India
For India, Esri provides a standard demographics dataset sourced from data supplied by Michael Bauer Research GmbH, an advanced demographics dataset sourced from data supplied by Esri India, and an ArcGIS Places dataset sourced from data supplied by Esri India. Visit Where to find ArcGIS Data to learn more about using Esri Demographics and ArcGIS Places.
Release dates
The standard demographics dataset was updated in November 2026; the vintage is 2026.
The advanced demographics dataset was updated in November 2026; the vintage is 2011 with projected populations from 2011-2036.
The ArcGIS Places dataset was updated in November 2026 with vintage July 2026 data from Esri India.
Settlement points
Esri's Indian standard demographics settlement points use the European Commission Global Human Settlement Layer (GHSL), 100-meter resolution 2025 estimated population raster layer. The points were verified using the latest Esri imagery. More information about the data can be found at
https://ghslsys.jrc.ec.europa.eu.The advanced demographics settlement points use the 2023 European Commission Global Human Settlement Layer (GHSL). More information about the data can be found at
https://ghslsys.jrc.ec.europa.eu. The data was verified using the latest Esri imagery and Michael Bauer Research 2021 population.
Location accuracy
The Indian ArcGIS Places base level geography is geocoded points.
Geography levels
| Esri geography name | Local geography name | Standard demographics count | Advanced demographics count |
|---|---|---|---|
| Country | भारत / India / Bhārat | 1 | 1 |
| States | राज्य / Rajyon aur Kendra Shasit Pradeshon | 36 | 36 |
| Districts | जज़िले / Jilon | 778 | 782 |
| Parliamentary Constituencies | None | — | 545 |
| Subdistricts | तहसील / Tahsilon | 6,996 | 7,038 |
| Assembly Constituencies | None | — | 4,130 |
| Pincodes | None | — | 19,312 |
| Villages and Wards | None | — | 661,194 |
Visualize demographic data variables
The data browser is an interface to help you visualize and explore the data categories and analysis variables available in Esri Demographics. See Explore data variables to learn more about this visualization tool.
Standard demographics use cases
The Esri standard demographics dataset for India is updated with Michael Bauer Research GmbH data updates to this region, approximately every two years. See the Standard demographics related links section below for a variable list and release notes.
The following sections include example use cases that may help you understand India's standard demographics.
Total Population
What is measured: The total number of individuals living in a specific area.
How you use it: Population counts are often used by local and national governments for policy planning, resource allocation, and informed decision-making based on the needs of various population groups within a country or region. You can use this data to explore the allocation of public services, economic development, political representation, social research, and resources available for disaster preparedness.
Population Density
What is measured: The number of people per unit of area (square mile or square kilometer).
How you use it: Population Density is typically used for national and local projects such as infrastructure design, urban planning to allocate and distribute public services, and environmental impact assessments of human activity based on where people are concentrated.
Population per Mill
What is measured: The region's proportional share of the total national population.
How you use it: Population per Mill is used to understand the comparative distribution of population in a country or region based on a per-thousand ratio. This data is used to support market trend analysis, infrastructure planning, and regional and national policy development. Population distribution is often used in health care to track disease prevalence or vaccination rates.
Male/Female Population Totals
What is measured: The total number of females and males in a region's population.
How you use it: Population by Gender counts provide insight into the balance between females and males in a region, which is used for informed decision-making in areas such as education, workforce planning, health care, and skills training. This data is also used to help interpret complex results, such as health-care outcomes, crime statistics, targeted marketing campaigns, and housing shortages.
Population by 15-Year Age and Gender
What is measured: The distribution of regional population across 15-year age groups and gender.
How you use it: Total, Female, and Male Population by 15-Year Age counts can be used to help predict future social and economic trends and to plan for future resource allocation based on age groups in fields such as education, health care, and the labor force. This data is important for identifying potential challenges related to shifts in age or gender ratios within different age brackets.
Total Households
What is measured: The total number of households in a region.
How you use it: Total Household counts can help you understand the composition of a country's population based on how many people live in a single dwelling or housing unit. This data assists with informed decision-making in areas such as government policy, business strategy, community planning, and social research. You can use household counts to identify community needs, allocate public policy funds, perform business market analysis, and design targeted social programs. Local authorities use household counts to plan for community development projects, considering factors such as housing availability and density.
Average Household Size
What is measured: The median or average size of households (people who share the same living quarters) in a region.
How you use it: Average Household Size data helps you understand the overall population structure and informs policy decisions related to housing, resource allocation, and service provisioning. This data is used to analyze economic trends, specifically consumption patterns, based on the number of people sharing living spaces in a region.
Purchasing Power
What is measured: The ability of individuals or households to buy goods and services in a region. Purchasing Power data consists of four metrics:
Total—The sum of all regional household disposable income.
Per Mill—The region's proportional share of the nation's disposable income.
Per Capita—The per-person average of all regional disposable income.
Index—The comparison of regional disposable income to the national average, which has an index value of 100. For example, if a region's purchasing power index is 89, it has 11 percent less disposable income than the national average; if the region's index is 117, it has 17 percent more purchasing power than average.
