Post-Sale Management

A SaaS company spent six months building the "perfect" onboarding program. Training sessions, documentation, videos, dedicated CSMs. Usage still stayed at 35% of expected levels.

When they finally asked why people weren't using the product instead of assuming they just needed more training, the real barriers emerged:

"I didn't know that feature existed. Nobody told me." (Awareness)

"My manager doesn't use it, so I don't either." (Organizational)

"The integration doesn't work with our ERP system, so I have to duplicate data entry." (Technical)

"I don't see how this helps me personally. It helps the company, but creates more work for me." (Motivation)

"I don't have time to learn a complicated new system right now." (Capability)

They were solving for knowledge when the actual barriers were awareness, organizational alignment, technical friction, motivation, and capacity. More training wouldn't fix any of those.

Once they addressed what was actually blocking people—made hidden features more visible, got executive mandate for usage, fixed the integration, showed individual benefits instead of just company ROI, and simplified early workflows—usage jumped from 35% to 73% in 60 days.

Not because of more training. Because they removed what was actually in the way.

Understanding why customers don't use your product is more valuable than understanding why they do. Adoption isn't about motivating the willing. It's about removing barriers for everyone else.

Types of Adoption Barriers

Six categories explain most adoption resistance.

Awareness Barriers: "I Didn't Know About It"

Customers can't use features they don't know exist.

You'll hear variations of: "Wait, the product does that?" or "I've been doing this manually, had no idea there was a feature for it" or "Nobody told me about this."

This happens when features have poor discoverability in the UI, when onboarding covers too much too fast (people forget what was mentioned), when features get released without any announcement, when documentation is buried, or when CSMs focus only on basics during kickoff.

A marketing automation platform had a powerful A/B testing feature that only 8% of customers used. When they surveyed users, 67% didn't know it existed, 21% knew about it but didn't know how to access it, and just 12% knew and chose not to use it.

The actual problem wasn't the feature. It was that nobody knew it was there.

Knowledge Barriers: "I Don't Know How to Use It"

Customers know the feature exists but don't understand how to use it effectively.

Listen for: "This seems complicated" or "I tried it once and couldn't figure it out" or "I don't want to break something" or "I'm not technical enough for this."

Usually caused by insufficient or unclear documentation, no hands-on practice during training, complex UX without guidance, jargon or technical terminology that confuses people, missing examples and use cases, or an all-or-nothing learning approach that overwhelms.

One company's workflow automation feature had high awareness (onboarding covered it) but only 15% adoption. When they dug in, they found the documentation was a reference manual, not a how-to guide. There were no templates or examples to start from. Users feared building incorrect automations. One person commented: "I know it's there, but I'd need a computer science degree to use it."

The feature was powerful but not learnable.

Motivation Barriers: "I Don't See the Value"

Customers understand what the feature does but don't care because there's no perceived personal benefit.

This sounds like: "Why should I bother?" or "My current way works fine" or "That's nice for the company, but what's in it for me?" or "I don't have time for this."

The root causes are usually that the value proposition is organizational rather than personal, the benefit isn't immediate or obvious, it requires work upfront for payoff later, the change seems like an extra burden, there are no consequences for non-adoption, or no recognition for adoption.

Take a sales CRM. Management wanted pipeline visibility (organizational value). Sales reps saw it as extra data entry (burden), management surveillance (threat), and no help hitting quota (no personal benefit).

The result? Compliance adoption only, minimal usage, poor data quality. The real barrier was motivation. They didn't want to because they saw no upside for themselves.

Capability Barriers: "I Can't Do This Right Now"

Customers want to adopt but lack the skills, time, or resources.

You'll hear: "I don't have time to learn this" or "I'd need to hire someone to set this up" or "This requires technical skills I don't have" or "We're too understaffed to implement this properly."

Common causes include a high learning curve, resource-intensive setup or implementation, missing technical prerequisites, competing priorities taking precedence, or teams that are too small or busy.

An advanced analytics feature required SQL knowledge to write custom queries, 3-4 hours to set up dashboards initially, and clean data (garbage in, garbage out). Small companies had no one on the team who knew SQL, no time to learn it, messy data quality, and couldn't justify hiring an analyst.

They wanted the value but couldn't access it. That's a capability barrier.

