For Germany, Esri provides a standard demographics dataset sourced from data supplied by Michael Bauer Research GmbH and an advanced demographics dataset sourced from data supplied by Nexiga. Visit Where to find Esri Location Data to learn more about using standard and advanced demographics.
Release dates
- The standard demographics dataset was updated in February 2025; the vintage is 2024 (Unemployed Population 2023).
- The advanced demographics dataset was updated in February 2025; the vintage is 2024.
Settlement points
- Esri's German standard demographics settlement points use Nexiga Jan 2024 residential building centroids with population, verified with Esri imagery.
- Esri's German advanced demographics settlement points use 2024 Nexiga residential housing unit points, verified using Esri imagery and previous settlement points.
Geography levels
| Esri geography name | Local geography name | Standard demographics feature count | Advanced demographics feature count |
|---|---|---|---|
Country | Deutschland | 1 | 1 |
Postcodes1/Postal Zones | Postleitzonen | 10 | 10 |
States | Bundesländer | 16 | 16 |
Provinces | Regierungsbezirke | 38 | — |
Postcodes2/Postal Regions | Postleitregionen | 95 | 95 |
Districts | Kreise | 400 | 400 |
Postcodes5/Postcodes | Postleitzahlen | 8,169 | 8,170 |
Municipalities | Gemeinden | 10,957 | 10,979 |
Neighborhoods | None | — | 88,010 |
Visualize demographic data categories
The data browser is a visualization tool to help you explore the data categories available in this country or region's standard and advanced demographics. See Use the data browser to learn more about this visualization tool.
Standard demographics use cases
The Esri standard demographics dataset for Germany is updated with Michael Bauer Research GmbH data updates to this region, approximately every year. See the Standard demographics related links section below for a complete list of variables, release notes, and a sample report.
Example use cases that may help you understand Germany's standard demographics include the following:
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 to make informed decisions based on the needs of different 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 (sq. mile or sq. 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 to assess the environmental impact of human activity based on where people are concentrated. |
Population per Mill
 | What is measured: The number of individuals in a region per thousand. How you use it: Population per Mill is used to understand the comparative distribution of population around 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 males and females in a region's population. How you use it: Male and Female Population counts provide insight into gender balance, which is used for informed decision-making in areas like 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 Totals by Age and Gender
 | What is measured: The distribution of regional population across age groups and gender. How you use it: Male and Female Population by 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 like 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 like 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 to 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. |
Households by Income
 | What is measured: Regional households based on reported income levels. How you use it: Households by Income data is used to analyze income inequality within a country's population. Income quintiles can help you understand the distribution of wealth across different socioeconomic groups. This data can help you effectively target policies or marketing strategies based on income levels, identifying areas where specific demographics might need additional support or where certain products or services could have higher market potential based on income brackets. |
Households by Type
 | What is measured: Regional households based on their relationship structure. How you use it: Households by Type categories are used to tailor housing and marketing policies in a region based on different household compositions—such as single-person households, extended families, and so on—and their specific needs. This data is important for policymakers and data analysts who work with infrastructure, housing, education, health-care, and marketing information. |
Marital Status
 | What is measured: Regional population based on marital status categories. How you use it: Marital Status categories are used to understand the social structure of the population, inform policy decisions related to family dynamics, plan the needs of programs with spousal benefits, analyze trends in regional marriage rates, and improve marketing campaigns based on life stages and household composition. This data is used in government policy planning, economic analysis, social and market research, and health-care planning. |
Educational Attainment
 | What is measured: Levels of education achieved by individuals in the regional population. How you use it: Educational Attainment categories help improve understanding of the overall regional education experience. This data is typically used to assess a country's economic potential, social development, workforce capabilities, and to inform policy decisions related to workforce training and social programs. Education data can also be used to assess the effectiveness of existing public education policies and employment training programs. |
Unemployed Population
 | What is measured: The number of individuals actively seeking employment who are currently unemployed in a region. How you use it: Unemployed Population counts help policymakers, researchers, and businesses identify patterns, target specific job-seeking groups with support programs, and make informed decisions about specific economic policies aimed at reducing unemployment. This data is particularly useful in areas like job training, education, and regional development, particularly when combined with other variables, such as age, gender, race, education level, and location. Regional unemployment data is used to identify trends and disparities, such as whether specific populations are disproportionately affected by unemployment. This data can inform the design of unemployment benefits, job training programs, and economic stimulus packages tailored to regional demographic needs. Unemployed Population data can also be used to perform labor market analysis, helping predict future market needs, trends, and challenges. |
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:
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:
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 like 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:
- Release notes (PDF)
- Variable list (CSV)
- Sample report (PDF)
- Demographic map layers
Advanced demographics sample questions and use cases
Germany's advanced demographics provide additional insight about this region for most data categories. You will find a range of detailed information about German regional population and population projections; annual birth and death rates; household income; age categories; households and lifestyles; housing and ownership status; industry and business data; nationality and immigration; retail purchasing power, turnover, and centrality; automobile availability; and commutes. See the Advanced demographics related links section below for the complete list of variables, release notes, and sample reports.
