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TwitterQuick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.
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TwitterSuccess.ai’s Agricultural Data provides unparalleled access to verified profiles of agriculture and farming leaders worldwide. Sourced from over 700 million LinkedIn profiles, this dataset includes actionable insights and contact details for professionals shaping the global agricultural landscape. Whether your objective is to market agricultural products, establish partnerships, or analyze industry trends, Success.ai ensures your outreach is powered by accurate, enriched, and continuously updated data.
Why Choose Success.ai’s Agricultural Data? Comprehensive Professional Profiles
Access verified LinkedIn profiles of farm owners, agricultural consultants, supply chain managers, agribusiness executives, and industry leaders. AI-validated data ensures 99% accuracy, minimizing wasted outreach and improving communication efficiency. Global Coverage Across Agricultural Sectors
Includes professionals from crop farming, livestock production, agricultural technology, and sustainable farming practices. Covers key regions such as North America, Europe, APAC, South America, and Africa. Continuously Updated Dataset
Real-time updates reflect role changes, organizational shifts, and emerging trends in agriculture and farming. Tailored for Agricultural Insights
Enriched profiles include professional histories, areas of specialization, and industry affiliations for deeper audience understanding. Data Highlights: 700M+ Verified LinkedIn Profiles: Gain access to a global network of agricultural and farming professionals. 100M+ Work Emails: Communicate directly with decision-makers in agribusiness and farming. Enriched Professional Histories: Understand career trajectories, expertise, and organizational affiliations. Industry-Specific Segmentation: Target professionals in crop farming, agtech, and sustainable agriculture with precision filters. Key Features of the Dataset: Agriculture and Farming Professional Profiles
Identify and connect with farm operators, agricultural consultants, supply chain managers, and agribusiness leaders. Engage with professionals responsible for farm management, equipment procurement, and sustainable farming initiatives. Detailed Firmographic Data
Leverage insights into farm sizes, crop or livestock focus, geographic distribution, and operational scales. Customize outreach to align with specific farming practices or market needs. Advanced Filters for Precision Targeting
Refine searches by region, type of agriculture (crop farming, livestock, horticulture), or years of experience. Customize campaigns to address unique challenges such as climate adaptation or supply chain optimization. AI-Driven Enrichment
Enhanced datasets deliver actionable data for personalized campaigns, highlighting certifications, achievements, and key projects. Strategic Use Cases: Marketing Agricultural Products and Services
Promote farm equipment, crop protection solutions, or livestock management tools to decision-makers in agriculture. Engage with professionals seeking innovative solutions to enhance productivity and sustainability. Collaboration and Partnerships
Identify agricultural leaders for collaborations on sustainability programs, research projects, or community initiatives. Build partnerships with agribusinesses, cooperatives, or government bodies driving agricultural development. Market Research and Industry Analysis
Analyze trends in crop yields, livestock production, and agricultural technology adoption. Use insights to refine product development and marketing strategies tailored to evolving industry needs. Recruitment and Talent Acquisition
Target HR professionals and agricultural firms seeking skilled farm managers, agronomists, or agtech specialists. Support hiring for roles requiring agricultural expertise and leadership. Why Choose Success.ai? Best Price Guarantee
Access industry-leading Agricultural Data at the most competitive pricing, ensuring cost-effective campaigns and strategies. Seamless Integration
Easily integrate verified agricultural data into CRMs, recruitment platforms, or marketing systems using APIs or downloadable formats. AI-Validated Accuracy
Depend on 99% accurate data to minimize wasted outreach and maximize engagement outcomes. Customizable Solutions
Tailor datasets to specific agricultural segments, regions, or areas of focus to meet your strategic objectives. Strategic APIs for Enhanced Campaigns: Data Enrichment API
Enhance existing records with verified agricultural profiles to refine targeting and engagement. Lead Generation API
Automate lead generation for a consistent pipeline of qualified professionals in the agriculture sector, scaling your outreach efficiently. Success.ai’s Agricultural Data empowers you to connect with the leaders and innovators transforming global agriculture. With verified contact details, enriched professional profiles, and global reach, your marketing, partn...
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TwitterThe Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports broken down by agricultural and nonagricultural commodities. The USDA endpoint in the Census data API provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.
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TwitterNMCDC Copy of Living Atlas map. Source: https://www.arcgis.com/home/item.html?id=23ab8028f1784de4b0810104cd5d1c8fIllustration by Brian BrenemanThis layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2013-2017ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 7, 2018National Figures: American Fact FinderThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This dataset is updated automatically when the most current vintage of ACS data is released each year. The service contains the ACS data as of the current vintage listed. Tabular data is updated annually with the Census Bureau's release schedule. This may alter data values, fields, and boundaries. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.
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TwitterYourharvest Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterSuccess.ai’s Agriculture Dataset for Europe provides verified contact and company data across the entire agricultural value chain—from farm operators and equipment manufacturers to agri-food processors and distributors. Covering Western, Central, and Eastern Europe, the dataset is tailored for companies selling software, machinery, services, or conducting research into the agritech space.
It includes full company profiles, contact info for key stakeholders, and LinkedIn URLs for outreach, enrichment, and analytics.
Why Use Success.ai for Agricultural Data?
- Pan-European Coverage: France, Germany, Poland, Netherlands, Spain, and more.
- Precision Role Targeting: Find Directors, Procurement Heads, Farm Managers, and Tech Leads.
- Updated & Verified: 99% accuracy on contacts and firms, GDPR-compliant.
Data Points Include:
- Company name, sector (e.g. farming, processing, logistics)
- Contact name, job title, email, phone
- Company size, ownership, location
- LinkedIn URL (when available)
- Operational focus (e.g. crop, dairy, tech, distribution)
Use Cases:
- AgTech Product Sales
- Supply Chain Development
- Investment Research & Market Mapping
- Event Promotion to Agribusiness Leaders
- Precision Targeting of Farmers, Cooperatives, and Exporters
Industries Served:
- Agribusiness
- Food Production
- Farming Equipment
- Agricultural Software
- Sustainability & Climate Tech
Why Success.ai?
- Best Price Guarantee
- Wide Coverage + Deep Filtering
- White-Glove Support for Custom Lists
- API & Flatfile Options
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TwitterThe Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date exports broken down by agricultural and nonagricultural commodities. The USDA endpoint in the Census data API provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.
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TwitterSager Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterOmni Logistics Dba Ag World Trans Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterInbra Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterPlatit Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterIkea Suppy Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterKisling Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterGelita Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterDelipet Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterPresstrade Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterPurolite Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterSonova Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterMinn Dak Ag Llc Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterGeolam Ag Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
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TwitterQuick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.