Environmental Barriers: "The Organization Won't Let Me"

The individual wants to adopt, but organizational factors prevent it.

This sounds like: "My boss doesn't use it, so I can't either" or "Policy requires us to use the old system" or "Other departments aren't on board" or "We'd need executive approval we won't get."

Usually caused by lack of executive sponsorship, competing tools or processes, departmental silos, change resistance from influencers, no organizational mandate, or cultural resistance.

A marketing team adopted a project management tool. But the creative team still used email for requests, finance used a separate tool for budgets, and marketing couldn't enforce cross-department adoption. The result was fragmented data, duplicate work, and the tool became seen as a burden rather than a help.

They couldn't succeed in isolation. That's an environmental barrier.

Technical Barriers: "The Product Won't Let Me"

The product itself creates friction that blocks adoption.

People complain: "It's too slow" or "It keeps crashing" or "The UI is confusing" or "It doesn't work on mobile" or "The integration is broken" or "I have to do workarounds to make it function."

Common causes are UX complexity or poor design, performance issues, bugs and reliability problems, missing platform support (mobile, browser), integration failures, or inflexible workflows that don't match how people actually work.

One mobile app had only 12% adoption despite 89% of users working remotely. When they investigated, they found the app crashed frequently, had 15+ second load times, and had limited functionality compared to desktop (10× fewer features). Users gave up and stopped trying.

The product experience blocked adoption. That's a technical barrier.

Barrier Discovery Methods

How to find what's actually blocking adoption.

Usage Data Analysis: What's Not Being Used

Start with the numbers.

Look for low-adoption features: Feature X has only 8% of users who ever tried it. Feature Y has 23% who tried it, but only 9% still use it after 30 days.

These are barrier candidates. Something is preventing adoption.

Watch for behavioral signals like high drop-off rates (people start the feature but don't complete the workflow), short session times (open feature, leave quickly), no repeat usage (try once, never again), or low breadth adoption (few users trying it).

Here's what data tells you: that a barrier exists and how severe it is (how many people are affected).

Here's what data doesn't tell you: why the barrier exists, what type of barrier it is, or how to fix it.

Next step: talk to customers.

Customer Interviews and Feedback

Have direct conversations.

Interview low-adopters: "I noticed you haven't used [Feature]. Can you tell me why?"

Their responses reveal the barrier type. "Didn't know it existed" is awareness. "Tried it, couldn't figure it out" is knowledge. "Don't see the point" is motivation. "Too complicated for my needs" is capability. "My team doesn't use it" is environmental. "It's buggy/slow" is technical.

Use this script:

"Have you heard of [Feature]?" (awareness check)
"Have you tried it?" (activation check)
"What prevented you from trying it or continuing to use it?" (barrier identification)
"What would need to change for you to use it?" (solution discovery)

Interview 15-20 non-adopters. Patterns emerge quickly, and you get more precision than surveys alone.

Support Ticket Analysis

Mine your support data.

Ticket patterns reveal barriers. 47 tickets about "how to configure X" suggests a knowledge barrier. 33 tickets about "feature not working" points to a technical barrier. 28 tickets about "can't find where to do X" indicates an awareness barrier.

Pay attention to ticket sentiment too. Frustrated tone usually means a technical or capability barrier. Confused tone suggests a knowledge barrier. Apathetic tone hints at a motivation barrier.

Look at resolution patterns as well. If tickets get solved with a documentation link, you have a knowledge barrier (the docs exist but people aren't finding them). Bug fixes point to technical barriers. Explanations of value suggest motivation barriers.

The benefit of ticket analysis? Customers tell you problems unprompted, unlike surveys where you have to ask.

Session Recordings and User Testing

Watch how people actually use the product.

Session recordings (tools like FullStory, Hotjar, LogRocket) let you see where users get stuck, watch feature abandonment in real-time, and identify UX friction.

Confusion signals include hovering over elements without clicking (doesn't know what to do), clicking around randomly (lost), repeatedly clicking the same thing (expecting different result), rage clicking (frustrated), or backtracking frequently (wrong path).

Abandonment signals look like starting a workflow then stopping midway and leaving, opening a feature then staring at the screen for 30+ seconds before closing, or attempting an action multiple times then giving up.

