★ WIDE MOAT STOCKS & COMPETITIVE ADVANTAGES ★
VOL. XCIV, NO. 247
Stock Profile
Deere & Company (DE) Moat Analysis
Deere & Company
DE · New York Stock Exchange
Weighted average of segment moat scores, combining moat strength, durability, confidence, market structure, pricing power, and market share.
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Overview
Deere & Company makes agricultural, turf, construction and forestry equipment and operates a captive finance arm. Its strongest advantages are the John Deere brand in agriculture, a scaled dealer and field-service network that supports equipment uptime, and connected-machine workflows through the John Deere Operations Center. Those advantages are strongest in large agriculture and construction; smaller turf products face more price-sensitive and nonexclusive retail channels, while construction-brand evidence was insufficient to support a separate moat beyond service and workflow integration. Captive financing helps close equipment sales at the point of sale, but Deere's investment-grade funding access was not treated as a distinct advantage over large banks and finance companies. Right-to-repair rules, interoperable software, dealer execution, cyclicality and strong OEM rivals are the main constraints.
Primary segment
Production & Precision Agriculture
Market structure
Oligopoly
Market share
—
HHI: —
Coverage
4 segments · 7 tags
Updated 2026-07-12
Segments
Production & Precision Agriculture
Large-scale agricultural equipment and integrated precision agriculture technology
Revenue
38.4%
Structure
Oligopoly
Pricing
moderate
Share
—
Peers
Small Agriculture & Turf
Small/medium agricultural equipment, hay & forage, and turf care equipment
Revenue
22.8%
Structure
Competitive
Pricing
weak
Share
—
Peers
Construction & Forestry
Construction equipment, roadbuilding equipment, and forestry equipment (including smart/precision jobsite solutions)
Revenue
25.4%
Structure
Oligopoly
Pricing
moderate
Share
—
Peers
Financial Services
Captive equipment financing for agricultural, turf, construction and forestry equipment (retail/wholesale financing, leases, revolving accounts, extended warranties)
Revenue
12.7%
Structure
Competitive
Pricing
none
Share
—
Peers
—
Moat Claims
Production & Precision Agriculture
Large-scale agricultural equipment and integrated precision agriculture technology
Revenue share computed from FY2025 segment external net sales ($17.311B), external finance & interest income ($0.043B), and external other income ($0.211B) versus consolidated net sales and revenues ($45.684B) in Deere's FY2025 Form 10-K segment note.
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength
Durability
Confidence
Evidence
Connected-machine telematics and the John Deere Operations Center tie equipment, agronomic/job data, and dealer support workflows together, increasing switching friction for customers standardizing on Deere fleets and digital tools.
Data Workflow Lockin moat: definition, examples, and stocks
Erosion risks
- Data portability requirements and open-ecosystem regulation
- OEM/third-party interoperability reduces platform differentiation
- Cybersecurity incidents harming trust in connected services
Leading indicators
- Connected machine penetration and paid digital feature adoption
- Deere Operations Center active users and integration breadth
- Precision upgrade/retrofit attach rates via dealers
Counterarguments
- Farm management software and telematics can be vendor-agnostic, enabling multi-OEM fleets
- Competing OEMs are investing heavily in similar connectivity and automation capabilities
Service Field Network
Supply
Service Field Network
Strength
Durability
Confidence
Evidence
A large independent dealer network plus proprietary parts availability and aftersales support (maintenance/repair contracts, warranty extensions, connected support) helps maximize uptime and reinforces preference for Deere equipment.
Service Field Network moat: definition, examples, and stocks
Erosion risks
- Dealer consolidation or channel conflict reducing service quality
- Right-to-repair initiatives reducing proprietary service advantage
- Parts supply disruptions or quality issues
Leading indicators
- Dealer density and service response time metrics
- Parts fill rates and backorder/lead-time trends
- Aftermarket/service revenue resilience through cycles
Counterarguments
- Independent dealers can represent or add competing lines, diluting exclusivity
- Third-party parts and independent service networks can reduce dependence on OEM channels
Brand Trust
Demand
Brand Trust
Strength
Durability
Confidence
Evidence
John Deere brand recognition is explicitly cited as a competitive factor; in premium agricultural equipment, brand and perceived reliability support purchase preference and pricing.
Brand Trust moat: definition, examples, and stocks
Erosion risks
- Reliability/quality failures or safety incidents
- Perceived technology/automation lag versus peers
- Geopolitical backlash affecting brand preference in certain regions
Leading indicators
- Price realization and mix (large tractors/combines) versus peers
- Customer satisfaction and warranty/recall trends
- Share of wallet among large-farm customers and fleet standardization
Counterarguments
- Farm economics are cyclical; in downturns, buyers may prioritize price over brand
- Competitors can match performance/technology features and compete aggressively on total cost of ownership
Small Agriculture & Turf
Small/medium agricultural equipment, hay & forage, and turf care equipment
Revenue share computed from FY2025 segment external net sales ($10.224B), external finance & interest income ($0.045B), and external other income ($0.133B) versus consolidated net sales and revenues ($45.684B) in Deere's FY2025 Form 10-K segment note.
Service Field Network
Supply
Service Field Network
Strength
Durability
Confidence
Evidence
Sales and support through a broad dealer network (and, in turf, distribution through major mass retailers) improves availability, service access, and reduces adoption friction for customers.
