This study, designed and carried out by the "http://www.asarb.org/" Target="_blank">Association of Statisticians of American Religious Bodies (ASARB), compiled data on 372 religious bodies by county in the United States. Of these, the ASARB was able to gather data on congregations and adherents for 217 religious bodies and on congregations only for 155. Participating bodies included 354 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao, Zoroastrian, American Ethical Union, and National Spiritualist Association congregations, and counts of congregations and adherents from Baha'i, three Buddhist groupings, two Hindu groupings, four Jewish groupings, and Muslims. The 372 groups reported a total of 356,642 congregations with 161,224,088 adherents, comprising 48.6 percent of the total U.S. population of 331,449,281. Membership totals were estimated for some religious groups.

In January 2024, the ARDA added 21 religious tradition (RELTRAD) variables to this dataset. These variables start at variable #12 (TOTCNG_2020). Categories were assigned based on pages 88-94 in the original "https://www.usreligioncensus.org/index.php/node/1638" Target="_blank">2020 U.S. Religion Census Report.

Visit the "https://www.thearda.com/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data sources.

This study, designed and completed by the Association of Statisticians of American Religious Bodies (ASARB), represents statistics for 149 religious bodies on the number of congregations within each county of the United States. Where available, also included are actual membership (as defined by the religious body) and total adherents figures. Participants included 149 Christian denominations, associations, or communions (including Latter-day Saints and Unitarian/Universalist groups); two specially defined groups of independent Christian churches; Jewish and Islamic totals; and counts of temples for six Eastern religions.

It is important to understand the methodology producing these data and its limitations. While these data contain membership data for many religious groups in the United States, including most of the larger groups, they do not include every group. It is recommended that users read the notes below. Users may also want to refer to a paper by Roger Finke and Christopher P. Scheitle that explains the "adjusted" adherence rates included in the file.

Visit the "/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data.

Anti-Jewish attacks were the most common form of anti-religious group hate crimes in the United States in 2023, with ***** cases. Anti-Islamic hate crimes were the second most common anti-religious hate crimes in that year, with *** incidents.

In 2023, **** percent of Americans were unaffiliated with any religion. A further **** percent of Americans were White evangelical Protestants, and an additional **** percent were White mainline Protestants. Religious trends in the United States Although the United States is still home to the largest number of Christians worldwide, the nation has started to reflect a more diverse religious landscape in recent years. Americans now report a wide range of religious beliefs and backgrounds, in addition to an increasing number of people who are choosing to identify with no religion at all. Studies suggest that many Americans have left their previous religion to instead identify as atheist, agnostic, or nothing in particular, with many reasoning that they stopped believing in the religion's teachings, that they didn't approve of negative teachings or treatment of LGBTQ+ people, or that their family was never that religious growing up. Christian controversies Over the last few years, controversies linked to Christian denominations have plagued the nation, including reports of child sexual abuse by the Catholic Church, the Church of Jesus Christ of Latter-day Saints, and the Southern Baptist Convention. Christian churches have also been accused of supporting discriminatory actions against LGBTQ+ people and people belonging to other religious groups. In addition, there have been increasing concerns about Christian nationalism, the political ideology that asserts that America was founded to be a Christian nation. Although the majority of Americans still think that declaring the United States a Christian nation would go against the U.S. Constitution, studies found that most Republicans would be in favor of this change.

About this dataset

Context

The dataset tabulates the population of Faith by race. It includes the population of Faith across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Faith across relevant racial categories.

Key observations

The percent distribution of Faith population by race (across all racial categories recognized by the U.S. Census Bureau): 95.72% are white, 2.14% are Black or African American and 2.14% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Faith
• Population: The population of the racial category (excluding ethnicity) in the Faith is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Faith total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Faith Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Faith. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Faith population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 89.36% of the total residents in Faith. Notably, the median household income for White households is $151,250. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $151,250.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Faith.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Faith median household income by race. You can refer the same here

DRAKO is a Mobile Location Audience Targeting provider with a programmatic trading desk specialising in geolocation analytics and programmatic advertising. Through our customised approach, we offer business and consumer insights as well as addressable audiences for advertising.

