Cultivating resilience: agricultural marketing in the age of volatility
Amy O'Hara
March 24, 2026
6
minutes read
For years, agricultural marketing has been built around a familiar rhythm. Plans are set by season, media is flighted against expected purchase windows, and messaging assumes that the market will move more or less on cue.
Recent disruption across fertilizer production and shipping has pushed a structural weakness into the open. The effective closure of the Strait of Hormuz has hit a route that handles about one-third of global seaborne fertilizer trade, while China has tightened fertilizer export restrictions at the same time. Reuters has reported international urea prices up about 40% from pre-war levels, with U.S. prices also climbing sharply as supply tightens ahead of planting.
The implications reach well beyond procurement. It changes farmer economics, crop planning, purchase timing, and the way agricultural brands should think about media. When the real decision window is dictated by input availability and margin pressure rather than the old seasonal calendar, rigid campaign planning stops looking efficient and starts looking late.
The fixed calendar is no longer reliable
Agricultural marketers have always planned around seasonal patterns, but volatility is now reshaping those patterns in real time. The current fertilizer shock is landing just as planting decisions are being finalized, and that creates a moving target by crop, by region, and by producer economics.
👉 For instance, in Illinois' budget analysis for 2026, projected corn returns trail soybeans by roughly $55 to $80 per acre, pointing to possible acreage shifts. That is a reminder that demand is not disappearing but redistributing.
This is where many media plans fall behind reality. A plan built months earlier may still be technically “on schedule” while being strategically out of step with the market. If supply is delayed, if fertilizer is harder to source, or if growers begin changing crop mix, messaging and geography may need to shift with it. A brand that can move dollars, timing, and emphasis quickly has a better chance of staying relevant to the actual purchase decision rather than the one it expected to happen.
Margin pressure changes the message
Volatility influences the buying decision at every level—not only when farmers purchase but how they weigh what's worth purchasing.
👉 USDA’s latest farm income forecast says overall farm cash receipts are expected to decline by $14.2 billion, or 2.7%, in 2026. At the same time, farmers are still dealing with elevated production costs and fresh uncertainty around critical inputs. In practical terms, that means more scrutiny, tighter comparisons, and less patience for broad feature-led messaging.
The farmer mindset in conditions like this is not hard to understand. Per-acre impact takes over—what does this protect, what does it save, what does it improve? Messaging needs to match that focus, working harder on yield efficiency, input optimization, operating resilience, and financial payback. Attention goes to the brands that make the economics visible and concrete.
Pic. Ag Economy Barometer, showing farmer sentiment dropping sharply at the start of 2026 (Source).
That does not mean agricultural marketing should become cold or purely transactional. Agriculture is still a trust-based category with long buying cycles and high relationship value. But trust alone is not enough when margins are under strain. Brands need to show that they understand the pressure on the farm business itself. When they do, their message lands differently.
Visibility matters more when the market feels shaky
The instinct in a volatile market is often to pull back. That reaction is understandable, but it can be strategically expensive.
👉 McKinsey has argued that disciplined spend management can free up as much as 20% of marketing budget and support rapid redeployment toward higher-value activity. Separate long-term evidence summarized by the IPA shows that brands maintaining or increasing advertising investment during downturns tend to grow profits and market share faster in recovery than brands that retreat. The lesson is not “spend blindly.” It is “protect visibility while getting stricter about waste.”
In agriculture, that distinction carries particular weight. This is not a category where trust can be switched off for a quarter and switched back on when conditions improve. If anything, periods of uncertainty are when consistent presence becomes more valuable. Farmers are under pressure, but they are still evaluating options, still comparing suppliers, and still looking for signals of reliability. Going quiet at that moment hands space to competitors that stay visible and useful.
Fragmentation is expensive when the ground keeps moving
There is another problem volatility exposes: fragmentation inside the media plan itself.
👉 Farm audiences do not live in one channel. USDA data shows that 85% of farms had internet access in 2025, 50% used the internet to purchase agricultural inputs, and 29% used it to market agricultural activities. Farm Journal has also reported strong use of streaming and social media among producers. The audience is reachable, but not through a single neat path.
Pic. Digital matters for agricultural purchases, but growers still prefer in-person interactions (Source).
That makes fragmented execution harder to justify. When brands are spread across niche publishers, direct platform buys, siloed reporting, and disconnected vendors, they pay for it twice: once in operational drag and again in slower decision-making. In stable conditions, that inefficiency is frustrating. In volatile conditions, it becomes a tax.