How you use it: Purchasing Power data can help improve understanding of the potential consumer market in a country or region, specifically to determine pricing strategies and market potential options. This data can be used to develop targeted product, business, and sales strategies when entering a new market or expanding within an existing one.
Consumer Spending
What is measured: The amount of money spent by consumers on goods and services in a region. Consumer Spending data consists of four metrics:
Total—The sum of all regional annual spending on a product or service category—for example, the total amount spent in this region annually on Alcoholic Beverages.
Per Mill—The region's proportional share of the nation's overall annual spending on a category.
Per Capita—The estimated amount spent annually in this region per person on a category.
Index—A comparison of the region's spending on a category to national spending, which has an index value of 100. If a region's spending index is 89, the region spends 11 percent less than the national average on this category; if the regional index is 117, it spends 17 percent more than the national average.
How you use it: Consumer Spending data can be used to understand economic health, consumer behaviors, regional buying trends, and the preferences of different population segments across a country. This data can be used to inform marketing, product development, investment, and public policy strategies based on factors such as age, income level, and geographic location data. Consumer Spending data can support market analysis initiatives, economic forecasting, investment planning, and policy development.
Standard demographics related links
Refer to the following content:
Advanced demographics sample questions and use cases
India's advanced demographics provide additional insight about this region for most data categories. You can find a range of information about Indian regional population and population projections; households, housing characteristics, and dwelling conditions; marital status; access to services, facilities, and resources; education; employment; and income. See the Advanced demographics related links section below for a variable list and release notes.
Some sample questions that could be answered using Indian advanced demographics include the following:
Which regions have the greatest need for additional health care or education services?
What is the projected population growth in major Indian cities over the next decade?
What are the primary spending habits of young adults in major metropolitan areas?
Which areas require additional infrastructure development to support population growth?
Which occupations have the highest employment rates?
The following sections include example use cases that may help you understand Indian advanced demographics.
Household Water Source
What is measured: Regional households based on the source of household drinking water, such as treated tap water or an uncovered well.
How you use it: Indian households grouped by the source of household water can be used by local and national policymakers to manage health risks and water-purification costs based on shifting water quality. Households frequently switch between multiple water sources—such as municipal supply, private borewells, tanker trucks, and rainwater—depending on the season, local scarcity, and daily availability. Because each source has a vastly different chemical and biological profile, tracking them offers immediate practical benefits.
For example, municipal water may have bacterial contamination, borewell water often has high Total Dissolved Solids (TDS) or heavy metals (such as arsenic and fluoride), and tanker water is highly unpredictable. By tracking which source is actively filling the household storage tanks, families can adjust their filtration systems. For example, some smart water purifiers or manual habits bypass aggressive reverse osmosis (RO) filtration when clean municipal water is available (preserving essential minerals and reducing water waste) but switch it on when high-TDS borewell water is used.
Income Housing Characteristics
What is measured: Regional households based on housing unit condition or composition. For example, the number of households in this region with household roof material made from grass, thatch, or bamboo.
How you use it: Indian households by housing characteristics data can be used to target beneficiaries for government affordable housing schemes, such as the Pradhan Mantri Awas Yojana (PMAY). By linking income levels with specific housing deprivation metrics (such as wall material, roof material, and room crowding), policymakers and urban planners can ensure that housing subsidies reach the families who need them most.
India’s affordable housing programs classify eligibility based on economic categories like Economically Weaker Sections (EWS) and Low Income Groups (LIG). Tracking these income metrics alongside current housing conditions (for example, kutcha versus pucca houses) prevents resource leakages to wealthier households and prioritizes those living in unsafe structures.
Urban local bodies (ULBs) use correlated income and structural data to identify specific neighborhoods that require in-situ redevelopment versus those that need basic infrastructure retrofitting (such as piped water or individual toilets). For banks and microfinance institutions, mapping income characteristics against housing types helps design realistic micro-mortgage products for informal sector workers who lack traditional income documentation but need capital for home improvements.