Mobile Location Data can be meaningfully transformed into Audience Targeting when used in conjunction with other dataset. Our expansive POI Data allows us to segment users by visitation to major brands and retailers as well as categorizes them into syndicated segments. Beyond POI visits, our proprietary Home Location Model determines residents of geographic areas such as Designated Market Areas, Counties, or States. Relatedly, our Home Location Model also fuels our Geodemographic Census Data segments as we are able to determine residents of the smallest census units. Additionally, we also have audiences of: ticketed event and venue visitors; survey data; and retail data.

All of our Audience Targeting is 100% deterministic in that it only includes high-quality, real visits to locations as defined by a POIs satellite imagery buildings contour. We never use a radius when building an audience unless requested. We have a horizontal accuracy of 5m.

Additionally, we can always cross reference your audience targeting with our syndicated segments:

Overview of our Syndicated Audience Data Segments: - Brand/POI segments (specific named stores and locations) - Categories (behavioural segments - revealed habits) - Census demographic segments (HH income, race, religion, age, family structure, language, etc.,) - Events segments (ticketed live events, conferences, and seminars) - Resident segments (State/province, CMAs, DMAs, city, county, sub-county) - Political segments (Canadian Federal and Provincial, US Congressional Upper and Lower House, US States, City elections, etc.,) - Survey Data (Psychosocial/Demographic survey data) - Retail Data (Receipt/transaction data)

All of our syndicated segments are customizable. That means you can limit them to people within a certain geography, remove employees, include only the most frequent visitors, define your own custom lookback, or extend our audiences using our Home, Work, and Social Extensions.

In addition to our syndicated segments, we’re also able to run custom queries return to you all the Mobile Ad IDs (MAIDs) seen at in a specific location (address; latitude and longitude; or WKT84 Polygon) or in your defined geographic area of interest (political districts, DMAs, Zip Codes, etc.,)

Beyond just returning all the MAIDs seen within a geofence, we are also able to offer additional customizable advantages: - Average precision between 5 and 15 meters - CRM list activation + extension - Extend beyond Mobile Location Data (MAIDs) with our device graph - Filter by frequency of visitations - Home and Work targeting (retrieve only employees or residents of an address) - Home extensions (devices that reside in the same dwelling from your seed geofence) - Rooftop level address geofencing precision (no radius used EVER unless user specified) - Social extensions (devices in the same social circle as users in your seed geofence) - Turn analytics into addressable audiences - Work extensions (coworkers of users in your seed geofence)

Data Compliance: All of our Audience Targeting Data is fully CCPA compliant and 100% sourced from SDKs (Software Development Kits), the most reliable and consistent mobile data stream with end user consent available with only a 4-5 day delay. This means that our location and device ID data comes from partnerships with over 1,500+ mobile apps. This data comes with an associated location which is how we are able to segment using geofences.

Data Quality: In addition to partnering with trusted SDKs, DRAKO has additional screening methods to ensure that our mobile location data is consistent and reliable. This includes data harmonization and quality scoring from all of our partners in order to disregard MAIDs with a low quality score.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Faith, SD, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 8,424, while the mean income for the highest quintile (20% of households with the highest income) is 137,480. This indicates that the top earners earn 16 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 212,438, which is 154.52% higher compared to the highest quintile, and 2521.82% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Faith median household income. You can refer the same here

About this dataset

Context

The dataset presents median household incomes for various household sizes in Faith, NC, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Faith did not include 6, or 7-person households. Across the different household sizes in Faith the mean income is $135,309, and the standard deviation is $65,494. The coefficient of variation (CV) is 48.40%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $34,049. It then further increased to $195,240 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/faith-nc-median-household-income-by-household-size.jpeg" alt="Faith, NC median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Faith median household income. You can refer the same here

