Agricultural Data Analytics Market
Agricultural Data Analytics Market Forecasts to 2032 – Global Analysis By Component (Solutions and Services), Deployment Mode (Cloud-based, and On-Premises), Farm Size, Technology, Application, and By Geography
According to Stratistics MRC, the Global Agricultural Data Analytics Market is accounted for $7.5 billion in 2025 and is expected to reach $20.6 billion by 2032 growing at a CAGR of 15.6% during the forecast period. The agricultural data analytics market leverages big data, IoT devices, AI, and predictive analytics to optimize farming practices and decision-making. By analyzing weather patterns, soil health, crop performance, and supply chain metrics, farmers can achieve precision agriculture, higher yields, and reduced resource wastage. Increasing adoption of digital farming solutions, government initiatives for smart agriculture, and rising demand for sustainable practices are driving growth. The market is becoming crucial for modern agriculture, enabling actionable insights, improved productivity, and risk management across the farming ecosystem globally.
Market Dynamics:
Driver:
Adoption of Precision Farming
Precision agriculture has moved beyond pilot projects into mainstream adoption as farmers seek higher yields and lower input costs. By combining satellite and drone imagery with in-field sensors and machine learning, growers can apply water, fertilizer, and crop protection only where needed, improving resource efficiency and margins. Additionally, agronomic models and analytics platforms translate raw data into clear, actionable recommendations for planting, irrigation scheduling, and harvest timing. These practical benefits, paired with service models that lower technical barriers, are driving rapid uptake across commercial farms and progressive smaller operations and supporting long-term sustainability aims globally.
Restraint:
Limited Technological Infrastructure in Developing Regions
Poor broadband connectivity, unreliable power, and a shortage of local technical skills make it difficult to deploy sensors, edge devices, and cloud-based platforms at scale. Moreover, fragmented landholdings and informal data practices reduce the commercial incentive for vendors to build tailored solutions. Additionally, high upfront costs and limited financing options for smallholders slow adoption. Addressing these gaps requires coordinated public-private investment, training programs, and low-cost technology adaptations. Policy support and rural connectivity projects can bridge divides and accelerate adoption for smallholders.
Opportunity:
Development of Affordable Analytics Solutions
By designing low-cost sensors, simplified user interfaces, and subscription pricing, vendors can serve resource-constrained farms while maintaining viable business models. Furthermore, open data standards and modular platforms lower integration costs and enable local service providers to tailor offerings. Public subsidy programs and blended financing can de-risk initial purchases, and partnerships with cooperatives and input suppliers create distribution channels. It can democratize insights, raise incomes, and strengthen farm-level resilience locally.
Threat:
Cybersecurity Risks
Cybersecurity risks pose a meaningful threat to agricultural data analytics adoption and trust. Farms increasingly rely on connected sensors, telematics, and cloud platforms that collect sensitive operational and commercial data; breaches or manipulation could disrupt operations or expose competitive information. Additionally, weak security in third-party devices and limited awareness among smallholders increase vulnerability. Moreover, regulatory scrutiny and potential liability for data misuse create commercial uncertainty.
Covid-19 Impact:
The COVID-19 pandemic accelerated interest in digital agricultural tools by exposing vulnerabilities in labor supply chains and distribution. Remote monitoring and analytics enabled some operations to maintain productivity when movement was restricted, and buyers increasingly demanded traceability and supply-chain visibility. However, interrupted capital flows and project delays slowed deployments, especially among smaller farms. Overall, the crisis both highlighted the value of analytics and created short-term funding and implementation challenges. Recovery since 2021 supported renewed investment.
The solutions (software platforms) segment is expected to be the largest during the forecast period
The solutions (software platforms) segment is expected to account for the largest market share during the forecast period as platforms support multiple use cases crop health monitoring, yield forecasting, input optimization, and compliance reporting they attract broad customer segments including growers, advisors, and agribusinesses. Additionally, subscription models generate steady revenue streams for vendors and fund continuous improvement, while APIs and partner ecosystems increase stickiness. Interoperability with equipment manufacturers and input suppliers further boosts platform value, making software solutions the natural focal point for investments and market expansion and simplify regulatory compliance workflows.
The small and medium-sized farms segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the small and medium-sized farms segment is predicted to witness the highest growth rate These farms can rapidly adopt sensor bundles, mobile advisory services, and lightweight dashboards without extensive IT investments. Moreover, targeted financing products and donor-supported digital agriculture programs lower acquisition costs, while peer-to-peer knowledge sharing spreads successful practices. Manufacturers of compact machinery integrate telematics that feed into analytics, creating immediate value. As a result, these combined enablers propel the segment's growth ahead of large-farm transformations and attract focused regional investment from investors.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share due to well-established precision-agriculture ecosystems, high mechanization, and extensive farm consolidation that favor analytics deployment. Large commercial farms and agribusinesses have the capital and scale to invest in sensors, telematics and platform subscriptions, while strong broadband coverage and cloud infrastructure enable reliable services. Additionally, active venture investment, OEM partnerships, and mature dealer networks accelerate commercialization. Regulatory drivers for traceability and sustainability reporting further increase demand for analytics solutions. Together, these structural factors sustain North America's dominant position during the forecast period.