What you learn: the exact moment users get stuck (knowledge or technical barrier), which UI elements confuse (technical barrier), where complexity overwhelms (capability barrier).

For user testing, give users a task, watch them attempt it, and ask them to think aloud. "Please create a new project and assign it to your team."

Observe: Can they find where to create the project? (awareness) Do they understand the form fields? (knowledge) Do they complete successfully? (technical/capability) Do they comment "this is confusing"? (direct feedback)

Surveys and Polls

Quantify barriers at scale.

Survey non-adopters with these questions:

"Are you aware that [Product] has [Feature]?" (Yes / No)

"Have you tried using [Feature]?" (Yes, currently use it / Yes, tried it but stopped / No, haven't tried it)

If they haven't tried it: "What's the main reason you haven't used [Feature]?" (Select one)

Didn't know it existed (awareness)
Don't know how to use it (knowledge)
Don't see how it helps me (motivation)
Too complicated/time-consuming (capability)
My team/manager doesn't use it (environmental)
It doesn't work well (technical)

If they tried but stopped: "Why did you stop using [Feature]?" (same options)

Then ask: "What would make you more likely to use [Feature]?"

Better explanation of benefits
Step-by-step training
Simpler interface
Better documentation
Examples from similar companies
Management requirement

The benefit of surveys is that you can quantify barrier distribution across your entire customer base.

CSM Observations and Reports

Leverage what CSMs already know.

CSMs hear barriers in every customer conversation. Set up a barrier collection process.

After each customer call, have CSMs log: which feature(s) were discussed, adoption status (using or not using), the barrier identified (if applicable), and barrier type (awareness, knowledge, motivation, capability, environmental, or technical).

Weekly CS team meetings should review logged barriers: which barriers are most common, which features have the most barriers, which barrier types dominate, and patterns by customer segment.

Here's an example log entry:

Customer: Acme Corp
Feature: Workflow Automation
Barrier Type: Knowledge
Notes: "Wants to use it but doesn't understand how to build workflows. Needs hands-on training, not documentation."
Action: Schedule training session, create template library

CSM reports aggregate frontline intelligence that data alone can't provide.

Awareness Barriers: Solutions

When customers don't know features exist.

Symptoms and Identification

Look for usage analytics showing less than 10% of people ever tried the feature, support tickets asking "How do I do X?" when a feature already exists for X, interviews where people say "Wait, it can do that?", or surveys with a high percentage answering "didn't know it existed."

Root Causes

Features stay hidden when they're not visible in the UI (buried in menus, poor navigation), onboarding doesn't cover them (too many features to cover, cherry-picked basics only), there's no announcement when they're released, documentation isn't surfaced at the right time, or feature naming is unclear (users don't recognize what it does).

Solutions: Education, Communication, Visibility

Improve in-product discoverability with feature highlights and callouts, a "What's New" section, contextual hints like "You can also use [Feature] for this," and search with feature suggestions.

Add proactive communication through feature spotlight email campaigns, in-app announcements, webinars and office hours highlighting underused features, and CSM outreach ("Have you explored [Feature]?").

Include contextual education via tooltips explaining what features do, "Related features you might like" recommendations, and use case-based navigation ("Want to do X? Try Feature Y").

One company saw feature adoption jump from 9% to 34% after adding an in-app banner highlighting the feature, running an email campaign with use case examples, training CSMs to mention it in onboarding calls, and updating navigation to make it more prominent.

In-Product Discovery Improvements

Make features easier to find.

Navigation improvements mean reducing menu depth (fewer clicks to reach features), using clear descriptive labels (not jargon), and grouping related features logically.

Visibility enhancements include highlighting new or underused features, progressive disclosure (advanced features surface as users mature), and onboarding checklists that include all core features.

Smart suggestions look like: "Based on what you're doing, try [Feature]" or "Users like you often use [Feature] next" or "Complete these tasks to get more value."

Knowledge Barriers: Solutions

When customers know features exist but don't know how to use them.

Identifying Confusion and Misunderstanding

Watch for high trial rates but low continued usage, support tickets asking "how do I...?", session recordings showing confusion behaviors, high training attendance but still low usage, or users commenting "it's too complicated."

Specific signals include features being opened then closed quickly (confused, gave up), multiple attempts to complete a workflow with none successful, or errors and incorrect usage patterns.