Some sample questions that could be answered using Germany's advanced demographics include the following:
- Where are the optimal locations to open new business establishments in Bavaria based on demographic trends and consumer profiles?
- How can labor force characteristics in Cologne inform recruitment decisions at my company?
- Can I use consumer behavior patterns in Stuttgart to tailor product offerings and marketing campaigns?
- Where is the greatest increase in population expected in the next ten years for a planned light rail project?
- How does age distribution vary between Berlin and Spreewald?
A selection of example use cases that may help you understand German advanced demographics include the following:
Employment - Commuters
 | What is measured: The regional commuters inbound and outbound, commuters per thousand, and measures that compare inbound to outbound commuters and daytime to nighttime regional population. How you use it: German population by commute to work data can be used by regional planning organizations and policymakers to enhance transportation systems, urban planning strategies, and commuter experiences across different regions in the country. This data is used to understand the potential implications for urban planning and transportation infrastructure development. For example, to plan more efficient public transportation routes, bike lanes, or car pool initiatives based on commuter behavior. |
Household by Age of Landlord or Tenant
| What is measured: Regional households based on specific landlord or tenant age categories, such as households with a landlord or tenant age 70 years and older. How you use it: German household by the age of the landlord or tenant data is used to understand housing trends, ownership patterns, and implications for real estate development and rental market strategies. For example, this data can be used to identify areas with a high concentration of properties owned by specific age groups, indicating potential investment opportunities or rental market trends. You can also use this data to understand the preferences of landlords and tenants across different age brackets, influencing property management strategies and rental pricing. |
Retail Centrality
 | What is measured: Retail turnover in a region compared to local retail purchasing power. If a region spends more than it accumulates, it has a lower retail centrality index than a region that accumulates more disposable income than it spends. A centrality index of 100 indicates a balance of retail turnover with purchasing power. This measure consists of an index, a per MM €, and a per capita €. How you use it: German retail centrality data is used to understand the distribution of retail activities, identify shopping hubs, and optimize retail marketing campaigns for different regions. This data can be used to collect information about the types of retail activities, foot traffic, and consumer preferences in different retail locations. You can also use this data to identify key retail hubs or shopping districts based on factors like consumer density, retail diversity, and accessibility. For areas with high centrality, you can use retail centrality data to identify opportunities for retail expansion and growth. This data can also be used to increase competitive advantage by helping businesses determine the best locations to position new stores in key shopping districts. |
Advanced demographics related links
Refer to the following content:
- Release notes (PDF)
- Variable list (CSV)
- Nexiga demographic methodology statement (PDF)
- Nexiga purchasing power methodology statement (PDF)
- Germany Household Summary sample report (PDF)
- Germany Business and Retail Centrality Summary sample report (PDF)
- Germany Population Summary sample report (PDF)
- Demographic map layers