The New Immigrant Survey (NIS) was a nationally representative, longitudinal study of new legal immigrants to the United States and their children. The sampling frame was based on the electronic administrative records compiled for new legal permanent residents (LPRs) by the U.S. government (via, formerly, the U.S. Immigration and Naturalization Service (INS) and now its successor agencies, the U.S. Citizenship and Immigration Services (USCIS) and the Office of Immigration Statistics (OIS)). The sample was drawn from new legal immigrants during May through November of 2003. The geographic sampling design took advantage of the natural clustering of immigrants. It included all top 85 Metropolitan Statistical Areas (MSAs) and all top 38 counties, plus a random sample of MSAs and counties. The baseline survey (ICPSR 38031) was conducted from June 2003 to June 2004 and yielded data on: 8,573 Adult Sample respondents, 810 sponsor-parents of the Sampled Child, 4,915 spouses, and 1,072 children aged 8-12. This study contains the follow-up interview, conducted from June 2007 to October 2009, and yielded data on: 3,902 Adult Sample respondents, 351 sponsor-parents of the Sampled Child, 1,771 spouses, and 41 now-adult main children. Interviews were conducted in the respondents' language of choice. Round 2 instruments were designed to track changes from the baseline and also included new questions. As with the Round 1 questionnaire, questions that were used in social-demographic-migration surveys around the world as well as the major U.S. longitudinal surveys were reviewed in order to achieve comparability. The NIS content includes the following information: demographics, health and insurance, migration history, living conditions, transfers, employment history, income, assets, social networks, religion, housing environment, and child assessment tests.

This study, designed and carried out by the Association of Statisticians of American Religious Bodies (ASARB), compiled data on the number of congregations and adherents for 236 religious groups in each county of the United States. Participants included 217 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao and National Spiritualist Association congregations, and counts of congregations and adherents from Bahá'ís, three Buddhist groupings, four Hindu groupings, four Jewish groupings, Muslims and Zoroastrians. The 236 groups reported a total of 344,894 congregations with 150,686,156 adherents, comprising 48.8 percent of the total U.S. population of 308,745,538 in 2010.

Visit the "/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data.

The National Congregations Study (NCS) is a national survey effort to gather information about America's congregations. The first wave of the NCS took place in 1998, and the study was repeated in 2006-07, 2012, and 2018-19. The NCS tracks continuity and change among American congregations, and each NCS wave also explores new subjects. With information from 5,333 congregations collected over a span of more than 20 years, the NCS helps us better understand many aspects of congregational life in the United States, and how congregations are changing in the 21st century. The NCS contributes to knowledge about American religion by collecting information about a wide range of congregations' characteristics and activities at different points in time. In all four waves, the NCS was conducted in conjunction with the General Social Survey (GSS). The 1998, 2006, 2012, and 2018 waves of the GSS asked respondents who attend religious services to name their congregation, thus generating a nationally representative sample of religious congregations. Researchers then located these congregations. In 2006, the sample included re-interviews of a subset of congregations that participated in 1998, and in 2018-19, the sample included re-interviews of a subset of congregations that participated in 2012. A key informant at each congregation - a minister, priest, rabbi, or other staff person or leader - provided each congregation's information via a one-hour interview conducted either over the phone or in-person. The survey gathered information on many topics, including the congregation's leadership, social composition, structure, activities, and programming. The NCS gathers information about worship, programs, staffing, community activities, demographics, funding, and many other characteristics of American congregations. Respondents of the NCS survey were asked to describe the worship service and programs sponsored by the congregation other than the main worship services, including religious education classes, musical groups, and recreational programs. Informants described the type of building in which the congregation met, whether it belonged to the congregation, and whether visitors came just to view the building's architecture or artwork. Congregations were geocoded, and selected census variables are included in this study.

Nearly all research on the political impact of Americans’ religious and secular orientations assumes that such orientations are exogenous to politics. Using multi-wave panel and experimental data, we find that religious and secular orientations are endogenous to political orientations. In other words, religion and secularism are a consequence as well as a cause of politics. In showing this, we make three major contributions. First, we conceptualize and measure secular orientations in a new way—not just as the absence of religion, but as an affirmative secular identity and positive commitment to secular principles. Second, our panel and experimental data allow for the most definitive test to date of whether political orientations exert a causal effect on religious and secular orientations. Third, we isolate the conditions under which politics affects religious-secular perspectives, thus identifying the mechanism that underlies political orientations.