India's Consumer Styles Market Segmentation data
India's advanced demographics catalog includes a Consumer Styles Market Segmentation dataset that provides a summary of the most common traits of a community, used to describe its complexity and patterns at the neighborhood and community level. This dataset includes the following segments:
| Type | Consumer Style | Description |
|---|---|---|
| A | High Earning Urban Professionals | Individuals who typically live in metropolitan areas and large cities and possess a high income, often from a professional occupation. Most belong to single or multiperson households without children and have above-average educational attainment. This consumer style emphasizes careful purchase planning with a high value placed on quality and brand reputation. They are likely to seek products that reflect their status and lifestyle and are motivated by self-expression. |
| B | Comfortably Off Empty Nesters | Individuals typically in their late 40s to 60s whose children have moved out. Their per-capita income is significantly above average. This consumer style is characterized by their financial stability and affluence, often having downsized from larger family homes to smaller residences. They are looking not only for products and services but also for experiences that enhance their quality of life. When shopping, they value high-quality, well-known brands. They frequently return to favorite brands and brick-and-mortar stores, showing a preference for in-person shopping. |
| C | Modern and Pragmatic Over-50s | These individuals are predominantly in the second half of life and live in households without children. Their per-capita income is mostly well above average, however, their per-household income is around or slightly below average. They are characterized by a flexible and informed approach to purchasing decisions. They are tech-savvy and spend significant time online engaging with digital shopping platforms while also seeking personalized and meaningful experiences from brands. They prioritize quality, practicality, and relevance in products and services. |
| D | Well-informed Modern Consumers | These individuals are mostly white-collar employees, the majority earning an above-average per-capita income. They are well-informed consumers who are very knowledgeable about the products and services they purchase, considering factors such as quality, price, ethical implications, and environmental impacts. This consumer style emphasizes the importance of transparency and informed decision-making, makes choices critically, and buys products from companies whose values align with their own. They expect personalized experiences and are likely to engage with brands that resonate with their social and environmental consciousness. |
| E | Affluent Highly Educated Urban Families | These individuals predominantly live in families with children in metropolitan areas and large cities. While this consumer style shows the highest per-household income of all segments, they also show significantly high expenditures per household for almost all product groups. They are mainly employed in managerial positions with far-above-average educational attainment levels. This consumer style enjoys shopping and exhibits the highest online shopping frequency, particularly for new products. Innovation and environmental topics are important. This group has the highest percentage of smartphone users and social network usage. |
| F | Security-oriented Seniors | These individuals are almost all in the second half of life and mostly live in households without children, often in rural areas. This segment has the highest share of retirees and the majority has an average per-capita income. This consumer style places the strongest emphasis on security, relationships with one another, and self-respect, and are most likely to respond positively to marketing that emphasizes these qualities along with reliability. They typically search for the best value for their money and remain loyal to their favorite brands and shops. |
| G | Orientation-seeking Lower and Middle Class Consumers | These individuals are typically in younger age groups living in multiperson households, frequently with children. The majority have a below-average per capita income. What unifies this consumer style is its notable shared values seeking excitement, a sense of belonging, and social engagement. This group is interested in new products, but often finds the quantity and quality of available options confusing, which influences their purchasing behavior and brand loyalty. |
| H | Younger Lower and Middle Class Consumers | The majority of these individuals have a below-average per-capita income. They are mainly members of younger age groups and belong to multiperson households, mostly with children. This consumer style places significant value on education and tradition, which influences their purchasing decisions and lifestyle choices. Their consumption patterns are shaped by their economic constraints, leading to a focus on affordability while still seeking products that resonate with their values and aspirations. |
| I | Modern Younger Families | These individuals are typically part of a multiperson household, almost all with very young children. They are primarily employed in managerial positions or are self-employed. Due to the number of children per household, per-capita income for this consumer style is often below average but household income is often above average. Excitement is important to them, and they seek brands that resonate with their values and lifestyles. This consumer style typically has above-average spending on sports equipment and education while their children are small, and their purchasing behaviors in general are influenced by a desire for authenticity, sustainability, and social consciousness. |
| J | Low-income Modern Consumers | These individuals are almost all teenagers or in their twenties who live in rural areas or smaller cities. They have one of the lowest incomes per consumer style and are notably absent from the labor market, with the highest share of students, unemployed population, and housewives. This consumer style is characterized by a notable desire to engage with current food trends while seeking affordability. They prioritize fresh, less-processed options and are influenced by global culinary trends, aiming for quality at lower prices. This group often looks for good deals on essential items for their families, balancing the need for nutritious meals with budget constraints. Their consumer style reflects a blend of modern preferences and economic limitations, driving them to make informed choices that align with their lifestyle aspirations and financial realities. |
Advanced demographics related links
Refer to the following content:
Release notes—Esri India (PDF)
Variable list—Esri India (CSV)
ArcGIS Places example use cases
The ArcGIS Places dataset for India—sourced from data supplied by Esri India—contains information about more than 15 million places, including destinations such as shopping centers, hotels, banks, public parks, and more. Attributes may include the address, category, and details such as affiliated brands or building names, when available. Refer to Introduction to ArcGIS Places or the Esri India data source topic for more information.
Note:
Refer to Customizable reports and infographics to learn where you can use the Esri India ArcGIS Places dataset in an infographic.
The following sections include example use cases that may help you understand the ArcGIS Places dataset for India.
Businesses may use the ArcGIS Places dataset for India to locate competitors, perform site selections, identify marketing opportunities, and perform proximity analysis.
Urban planners may use the ArcGIS Places dataset for India to understand the distribution of amenities and services within a city, aiding in effective zoning and infrastructure development.
Retailers may use this dataset to assess how well their venues perform and to conduct market research.
Emergency services may use the ArcGIS Places dataset for India to identify critical facilities such as hospitals, fire stations, and schools, enhancing response times and resource allocation during emergencies.
Tourism industry professionals can use the ArcGIS Places dataset for India to create travel guides that highlight points of interest, helping visitors navigate local attractions.
Environmental study researchers can use the ArcGIS Places dataset for India to study the impact of human activities on the environment by analyzing the proximity of certain points of interest to natural resources or protected areas.