Why Great Products Still Fail to Achieve Adoption
Perfect product-market fit. Glowing testimonials. Clear business value. Yet 70% of your users never make it past basic features. The honest truth? Your adoption problem might not be a product problem, but an emotional one.
As product managers, we often assume that demonstrating value drives adoption. Build better features → Show clear ROI → Users adopt. But research reveals an uncomfortable truth: while users may rationally evaluate features, their adoption decisions are heavily influenced by emotional responses to workflow change. For 84% of your user base, that emotional experience begins with resistance, not enthusiasm.
The Adoption Paradox: When Logic Isn’t Enough
Consider Slack’s early enterprise rollouts. Despite obvious productivity benefits, many organizations saw pockets of resistance. Email veterans felt overwhelmed by real-time communication. Middle managers worried about losing control over information flow. The product was objectively better but adoption required addressing emotional responses to change.
This pattern repeats itself across B2B and consumer products alike. Figma faced designer resistance when moving from desktop to browser-based design. Netflix encountered user frustration when transitioning from DVDs to streaming. The technology was superior, but user adoption was limited by the emotional adjustment required.
Understanding Your Users Through the Adoption Curve
Rogers’ Diffusion of Innovation Theory segments users by adoption timing, but product managers need to understand the psychology behind these segments:
Innovators (2.5%) - Your risk-taking technology enthusiasts
- Embrace cutting-edge features and experimental functionality
- Tolerate instability in exchange for early access
- Often provide technical feedback and edge case discoveries
- PM Insight: Valuable for alpha testing and technical validation
Early Adopters (13.5%) - Your influential champions
- Seek competitive advantage through new tools
- Willing to tolerate bugs for early access
- Become internal advocates and case studies
- PM Insight: These users provide product feedback and social proof
Early Majority (34%) - Your pragmatic mainstream users
- Need proven value before committing
- Wait for peer validation and stable features
- Drive volume adoption when convinced
- PM Insight: Focus on reducing friction and demonstrating clear ROI
Late Majority (34%) - Your skeptical but necessary users
- Resist change until it becomes standard
- Need extensive support and gradual introduction
- Often represent largest user segments
- PM Insight: Require different onboarding flows and success metrics
Laggards (16%) - Your most reluctant adopters
- Adopt only when forced or given no alternative
- May never fully embrace new workflows
- Often vocal critics during transitions
- PM Insight: May require alternative interfaces or migration deadlines
Diffusion of Innovation Curve
Here’s the critical realization: 84% of your users (Early Majority + Late Majority + Laggards) will initially resist your product, not because it lacks value, but because change often triggers psychological distress. Even more alarming: only 16% (Innovators + Early Adopters) will usually enthusiastically embrace your product from the start.
The DOI Experience Model: Mapping the Emotional Journey
Research by du Plessis and Smuts revealed that user adoption follows predictable emotional stages, similar to grief processing. The DOI Experience Model maps this journey:
Stage 1: Refusal
User Mindset: “This doesn’t concern me” or “I don’t need this”
Behavioral Indicators:
- Ignoring onboarding emails
- Skipping product demos
- Questioning necessity during team meetings
PM Response: Don’t force engagement. Use social proof and peer success stories.
Stage 2: Anger/Bargaining
User Mindset: “This is unnecessary” or “Why can’t we just stick with the old system?”
Behavioral Indicators:
- Vocal complaints in user feedback
- Requests to delay implementation
- Comparing negatively to previous tools
PM Response: Listen actively. Create feedback channels. Address specific concerns.
Stage 3: Acquiesce
User Mindset: “I have to use this even if I don’t want to”
Behavioral Indicators:
- Minimal feature usage (only required workflows)
- Low engagement scores
- Compliance without enthusiasm
PM Response: This is the danger zone where adoption can stall. Focus on quick wins and gradual value discovery.
Stage 4: Exploration
User Mindset: “Maybe there’s something useful here” or “This looks interesting”
Behavioral Indicators:
- Increased session duration
- Trying optional features
- Asking questions about advanced functionality
PM Response: Provide guided discovery. Use progressive disclosure to reveal relevant features.
Stage 5: Adoption
User Mindset: “This makes my life easier” or “This is actually better than what we had before”
Behavioral Indicators:
- Regular use of core features
- Positive feedback and feature requests
- Recommending to colleagues
PM Response: Nurture these users as champions to drive adoption for users stuck in other stages. Gather case studies and feedback for product improvements.
The DOI Experience Model
Practical Application for Product Managers
Identifying User Stages Through Research
User Interviews:
- “How do you currently handle [workflow your product addresses]?”
- “What concerns do you have about changing your current process?”
- “When you think about adopting new tools, what typically concerns you?”