This dataset is the centerpiece of Pew Research Center's 2014 Religious Landscape Study, a nationally representative telephone survey conducted June 4-Sept. 30, 2014, among a sample of 35,071 U.S. adults. Approximately 60 percent of the interviews were conducted with respondents reached on cellphones (n=21,160) and 40 percent were completed on landlines (n=13,911). A minimum of 300 interviews were conducted in every state and the District of Columbia. Interviewing was conducted in English and Spanish. The survey is estimated to cover 97 percent of the non-institutionalized U.S. adult population; 3 percent of U.S. adults are not reachable by telephone or do not speak English or Spanish well enough to participate in the survey. No adjustments have been made to the data to attempt to account for the small amount of non-coverage.

The size of the national sample is unusually large for a religion survey. There are two main reasons for this. First, the large sample size makes it possible to estimate the religious composition of the U.S. with a high degree of precision. After taking into account the survey's design effect (based on the sample design and survey weights), the margin of error for the results based on the full sample is +/- 0.6 percentage points.

Second, the large sample size makes it possible to describe the characteristics of a wide variety of religious groups, including relatively small groups that cannot be analyzed using data from smaller surveys. With more than 35,000 respondents in total, the Religious Landscape Study includes interviews with roughly 350 in religious groups that account for just 1 percent of the U.S. population, and with 100 or more people in religious groups that are as small as three-tenths of 1 percent of the overall population. For instance, the study includes interviews with 245 Jehovah's Witnesses, a group that accounts for less than 1 percent of the U.S. population and is typically represented by only a few dozen respondents in smaller surveys.

The role of religion and politics in the responses to the coronavirus pandemic raises the question of their influence on the risk of other diseases. This study focuses on age-adjusted death rates of cancer, heart disease, and infant mortality per 1000 live births before the pandemic (2018-2019) and COVID-19 in 2020-2021. Eight hypothesized predictors of health effects were analyzed by examining their correlation to age-adjusted death rates among U.S. states, percentage who pray once or more daily, Republican influence on state health policies as indicated by the percentage vote for Trump in 2016, percent of household incomes below poverty, median family income divided by a cost-of-living index, the Gini income inequality index, urban concentration of the population, physicians per capita, and public health expenditures per capita. Since prayer for divine intervention is common to otherwise diverse religious beliefs and practices, the percentage of people claiming to pray daily in each state was used to indicate potential religious influence. All of the death rates were higher in states where more people claimed to pray daily, and where Trump received a larger percentage of the vote. Except for COVID-19, the death rates were consistently lower in states with higher public health expenditures per capita. Only COVID-19 was correlated to physicians per capita, lower where there were more physicians. Corrected statistically for the other factors, income per cost of living explains no variance. Heart disease and COVID-19 death rates were higher in areas with more income inequality. All of the disease rates were in correlation with more rural populations. Correlation of daily prayer with smoking cigarettes, and neglect of public health recommendations for fruit and vegetable consumption and COVID-19 vaccination suggests that prayer may be substituted for preventive practices.

Abstract (en): This study contains biographical data on the 92 Supreme Court justices appointed between 1789 and 1958. Potter C. Stewart, appointed in 1958, was the last justice to be included in the study. The study recorded personal data such as place of birth, education, political as well as nonpolitical occupation, legal and judicial experience, age at the time of Supreme Court appointment, ethnic background, and religious affiliation. Other background information on each justice includes party identification, reputation as a frequent dissenter, and the state from which he was appointed. Various aspects of family background such as social and economic status, paternal occupation, and familial traditions of judicial service were also explored. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Checked for undocumented or out-of-range codes.. United States Supreme Court justices appointed between 1789 and 1958. The sample in this study consists of the entire population.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for religion new testament in the U.S.