Region with highest CAGR:
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR because technological innovation and business model evolution continue to unlock new customer segments. Cloud services, edge computing, and advanced analytics make it economically viable for medium and smaller operations to adopt solutions. Growth is fueled by investments in agtech startups, expanding telematics in mid-sized machinery, and increasing demand for sustainability and carbon accounting. Furthermore, expanding value-added services crop insurance analytics and precision input marketplaces create fresh revenue streams, driving rapid year-over-year market expansion.
Key players in the market
Some of the key players in Agricultural Data Analytics Market include Deere & Company, Trimble Inc., Bayer AG, IBM Corporation, SAP SE, AGCO Corporation, Oracle Corporation, Microsoft Corporation, Accenture plc, Farmers Edge Inc., CropX Technologies, Taranis, Iteris, Inc., PrecisionHawk, Inc., Agrivi Ltd., SAS Institute Inc., Geosys SAS, Proagrica Ltd., and Conservis Corporation.
Key Developments:
In August 2025, Deere announced a partnership with ag-tech incubator The Reservoir, aiming to accelerate adoption of new precision/analytics solutions in specialty crops. Under the agreement, Deere becomes the exclusive OEM partner for Reservoir’s network, giving it early access to newly developed technologies.
In May 2025, John Deere announced the acquisition of Sentera, a leading provider of remote imagery solutions for agriculture headquartered in St. Paul, Minnesota. This acquisition will advance the capabilities of John Deere’s existing technology offerings, providing farmers and ag service providers with a more comprehensive set of tools to generate and use data to make decisions that improve farm profitability, efficiency, and sustainability.
In January 2025, Deere unveiled new autonomous tractors, a dump truck, and a battery-electric commercial mower at CES 2025, equipping them with advanced computer vision, AI, and autonomy features.
Components Covered:
• Solutions (Software Platforms)
• Services
Deployment Modes Covered:
• Cloud-based
• On-Premises
Farm Sizes Covered:
• Large Farms
• Small and Medium-Sized Farms
Technologies Covered:
• Core Technologies
• Enabling Technologies
Applications Covered:
• Farm Analytics
• Livestock Analytics
• Aquaculture Analytics
• Greenhouses & Indoor Farming Analytics
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Technology Analysis
3.7 Application Analysis
3.8 Emerging Markets
3.9 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Agricultural Data Analytics Market, By Component