This is where a more joined-up, adaptable approach becomes valuable. AI Digital’s Open Garden framework is not simply a media philosophy. In a market like this, it becomes a practical operating advantage. Transparency, cross-channel visibility, and the freedom to optimize without being trapped inside a single buying silo make it easier to respond when regional conditions shift, crop economics move, or messaging needs to change quickly. The goal is reducing friction when speed matters most, not adding complexity for its own sake.
Resilience is now a marketing discipline
Look past the supply-chain headline and the 2026 fertilizer shock reveals something larger: a stress test for how agricultural marketing is planned.
A fixed-calendar approach assumes the market will behave predictably enough for timing to do most of the work. That assumption is weaker now. Resilient agricultural marketing needs to be more adaptive in timing, sharper in economic messaging, steadier in visibility, and less burdened by fragmentation. It has to function more like a live operating system than a pre-set campaign calendar.
Brands that make that shift will be in a stronger position not only for this season, but for the next period of disruption too. Because volatility may not be the exception anymore. It may be the condition.
If this is where your team’s thinking is heading, we would be glad to talk through what a more agile, transparent media approach could look like in practice.
Blind spot
Key issues
Business impact
AI Digital solution
Lack of transparency in AI models
• Platforms own AI models and train on proprietary data • Brands have little visibility into decision-making • "Walled gardens" restrict data access
• Inefficient ad spend • Limited strategic control • Eroded consumer trust • Potential budget mismanagement
Open Garden framework providing: • Complete transparency • DSP-agnostic execution • Cross-platform data & insights
Optimizing ads vs. optimizing impact
• AI excels at short-term metrics but may struggle with brand building • Consumers can detect AI-generated content • Efficiency might come at cost of authenticity
• Short-term gains at expense of brand health • Potential loss of authentic connection • Reduced effectiveness in storytelling
Smart Supply offering: • Human oversight of AI recommendations • Custom KPI alignment beyond clicks • Brand-safe inventory verification
The illusion of personalization
• Segment optimization rebranded as personalization • First-party data infrastructure challenges • Personalization vs. surveillance concerns
• Potential mismatch between promise and reality • Privacy concerns affecting consumer trust • Cost barriers for smaller businesses
Elevate platform features: • Real-time AI + human intelligence • First-party data activation • Ethical personalization strategies
AI-Driven efficiency vs. decision-making
• AI shifting from tool to decision-maker • Black box optimization like Google Performance Max • Human oversight limitations
• Strategic control loss • Difficulty questioning AI outputs • Inability to measure granular impact • Potential brand damage from mistakes
Managed Service with: • Human strategists overseeing AI • Custom KPI optimization • Complete campaign transparency
Fig. 1. Summary of AI blind spots in advertising
Dimension
Walled garden advantage
Walled garden limitation
Strategic impact
Audience access
Massive, engaged user bases
Limited visibility beyond platform
Reach without understanding
Data control
Sophisticated targeting tools
Data remains siloed within platform
Fragmented customer view
Measurement
Detailed in-platform metrics
Inconsistent cross-platform standards
Difficult performance comparison
Intelligence
Platform-specific insights
Limited data portability
Restricted strategic learning
Optimization
Powerful automated tools
Black-box algorithms
Reduced marketer control
Fig. 2. Strategic trade-offs in walled garden advertising.
Core issue
Platform priority
Walled garden limitation
Real-world example
Attribution opacity
Claiming maximum credit for conversions
Limited visibility into true conversion paths
Meta and TikTok's conflicting attribution models after iOS privacy updates
Data restrictions
Maintaining proprietary data control
Inability to combine platform data with other sources
Amazon DSP's limitations on detailed performance data exports
Cross-channel blindspots
Keeping advertisers within ecosystem
Fragmented view of customer journey
YouTube/DV360 campaigns lacking integration with non-Google platforms
Black box algorithms
Optimizing for platform revenue
Reduced control over campaign execution
Self-serve platforms using opaque ML models with little advertiser input
Performance reporting
Presenting platform in best light
Discrepancies between platform-reported and independently measured results
Consistently higher performance metrics in platform reports vs. third-party measurement
Fig. 1. The Walled garden misalignment: Platform interests vs. advertiser needs.