Snapshot img

Church Management Software Market Size 2025-2029

The church management software market size is forecast to increase by USD 418.5 million, at a CAGR of 8.9% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing digital adoption by churches. This shift towards technology is enabling institutions to streamline their administrative processes, manage membership databases, and enhance communication with their congregations more effectively. Additionally, the introduction of new solutions continues to expand the market, offering features such as online donation platforms, event management tools, and mobile applications. However, this market is not without challenges. Data security and privacy concerns remain a major obstacle, as churches handle sensitive information related to their members.
Ensuring robust security measures and adhering to data protection regulations are essential for market players to build trust and maintain a strong customer base. Furthermore, the market is becoming increasingly competitive, with new entrants continuously emerging. Companies must differentiate themselves by offering innovative features, exceptional customer service, and competitive pricing to attract and retain clients.

What will be the Size of the Church Management Software Market during the forecast period?

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The market continues to evolve, with dynamic applications across various sectors. Seamless integration of entities such as online stores, children's ministries, mobile apps, social media, membership directories, online services, large churches, senior ministries, compliance regulations, communication channels, church websites, and more, is a constant requirement. The market's ongoing unfolding is marked by the development of intuitive designs, fundraising tools, online giving, communication tools, and media management. These features cater to the diverse needs of churches, enabling effective outreach programs and pastoral care. Cloud-based software solutions offer remote access, ensuring flexibility for churches of all sizes.

Data security and privacy are paramount, with API integrations and reporting and analytics tools providing valuable insights. virtual events and ministry scheduling streamline operations, while donor management, attendance tracking, email marketing, and volunteer management enhance engagement and communication. The market's evolution is driven by the need for user-friendly interfaces, calendar management, worship planning, and sermon management. Compliance regulations are addressed through robust features, ensuring adherence to industry standards. The continuous integration of technology into church administration enhances efficiency and effectiveness, allowing churches to focus on their core mission.

How is this Church Management Software Industry segmented?

The church management software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  On-premises
  Cloud-based


Application

  Mobile terminals
  PCs


Consumer

  Medium-sized churches
  Small churches
  Large churches


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    The Netherlands
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.

On-premises church management software is a popular choice for religious organizations seeking greater control over their data and software. Unlike cloud-based solutions, on-premises systems are installed and managed on the church's internal servers and IT infrastructure. This setup allows churches to manage sensitive information, such as financial records, membership details, and communication logs, with greater security and customization. On-premises church management software offers extensive customization options, enabling churches to tailor workflows, add unique features, and integrate the software with existing in-house systems. Churches can also customize the user interface to better suit their specific needs, ensuring an intuitive design that streamlines administrative tasks.

Key functionalities of on-premises ChMS include financial accounting, task management, fundraising tools, online giving, communication tools, youth ministries, data security, church administration, pastoral care, remote access, outreach programs, and more. These features cater to various aspects of church operations, from managing volunteer schedules and membership directories to planning worship services and communicating with congregants. On-premises ChMS is particularly beneficial for non-den

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: Not available in microdata sample - Vacant units: Not available in microdata sample - Households: Not available in microdata sample - Individuals: Yes - Group quarters: Microdata sample includes individuals in group quarters, but are not identified - Special populations: People in transit included in microdata sample

UNIT DESCRIPTIONS: - Dwellings: Separated space with independent access that serves as a human lodging - Group quarters: Group of persons who share a common roof and food because of work, health, religion, etc.

Universe

Population census included people in territories, sailors, diplomats and their families. The indigenous population residing in remote areas was not enumerated.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Centro Latinoamericano de Demografia (CELADE)

SAMPLE DESIGN: Systematic sample of every 50th individual after a random start. Drawn by DANE from the original census enumeration forms.

SAMPLE UNIT: Individual

SAMPLE FRACTION: 2%

SAMPLE SIZE (person records): 349,652

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form was used for the entire country. It requested information about buildings, dwellings, households and individuals.

Response rate

COVERAGE: 98.2%

About this dataset

Context

The dataset tabulates the population of Faith by race. It includes the population of Faith across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Faith across relevant racial categories.

Key observations

The percent distribution of Faith population by race (across all racial categories recognized by the U.S. Census Bureau): 89.36% are white, 2.39% are Black or African American, 7.34% are Asian and 0.92% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Faith
• Population: The population of the racial category (excluding ethnicity) in the Faith is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Faith total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Faith Population by Race & Ethnicity. You can refer the same here