can Am segmentation, Consumer Expenditures, Household Wealth
Singapore

150m x 150m grids
(major cities)

Outside of cities: 1km x 1km grids


2022
2020 Census Metrics: Residents by housing/visa type, age profile, ethnicity, income, language spoken at home, education level, students (Residents only)

2022

2022

2022

*Five year projections available