DEERE: FORCED ADOPTION AT SCALE
Driving platform-wide data adoption across 500K+ users without destroying trust—enabling $3.8B in connected-services revenue
34%→87%
Profile Completion
$3.8B
Revenue Enabled
-16%
Support Burden
500K+
Users · 12 Languages
Drove adoption 34%→87% across 500K users — unlocking $3.8B without breaking trust.
The Strategic Problem
John Deere's future depended on connected services, automation, and AI—but those capabilities required high-quality customer data. The existing model relied on optional data sharing across a fragmented ecosystem of legacy systems, which resulted in low adoption, incomplete profiles, and limited downstream value.
The challenge wasn't convincing users to click through forms. It was forcing adoption without eroding trust in a 185-year-old brand built on reliability.
Why This Was Hard
This problem sat at the intersection of business risk, user trust, and organizational complexity:
- User diversity: Customers ranged from highly technical operators to users without email access—and accessibility couldn't be an afterthought across that range
- Data sensitivity: Sharing triggered deep concerns around surveillance, ownership, and value exchange
- System fragmentation: Decades of acquisitions left inconsistent data models, legacy systems, and accumulated tech debt
- Sales-model variance: The same equipment was sold a dozen ways—per acre, per hour of use, outright, dealer-financed—so there was no single "customer" or "transaction" to design the flow around
- Relationship complexity: Dealers—not Deere—owned many customer relationships
- Hardware on a waterfall: Connected services ride on machines shipped on multi-year manufacturing cycles—you can't sprint embedded-equipment UX when the tractor it lives on is on a manufacturing waterfall
- Global scale: 12 languages across diverse regulatory environments
A purely coercive approach would have increased churn and damaged long-term brand trust.
Strategy
Instead of "forcing" adoption directly, we reframed the problem as progressive value exchange. Our strategy was built on four principles:
- Value Before Friction: Users should experience tangible benefits before being asked to share more data
- Transparency Builds Trust: Make it clear what data is requested, why, and how it's used—no dark patterns
- Multiple Paths, One Outcome: Support adoption through digital flows, dealer-assisted onboarding, and in-field support
- Graceful Degradation: Users who didn't complete profiles immediately still retained access—urgency was created through value, not lockout
What We Ruled Out
Three faster paths were on the table—and each was a trap:
- Hard-gate the account—lock features until the profile's complete. The fastest line to the number, but it spikes churn, floods dealers with angry calls, and on a 185-year-old reliability brand, forcing the door is a one-way trust hit.
- Dark-pattern nudges—pre-checked consent, buried opt-outs, manufactured urgency. Converts short-term and poisons the exact relationship you're building: the moment a customer feels tricked about their own machine data, connected services is dead on arrival.
- One universal flow—clean in Figma, impossible in reality given the sales-model variance, dealer-owned relationships, and 12 languages.
Killing the easy options was the strategy—the win was refusing the shortcut.
The bet. Progressive value exchange traded a fast, forced curve for a slower, durable one—and it cost real work: contextual prompts at every value moment, dealer tooling, and per-region trust messaging instead of one blocking form. The wager was that adoption that survives the relationship beats a number that burns it.
Execution
Progressive Profile Completion
Instead of a single blocking form, we designed contextual prompts tied to moments of value: predictive maintenance, equipment insights, automation features. Each step answered one question: "What do I get if I do this right now?"
Dealer-Enabled Adoption
Dealers became UX multipliers, not just support. Clear dealer workflows for assisting customers, shared visibility into completion state, and consistent language across touchpoints reduced friction while preserving trust in local relationships.
Trust-First Messaging
We replaced abstract legal language with plain-language explanations, explicit benefit statements, and clear reassurance around data use and control. This dramatically reduced resistance during onboarding.
Where It Got Hard: The Dealer Problem
The hardest part wasn't the flow. It was the dealer.
What We Got Wrong First
Our first instinct was dealer-up: arm the dealers, let adoption grassroots from the people who own the customer relationship. It didn't hold. Dealers sell too many ways—per acre, per usage, outright, concierge—to build coherent happy paths from the bottom up. We pivoted to top-down and user-centric: design the canonical flow around the end user and the value they get, then make the dealer a multiplier on top of it, not the foundation under it.
The B2B2C Twist
Deere reaches most customers through the dealer, and for the biggest accounts dealers run white-glove concierge—they do everything for the customer, including the digital setup. But the account that unlocks connected services carries Terms of Use and a data-sharing agreement that, legally, the equipment owner has to accept—not the dealer on their behalf. The thing standing between us and the data wasn't a form; it was agency. So we flipped the incentive: reward dealers for bringing customers into the digital relationship—their own account, their own data, their own sovereignty—instead of proxying it. That shift, more than any single flow, is what turned completion from a wall into a climb.
Results
- Profile completion increased from 34% to 87%
- Enabled $3.8B in connected-services revenue
- Reduced support tickets related to account setup by 16%
- Improved dealer efficiency by 28%
- Established a reusable adoption framework used across multiple Deere platforms
What This Unlocked
This work didn't just solve onboarding. It created:
- A scalable foundation for AI-driven services
- A repeatable model for introducing "forced" change without backlash
- A trust-based approach now reused across Deere's digital ecosystem
The real outcome was organizational confidence in using UX to drive adoption—not just usability.
Gallery
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