Success.ai’s User Profiles Data for Nonprofit and NGO Leaders provides businesses, organizations, and researchers with comprehensive access to global leaders in the nonprofit and NGO sectors. With data sourced from over 700 million verified LinkedIn profiles, this dataset includes actionable insights and contact details for executives, program managers, administrators, and decision-makers. Whether your goal is to partner with nonprofits, support global causes, or conduct research into social impact, Success.ai ensures your outreach is backed by accurate, enriched, and continuously updated data.

Why Choose Success.ai’s User Profiles Data for Nonprofit and NGO Leaders? Comprehensive Professional Profiles

Access verified LinkedIn profiles of nonprofit leaders, NGO managers, program directors, grant writers, and administrative executives. AI-driven validation ensures 99% accuracy for efficient communication and minimized bounce rates. Global Coverage Across Nonprofit Sectors

Includes profiles from nonprofits, humanitarian organizations, environmental groups, social enterprises, and advocacy organizations. Covers key markets across North America, Europe, APAC, South America, and Africa for global reach. Continuously Updated Dataset

Reflects real-time professional updates, organizational changes, and emerging trends in the nonprofit landscape to keep your targeting relevant and effective. Tailored for Nonprofit Insights

Enriched profiles include work histories, organizational affiliations, areas of expertise, and social impact projects for deeper engagement opportunities. Data Highlights: 700M+ Verified LinkedIn Profiles: Access a vast network of nonprofit and NGO professionals worldwide. 100M+ Work Emails: Direct communication with executives, managers, and decision-makers in the nonprofit sector. Enriched Organizational Data: Gain insights into leadership structures, mission focuses, and operational scales. Industry-Specific Segmentation: Target nonprofits focused on healthcare, education, environmental sustainability, human rights, and more. Key Features of the Dataset: Nonprofit and NGO Leader Profiles

Identify and connect with executives, program managers, fundraisers, and policy directors in global nonprofit and NGO sectors. Engage with individuals who drive decision-making and operational strategies for impactful organizations. Detailed Organizational Insights

Leverage firmographic data, including organizational size, mission, regional activity, and funding sources, to align with specific nonprofit goals. Advanced Filters for Precision Targeting

Refine searches by region, mission type, role, or organizational focus for tailored outreach. Customize campaigns based on social impact priorities, such as climate action, gender equality, or economic development. AI-Driven Enrichment

Enhanced datasets provide actionable insights into professional accomplishments, partnerships, and leadership achievements for targeted engagement. Strategic Use Cases: Partnership Development and Outreach

Identify nonprofits and NGOs for collaboration on social impact projects, sponsorships, or grant distribution. Build relationships with decision-makers driving advocacy, fundraising, and community initiatives. Donor Engagement and Fundraising

Target nonprofit leaders responsible for managing fundraising campaigns and donor relationships. Tailor outreach efforts to align with specific causes and funding priorities. Research and Analysis

Analyze leadership trends, mission focuses, and regional nonprofit activities to inform program design and funding strategies. Use insights to evaluate the effectiveness of social impact initiatives and partnerships. Recruitment and Talent Acquisition

Target HR professionals and administrators seeking qualified staff, consultants, or volunteers for nonprofits and NGOs. Offer talent solutions for specialized roles in program management, advocacy, and administration. Why Choose Success.ai? Best Price Guarantee

Access industry-leading, verified User Profiles Data at unmatched pricing to ensure your campaigns are cost-effective and impactful. Seamless Integration

Easily integrate verified nonprofit data into your CRM or marketing platforms with APIs or downloadable formats. AI-Validated Accuracy

Rely on 99% accuracy to minimize wasted outreach efforts and maximize engagement outcomes. Customizable Solutions

Tailor datasets to focus on specific nonprofit types, geographical regions, or areas of social impact to meet your strategic objectives. Strategic APIs for Enhanced Campaigns: Data Enrichment API

Update your internal records with verified nonprofit leader profiles to enhance targeting and engagement. Lead Generation API

Automate lead generation for a consistent pipeline of nonprofit and NGO professionals, scaling your outreach efforts efficiently. Success.ai’s User Profiles Data for Nonprofit and NGO Leader...