Service Field Network moat: definition, examples, and stocks
Erosion risks
- Mass retailers/private-label products increasing price competition
- Dealer economics pressured in downturns (service capacity and inventory)
- Commoditization in entry-level and mid-tier equipment
Leading indicators
- Dealer throughput and inventory levels in small ag/turf
- Promo intensity and discounting in residential turf
- Parts/service attachment in the installed base
Counterarguments
- Many products compete in fragmented markets where price and availability dominate
- Channel access is not exclusive; rivals also have strong dealer and retail distribution
Brand Trust
Demand
Brand Trust
Strength
Durability
Confidence
Evidence
Deere brand recognition supports customer preference in many regions, but turf and compact equipment face strong brand competition and price sensitivity.
Brand Trust moat: definition, examples, and stocks
Erosion risks
- Consumers trading down in housing/consumer downturns
- Competitor innovation and feature parity narrowing perceived differentiation
Leading indicators
- Market share trend in commercial mowing and compact tractors
- Retail sell-through and dealer order rates
- Net promoter score and product review trends
Counterarguments
- In turf, Toro and other specialists can be preferred in key professional niches
- Feature parity and commoditization can limit the brand premium in lower price tiers
Construction & Forestry
Construction equipment, roadbuilding equipment, and forestry equipment (including smart/precision jobsite solutions)
Revenue share computed from FY2025 segment external net sales ($11.382B), external finance & interest income ($0.012B), and external other income ($0.192B) versus consolidated net sales and revenues ($45.684B) in Deere's FY2025 Form 10-K segment note.
Service Field Network
Supply
Service Field Network
Strength
Durability
Confidence
Evidence
Dealer and company-owned sales/service channels plus training and parts support improve uptime for fleet customers; this service footprint is hard to replicate quickly at scale.
Service Field Network moat: definition, examples, and stocks
Erosion risks
- Rental channel concentration shifting bargaining power to large fleet buyers
- Dealer consolidation and service capacity constraints
- Supply chain disruptions affecting parts availability
Leading indicators
- Rental fleet penetration and large-account win rates
- Parts fill rates and service response times
- Warranty claim trends and uptime metrics in connected support
Counterarguments
- Large contractors can multi-source fleets and negotiate service terms across OEMs
- Competitors with strong dealer networks (e.g., Caterpillar) can match service coverage
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength
Durability
Confidence
Evidence
Smart construction solutions (machine control, automation, telematics) and access to the John Deere Operations Center can embed Deere into jobsite workflows and maintenance planning, raising switching friction for connected fleets.
Data Workflow Lockin moat: definition, examples, and stocks
Erosion risks
- Interoperable jobsite platforms reduce proprietary workflow lock-in
- Third-party machine control ecosystems (e.g., Trimble/Topcon) remaining OEM-agnostic
- Rapid competitor feature parity in automation and connectivity
Leading indicators
- Attach rate of machine control/automation packages
- Connected fleet adoption and active usage of jobsite data tools
- Software/service recurring revenue growth within CF
Counterarguments
- Contractors often standardize on third-party machine control that works across OEMs
- Workflow tools may be multi-homed; switching costs can be manageable for large fleets
Financial Services
Captive equipment financing for agricultural, turf, construction and forestry equipment (retail/wholesale financing, leases, revolving accounts, extended warranties)
Revenue share computed from FY2025 FS external finance & interest income ($5.351B) and external other income ($0.470B) versus consolidated net sales and revenues ($45.684B) in Deere's FY2025 Form 10-K segment note.
Suite Bundling
Demand
Suite Bundling
Strength
Durability
Confidence
Evidence
Point-of-sale captive financing (dealer wholesale and customer retail notes/leases) can increase close rates and attach to equipment sales; promotional financing can be coordinated with equipment operations.
Suite Bundling moat: definition, examples, and stocks
Erosion risks
- Competitors and banks matching promotional terms
- Higher interest rates reducing financing demand
- Credit losses rising in downturns and used-equipment values falling
Leading indicators
- Financing penetration rate on Deere equipment sales
- Dealer wholesale note balances and turn rates
- Credit losses, delinquency, and used-equipment collateral values
Counterarguments
- Customers can finance through banks and leasing companies, limiting stickiness
- Promotional financing can compress spreads and may be competed away
Evidence
Describes telematics connecting owners, managers, and dealers via the John Deere Operations Center with real-time equipment data.
States precision technology is integrated into equipment and supported through the Operations Center with service alerts and predictive repairs/maintenance.
Explains equipment is marketed primarily through independent retail dealer networks and highlights the importance of timely parts/services and customer assistance programs.
Lists principal competitive factors and notes that John Deere brand recognition is a competitive factor in North America and many other regions.
States SAT equipment is sold primarily through independent retail dealer networks and that the segment builds turf products for sale by mass retailers (including The Home Depot and Lowe's).
Showing 5 of 9 sources.
Risks & Indicators
Erosion risks
- Data portability requirements and open-ecosystem regulation
- OEM/third-party interoperability reduces platform differentiation
- Cybersecurity incidents harming trust in connected services
- Dealer consolidation or channel conflict reducing service quality
- Right-to-repair initiatives reducing proprietary service advantage
- Parts supply disruptions or quality issues
Leading indicators
- Connected machine penetration and paid digital feature adoption
- Deere Operations Center active users and integration breadth
- Precision upgrade/retrofit attach rates via dealers
- Dealer density and service response time metrics
- Parts fill rates and backorder/lead-time trends
- Aftermarket/service revenue resilience through cycles
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