5.1 Introduction
5.2 Solutions (Software Platforms)
5.2.1 Farm Management Software (FMS)
5.2.2 Yield Monitoring and Forecasting Solutions
5.2.3 Inventory Management Solutions
5.2.4 Supply Chain and Traceability Suites
5.3 Services
5.3.1 Managed Services
5.3.2 Professional Services
6 Global Agricultural Data Analytics Market, By Deployment Mode
6.1 Introduction
6.2 Cloud-based
6.3 On-Premises
7 Global Agricultural Data Analytics Market, By Farm Size
7.1 Introduction
7.2 Large Farms
7.3 Small and Medium-Sized Farms
8 Global Agricultural Data Analytics Market, By Technology
8.1 Introduction
8.2 Core Technologies
8.2.1 Predictive Analytics
8.2.2 Prescriptive Analytics
8.2.3 Descriptive Analytics
8.3 Enabling Technologies
8.3.1 Big Data & IoT (Internet of Things)
8.3.2 Artificial Intelligence (AI) & Machine Learning (ML)
8.3.3 Remote Sensing & Imagery
8.3.4 Geographic Information Systems (GIS)
9 Global Agricultural Data Analytics Market, By Application
9.1 Introduction
9.2 Farm Analytics
9.2.1 Yield Monitoring
9.2.2 Crop Health Monitoring
9.2.3 Irrigation Management
9.2.4 Field Mapping
9.2.5 Weather Tracking & Forecasting
9.3 Livestock Analytics
9.3.1 Health & Behavior Monitoring
9.3.2 Milk Harvesting Management
9.3.3 Feeding Management
9.4 Aquaculture Analytics
9.5 Greenhouses & Indoor Farming Analytics
10 Global Agricultural Data Analytics Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 Italy
10.3.4 France
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 Japan
10.4.2 China
10.4.3 India
10.4.4 Australia
10.4.5 New Zealand
10.4.6 South Korea
10.4.7 Rest of Asia Pacific
10.5 South America
10.5.1 Argentina
10.5.2 Brazil
10.5.3 Chile
10.5.4 Rest of South America
10.6 Middle East & Africa
10.6.1 Saudi Arabia
10.6.2 UAE
10.6.3 Qatar
10.6.4 South Africa
10.6.5 Rest of Middle East & Africa
11 Key Developments
11.1 Agreements, Partnerships, Collaborations and Joint Ventures
11.2 Acquisitions & Mergers
11.3 New Product Launch
11.4 Expansions
11.5 Other Key Strategies
12 Company Profiling
12.1 Deere & Company
12.2 Trimble Inc.
12.3 Bayer AG
12.4 IBM Corporation
12.5 SAP SE
12.6 AGCO Corporation
12.7 Oracle Corporation
12.8 Microsoft Corporation
12.9 Accenture plc
12.10 Farmers Edge Inc.
12.11 CropX Technologies
12.12 Taranis
12.13 Iteris, Inc.
12.14 PrecisionHawk, Inc.
12.15 Agrivi Ltd.
12.16 SAS Institute Inc.
12.17 Geosys SAS
12.18 Proagrica Ltd.
12.19 Conservis Corporation
List of Tables
1 Global Agricultural Data Analytics Market Outlook, By Region (2024-2032) ($MN)
2 Global Agricultural Data Analytics Market Outlook, By Component (2024-2032) ($MN)
3 Global Agricultural Data Analytics Market Outlook, By Solutions (Software Platforms) (2024-2032) ($MN)
4 Global Agricultural Data Analytics Market Outlook, By Farm Management Software (FMS) (2024-2032) ($MN)
5 Global Agricultural Data Analytics Market Outlook, By Yield Monitoring and Forecasting Solutions (2024-2032) ($MN)
6 Global Agricultural Data Analytics Market Outlook, By Inventory Management Solutions (2024-2032) ($MN)
7 Global Agricultural Data Analytics Market Outlook, By Supply Chain and Traceability Suites (2024-2032) ($MN)
8 Global Agricultural Data Analytics Market Outlook, By Services (2024-2032) ($MN)
9 Global Agricultural Data Analytics Market Outlook, By Managed Services (2024-2032) ($MN)
10 Global Agricultural Data Analytics Market Outlook, By Professional Services (2024-2032) ($MN)
11 Global Agricultural Data Analytics Market Outlook, By Deployment Mode (2024-2032) ($MN)
12 Global Agricultural Data Analytics Market Outlook, By Cloud-based (2024-2032) ($MN)
13 Global Agricultural Data Analytics Market Outlook, By On-Premises (2024-2032) ($MN)
14 Global Agricultural Data Analytics Market Outlook, By Farm Size (2024-2032) ($MN)
15 Global Agricultural Data Analytics Market Outlook, By Large Farms (2024-2032) ($MN)
16 Global Agricultural Data Analytics Market Outlook, By Small and Medium-Sized Farms (2024-2032) ($MN)
17 Global Agricultural Data Analytics Market Outlook, By Technology (2024-2032) ($MN)
18 Global Agricultural Data Analytics Market Outlook, By Core Technologies (2024-2032) ($MN)
19 Global Agricultural Data Analytics Market Outlook, By Predictive Analytics (2024-2032) ($MN)
20 Global Agricultural Data Analytics Market Outlook, By Prescriptive Analytics (2024-2032) ($MN)
21 Global Agricultural Data Analytics Market Outlook, By Descriptive Analytics (2024-2032) ($MN)
22 Global Agricultural Data Analytics Market Outlook, By Enabling Technologies (2024-2032) ($MN)
23 Global Agricultural Data Analytics Market Outlook, By Big Data & IoT (Internet of Things) (2024-2032) ($MN)
24 Global Agricultural Data Analytics Market Outlook, By Artificial Intelligence (AI) & Machine Learning (ML) (2024-2032) ($MN)
25 Global Agricultural Data Analytics Market Outlook, By Remote Sensing & Imagery (2024-2032) ($MN)
26 Global Agricultural Data Analytics Market Outlook, By Geographic Information Systems (GIS) (2024-2032) ($MN)
27 Global Agricultural Data Analytics Market Outlook, By Application (2024-2032) ($MN)
28 Global Agricultural Data Analytics Market Outlook, By Farm Analytics (2024-2032) ($MN)
29 Global Agricultural Data Analytics Market Outlook, By Yield Monitoring (2024-2032) ($MN)
30 Global Agricultural Data Analytics Market Outlook, By Crop Health Monitoring (2024-2032) ($MN)
31 Global Agricultural Data Analytics Market Outlook, By Irrigation Management (2024-2032) ($MN)
32 Global Agricultural Data Analytics Market Outlook, By Field Mapping (2024-2032) ($MN)
33 Global Agricultural Data Analytics Market Outlook, By Weather Tracking & Forecasting (2024-2032) ($MN)
34 Global Agricultural Data Analytics Market Outlook, By Livestock Analytics (2024-2032) ($MN)
35 Global Agricultural Data Analytics Market Outlook, By Health & Behavior Monitoring (2024-2032) ($MN)
36 Global Agricultural Data Analytics Market Outlook, By Milk Harvesting Management (2024-2032) ($MN)
37 Global Agricultural Data Analytics Market Outlook, By Feeding Management (2024-2032) ($MN)
38 Global Agricultural Data Analytics Market Outlook, By Aquaculture Analytics (2024-2032) ($MN)
39 Global Agricultural Data Analytics Market Outlook, By Greenhouses & Indoor Farming Analytics (2024-2032) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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