Key dimension
Challenge
Strategic imperative
ROAS volatility
Softer returns across digital channels
Shift from soft KPIs to measurable revenue impact
Media planning
Static plans no longer effective
Develop agile, modular approaches adaptable to changing conditions
Brand/performance
Traditional division dissolving
Create full-funnel strategies balancing long-term equity with short-term conversion
Capability
Key features
Benefits
Performance data
Elevate forecasting tool
• Vertical-specific insights • Historical data from past economic turbulence • "Cascade planning" functionality • Real-time adaptation
• Provides agility to adjust campaign strategy based on performance • Shows which media channels work best to drive efficient and effective performance • Confident budget reallocation • Reduces reaction time to market shifts
• Dataset from 10,000+ campaigns • Cuts response time from weeks to minutes
• Reaches people most likely to buy • Avoids wasted impressions and budgets on poor-performing placements • Context-aligned messaging
• 25+ billion bid requests analyzed daily • 18% improvement in working media efficiency • 26% increase in engagement during recessions
Full-funnel accountability
• Links awareness campaigns to lower funnel outcomes • Tests if ads actually drive new business • Measures brand perception changes • "Ask Elevate" AI Chat Assistant
• Upper-funnel to outcome connection • Sentiment shift tracking • Personalized messaging • Helps balance immediate sales vs. long-term brand building
• Natural language data queries • True business impact measurement
Open Garden approach
• Cross-platform and channel planning • Not locked into specific platforms • Unified cross-platform reach • Shows exactly where money is spent
• Reduces complexity across channels • Performance-based ad placement • Rapid budget reallocation • Eliminates platform-specific commitments and provides platform-based optimization and agility
• Coverage across all inventory sources • Provides full visibility into spending • Avoids the inability to pivot across platform as you’re not in a singular platform
Fig. 1. How AI Digital helps during economic uncertainty.
Trend
What it means for marketers
Supply & demand lines are blurring
Platforms from Google (P-Max) to Microsoft are merging optimization and inventory in one opaque box. Expect more bundled “best available” media where the algorithm, not the trader, decides channel and publisher mix.
Walled gardens get taller
Microsoft’s O&O set now spans Bing, Xbox, Outlook, Edge and LinkedIn, which just launched revenue-sharing video programs to lure creators and ad dollars. (Business Insider)
Retail & commerce media shape strategy
Microsoft’s Curate lets retailers and data owners package first-party segments, an echo of Amazon’s and Walmart’s approaches. Agencies must master seller-defined audiences as well as buyer-side tactics.
AI oversight becomes critical
Closed AI bidding means fewer levers for traders. Independent verification, incrementality testing and commercial guardrails rise in importance.
Fig. 1. Platform trends and their implications.
Metric
Connected TV (CTV)
Linear TV
Video Completion Rate
94.5%
70%
Purchase Rate After Ad
23%
12%
Ad Attention Rate
57% (prefer CTV ads)
54.5%
Viewer Reach (U.S.)
85% of households
228 million viewers
Retail Media Trends 2025
Access Complete consumer behaviour analyses and competitor benchmarks.
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Michaels Stores: Implemented a genAI platform that increased email personalization from 20% to 95%, leading to a 41% boost in SMS click through rates and a 25% increase in engagement.
Estée Lauder: Partnered with Google Cloud to leverage genAI technologies for real-time consumer feedback monitoring and analyzing consumer sentiment across various channels.
High
Medium
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Showmax: Partnered with AI firms toautomate ad creation and testing, reducing production time by 70% while streamlining their quality assurance process.
Headway: Employed AI tools for ad creation and optimization, boosting performance by 40% and reaching 3.3 billion impressions while incorporating AI-generated content in 20% of their paid campaigns.
High
High
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
L’Oréal: Analyzed millions of online comments, images, and videos to identify potential product innovation opportunities, effectively tracking brand sentiment and consumer trends.
Kellogg Company: Used AI to scan trending recipes featuring cereal, leveraging this data to launch targeted social campaigns that capitalize on positive brand sentiment and culinary trends.
High
Low
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
DoorDash: Leveraged Google’s AI-powered Demand Gen tool, which boosted its conversion rate by 15 times and improved cost per action efficiency by 50% compared with previous campaigns.
Kitsch: Employed Meta’s Advantage+ shopping campaigns with AI-powered tools to optimize campaigns, identifying and delivering top-performing ads to high-value consumers.
High
High
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
JPMorgan Chase: Collaborated with Persado to develop LLMs for marketing copy, achieving up to 450% higher clickthrough rates compared with human-written ads in pilot tests.
Hotel Chocolat: Employed genAI for concept development and production of its Velvetiser TV ad, which earned the highest-ever System1 score for adomestic appliance commercial.
High
High
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
Stitch Fix: Uses genAI to help stylists interpret customer feedback and provide product recommendations, effectively personalizing shopping experiences.
Instacart: Uses genAI to offer customers personalized recipes, mealplanning ideas, and shopping lists based on individual preferences and habits.
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