The Global Trust dataset measures how much trust people around the world have in major institutions and social networks. It contains two data files, one with the raw survey data and one putting the raw data into percentages of trust in certain institutions. These can be analyzed in different ways. The data comes from surveys of over 119,088 people from 113 countries. Survey respondents were asked such things as “How much do you trust each of the following: other people in your neighborhood; your national government; scientists; journalists; doctors and nurses; people who work at non-governmental or non-profit organizations; healers? Do you trust them a lot, some, not much, or not at all?" The National Trust Codebook contains both the survey and the national rate codebook files, titled “Survey” and “Rate” respectively. Both files contain the same variables such as neighbors, government, and journalists, with the only difference being that “Survey” has id as a variable to account for the 119,088 unique responses. The Survey file has the raw data of all the 119,088 unique responses and both categorical and ordinal variables. It can be used to analyze how different countries feel about trust in different people or institutions as well as how those variables can relate to each other. The Rate file creates a percentage of how much people from each country trust certain communities or institutions and this can be used to analyze how different countries feel about certain things, this allows room to analyze each country with each other in a more clear way than the raw data. Both files are unique in the sense of the data being worldwide, it is a unique trait to be able to compare from different countries survey respondents that were asked the same questions with the same methodology, making comparison all the more easy. Another interesting element of this survey data is the number of responses per nation. There were, at minimum, 1000 responses gathered from each nation featured in the survey. The sample size allows for better than typical representation for each country.

This dataset is about books. It has 1 row and is filtered where the book is Dictionary of environment and development : people, places, ideas and organizations. It features 7 columns including author, publication date, language, and book publisher.

The Community Credit research project explores pathways for trusted collaboration between credit unions and the communities they serve. To understand the experiences of people historically underserved by the consumer financial services industry, we focused in particular on the lived experience of low-income residents in Southern California. As part of a larger, mixed-methods study, in 2022 we conducted 30 semi-structured interviews exploring people’s everyday financial practices and their attitudes toward consumer financial services providers. This data set contains the transcripts from the interviews after excluding any personally identifying data. All study materials and procedures were approved by the University of California, Irvine Office of Human Research Protections and the Institutional Review Board (protocol ID 20216839). This material is based upon work supported by the National Science Foundation under Grant No. 2137567. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Methods Interview participants were recruited through the project’s other data collection methods, including community listening sessions, photovoice workshops, and a large-scale survey. Participants were eligible to complete an interview if they live in Orange County or Los Angeles County, are older than 18, and have a combined household income of less than $100,000. Although the interviews are focused on participants’ individual experiences, some participants also speak to their experience working for local nonprofits involved in advocating for financially marginalized people. Interviews were conducted over the telephone or via the Zoom platform. Every interview began with obtaining informed consent and permission to record. The interviews followed a 10-question script (included in the Question Guide file), although the order of the questions and the depth in which each was discussed varied organically based on the flow of conversation and the degree of detail participants were comfortable with sharing. The average interview time was 54 minutes.

This dataset is about books. It has 1 row and is filtered where the book is Evaluation training : a resource for measuring the results and impact of training on people, departments and organizations. It features 7 columns including author, publication date, language, and book publisher.

This dataset includes five files. The Excel file is a dataset with authors and articles titles that grounded the research. The four PDF files are word trees for each research keyword as follow: "Organization", "Racism", "Black People", and "Racial Diversity". This dataset is from research about how organizations relate to black people over time and how to improve this relationship to benefit both. Scopus and Web of Science, two big and multidisciplinary databases, were chosen as the source articles for this study. These databases were also preferred because of the scientific community's trust, the number of quality documents indexed, and the conditions for building metrics from these. The data studied refers to ESG and Black people in the organization, and the analyzed data results from extracting, understanding, and analyzing manuscripts and relations of these two subjects over time.