Behavioral Analytics:
- Refusal: Low login frequency, incomplete onboarding
- Anger/Bargaining: High support ticket volume, negative NPS comments
- Acquiesce: Basic feature usage only, low session engagement
- Exploration: Increasing feature breadth, longer sessions
- Adoption: Regular usage patterns, positive feedback loops
Product Metrics That Correlate:
- Time-to-first-value varies dramatically by DOI stage
- Feature adoption curve shows different patterns for each segment
- Support ticket sentiment reveals emotional position
Designing for Different Adoption Stages
For Product-Led Growth (PLG):
- Knowledge Bases: Create content addressing specific stage concerns—FAQs for Anger stage like “Why can’t I use the current tool?” and advanced workflow guides for users in Exploration
- Digital Adoption Platforms: Contextual help that adapts to user emotional state—gentle nudges during Acquiesce, feature discovery tours during Exploration
- Progressive Onboarding: Allow users to control pacing and depth—freemium users in Refusal stage need minimal friction, while Exploration users want comprehensive feature access
- In-App Messaging: Celebrate small wins during Acquiesce → Exploration transition, like “Well done! You’ve created your first workflow!” to build confidence
For Sales-Led Growth (SLG):
- Customer Success Programs: Train CSMs to recognize emotional stages—Acquiesce users need quick wins and hand-holding, while Exploration users want advanced feature demos and best practices
- Implementation Training: Structure training to match emotional readiness—don’t overwhelm Late Majority users with advanced features until they’ve mastered basics
- Account Management: Use stage identification to customize expansion conversations—users in Adoption stage are ready for advanced modules, Acquiesce users need proof of current value first
- Support Escalation: Route emotional resistance (“This is too complicated”) differently than technical issues (“The API isn’t working”) to appropriate teams
Product Development Integration
User Story Framework:
As a [Late Majority user in Acquiesce stage]
I want [minimal viable workflow with clear value]
So that [I can complete required tasks without feeling overwhelmed]Feature Prioritization:
- Early Adopters: Advanced features and customization
- Early Majority: Reliability and integration capabilities
- Late Majority: Simplification and guided workflows
- Laggards: Migration tools and legacy support
Go-to-Market Strategy:
- Phase 1: Early Adopter beta with advanced features
- Phase 2: Early Majority rollout with case studies and ROI proof
- Phase 3: Late Majority adoption with extensive support and training
- Phase 4: Laggard conversion with transition deadlines and alternatives
Interested in exploring these adoption strategies?
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Real-World Implementation: A B2B SaaS Example
Scenario: Rolling out a new project management platform across a 500-person organization
Traditional Approach: Train everyone on all features simultaneously
DOI Experience Approach:
Phase 1 - Discover Facilitators (Weeks 1-2)
- Identify Early Adopters through surveys about technology adoption attitudes
- Give early access and gather feedback
- Create internal case studies and success stories
Phase 2 - Convert Mainstream Users (Weeks 3-12)
- Early Majority: Launch with peer testimonials and proven ROI metrics
- Late Majority: Provide extra training, peer mentors, and gradual feature introduction
- Laggards: Offer parallel system access with migration timeline and dedicated support
Consumer Example: Spotify’s transition from music ownership to streaming required similar emotional management—addressing loss of “ownership,” fear of subscription costs, and concerns about music availability.
Measuring Success Across the Journey
Stage-Specific Metrics:
- Refusal → Anger: Engagement rate, demo completion
- Anger → Acquiesce: Support ticket sentiment, feature adoption breadth
- Acquiesce → Exploration: Session depth, optional feature usage
- Exploration → Adoption: Usage consistency, NPS scores, referral behavior
Leading Indicators:
- Reduced negative feedback during Anger stage
- Increased session duration during Exploration
- Feature breadth expansion as users move from Acquiesce to Exploration
The Competitive Advantage of Emotional Intelligent Design
Products that acknowledge and design for emotional adoption journeys consistently outperform those focused solely on features. Users become advocates not just because the product works, but because the adoption experience respected their psychological needs.
Key Takeaways for Product Managers:
- Segment by emotional readiness, not just demographics or use cases
- Design different onboarding flows for different adoption stages
- Measure emotional indicators alongside traditional product metrics
- Train customer-facing teams to recognize and respond to adoption stages
- Use facilitators strategically to influence mainstream adoption
The DOI Experience Model isn’t just a change management theory—it can be applied as a product strategy framework that helps PMs build adoption into the product experience itself. By understanding that emotion often drives adoption more than features, product managers can design user journeys that transform inevitable resistance into enthusiastic advocacy.
The DOI Experience Model is based on peer-reviewed research by Gustav du Plessis and Hanlie Smuts, University of Pretoria (2021), combining Rogers’ Diffusion of Innovation Theory with psychological models of change adaptation. Source