This dataset is about book subjects. It has 3 rows and is filtered where the books is The leader on the couch : a clinical approach to changing people and organizations. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This dataset is about books. It has 2 rows and is filtered where the book is Edgewalkers : people and organizations that take risks, build bridges, and break new ground. It features 4 columns: author, book publisher, and BNB id.

This dataset contains a list of organizations funded under the Canada Summer Jobs programs during the year of 2019. Canada Summer Jobs is an initiative of the Youth Employment Strategy, which is the Government of Canada’s commitment to help young people between the ages of 15 and 30, particularly those facing barriers to employment, get the information and gain the skills, work experience and abilities they need to transition successfully into the labour market. The program provides wage subsidies to employers from not-for-profit organizations, the public-sector, and private sector organizations with 50 or fewer full-time employees, to create quality summer work experiences for young people aged 15 to 30 years.

This dataset contains a list of organizations funded under the Canada Summer Jobs programs during the year of 2019. Canada Summer Jobs is an initiative of the Youth Employment Strategy, which is the Government of Canada’s commitment to help young people between the ages of 15 and 30, particularly those facing barriers to employment, get the information and gain the skills, work experience and abilities they need to transition successfully into the labour market. The program provides wage subsidies to employers from not-for-profit organizations, the public-sector, and private sector organizations with 50 or fewer full-time employees, to create quality summer work experiences for young people aged 15 to 30 years.

The Employment Equity Act prescribes that this report cover the portions of the public service of Canada set out in Schedules I and IV of the Financial Administration Act. Seventy-three departments, agencies and commissions comprise the core public administration (CPA), for which the Treasury Board is the employer (see Table 1). The statistics in this report include only employees working for these organizations, which numbered 181,356 on March 31, 2014.

This report includes information on indeterminate employees, term employees of three months or more, and seasonal employees, with the exception of those seasonal employees who are on leave without pay at the end of March for each fiscal year. No information is reported on students, casual workers or employees on leave without pay, such as those on care and nurturing leave and educational leave.

Statistics in this document also exclude Governor in Council appointees, ministerial staff, federal judges and deputy ministers, who are also on the public service payroll. As required under the Employment Equity Act, annual reports to Parliament present information for the fiscal year beginning April 1 and ending March 31.

The statistics of separate employers, covered under Schedule V of the Financial Administration Act, are not included in this report. Under the Employment Equity Act, separate employers that have more than 100 employees (e.g., the Canada Revenue Agency and the Canadian Food Inspection Agency) are required to provide their reports to the Office of the Chief Human Resources Officer (OCHRO) of the Treasury Board of Canada Secretariat only for the purposes of tabling in Parliament at the same time as this report. To view their employment equity reports, readers should visit those organizations’ websites, or contact them directly.

Reports on employment equity in the Canadian Forces and with respect to members of the Royal Canadian Mounted Police are prepared by those organizations and are also tabled in Parliament at the same time as those of separate employers.

To assure the consistency of data presented in this report, OCHRO uses the incumbent file, which contains information on all employees for whom the Treasury Board is the employer, in accordance with Schedules I and IV of the Financial Administration Act. Since 2011–12, the executive category includes data on the LC Group (Law Management Occupational Group) in its total workforce, which will need to be taken into consideration when comparing data historically.

All tabulations, other than those for women, contain data obtained through self-identification. This data is provided voluntarily by employees and maintained separately and confidentially in the Employment Equity Data Bank by OCHRO, and where applicable, through the self-declaration of individuals applying to the public service through the Public Service Commission of Canada’s (PSC’s) Public Service Resourcing System. A reconciliation process is carried out each year by OCHRO, the PSC and the departments of the CPA to ensure that information derived from the Public Service Resourcing System, the Employment Equity Data Bank, and incumbent file harmonizes with the information from departmental sources.

The completeness and accuracy of employment equity data for the CPA depend on the willingness of employees to self-identify and on departments providing opportunities for them to do so. Employees, including those engaged as students or casual workers, are given an opportunity to provide this information when they are hired and during departmental self-identification surveys or other campaigns. Furthermore, they may complete a self-identification form, available from their departmental employment equity coordinator, at any time.