Documentation and Training Gaps

Documentation problems usually fall into a few categories.

Gap 1 is the reference manual problem. The docs explain what a feature does but not how to achieve goals. They're technically accurate but not learnable.

Fix this by creating goal-based guides like "How to automate your weekly reports" or "Setting up your first workflow in 5 steps" or "Quick start: Get results in 10 minutes."

Gap 2 is missing examples or templates. Abstract explanations without concrete starting points mean users don't know where to begin.

Fix this by providing pre-built templates users can customize, real-world examples from similar companies, and before/after comparisons.

Gap 3 is the all-or-nothing approach to learning. Everything at once or nothing at all, which creates overwhelming complexity upfront.

Fix this by breaking content into levels: beginner (basic usage), intermediate (common use cases), and advanced (power user techniques).

Training problems often stem from one-time sessions during onboarding, when the reality is that people forget 70% of what they learned within a week.

Fix this with spaced learning: initial training covering basics, a follow-up session 2 weeks later for Q&A and advanced topics, ongoing office hours for support as needed, and microlearning (bite-sized tips delivered over time).

Solutions: Better Education, Simpler UX

Education solutions include hands-on practice through sandbox environments for safe experimentation, guided tutorials (interactive, not just videos), and "follow along" live training sessions.

Just-in-time help means contextual tooltips right when users need them, embedded video tutorials inside the feature itself, and "Help me do this" wizards.

Peer learning looks like customer communities where users help each other, best practice sharing sessions, and customer champions who evangelize.

UX solutions include simplifying the interface by reducing options (progressive disclosure), using clear labels and instructions, and visual hierarchy (important things prominent).

Inline guidance means placeholder text showing examples, field-level help text, and error messages that explain how to fix the problem.

Workflow wizards provide step-by-step guided setup, prevent users from proceeding until each step is complete (which prevents errors), and show progress (which motivates completion).

One company increased workflow builder adoption from 14% to 51% after adding a wizard for the first workflow, creating 12 templates for common use cases, adding inline help text at each step, embedding a 2-minute video tutorial, and running monthly "Workflow Office Hours" webinars.

Just-in-Time Help and Guidance

Deliver help when and where it's needed.

Instead of a 45-minute training video users watch once and forget, embed contextual help in the workflow. When users start a workflow, a tooltip appears. When they get stuck, a "Need help?" prompt offers quick tips. When they make an error, they see an explanation and how to fix it. When they complete the task, a "Want to learn more?" link takes them to an advanced guide.

The benefits: learning happens during doing (better retention), reduced friction (don't have to leave the product to search docs), and it scales (automated, not CSM-dependent).

Motivation Barriers: Solutions

When customers understand the feature but don't care to use it.

Understanding the "Why Should I Care" Problem

Motivation failures happen when company value doesn't equal individual value.

Take time tracking. The company wants it for project profitability. Employees see it as micromanagement and extra work with no personal benefit, only burden. The result is minimal adoption, poor data quality, and resentment.

The root cause? The value proposition targets the wrong audience (company, not individual).

This is the WIIFM problem: "What's In It For Me?" If the answer is unclear or unsatisfying, adoption fails.

Value Proposition Clarity

Make individual benefits obvious.

A bad value prop (company-focused) sounds like: "Use [Feature] to improve organizational efficiency and enable better reporting for leadership." Which translates to: "Do extra work so executives get better dashboards."

A good value prop (individual-focused) sounds like: "Use [Feature] to eliminate manual report creation (saves you 4 hours per week) and automatically track your progress so you can prove your impact." Which translates to: "Do less work, look better."

Frame benefits as time saved (less work), recognition earned (visibility of contribution), problems avoided (mistakes prevented), career advancement (skills developed, results proven), or autonomy increased (less oversight because data provides accountability).

Solutions: Better Positioning, Proof of Value

Reframe your value proposition from "This helps the company..." to "This helps you personally by..."

For CRM adoption, the old pitch was "Enter opportunities so management can forecast revenue." The new pitch became "Track opportunities so you never lose track of deals, can prove your pipeline size, and get credit for everything you're working on."

Show proof, not theory. Instead of "This will save time," say "Sarah saved 6 hours last week using this. Here's how."

Proof formats include customer testimonials (peers saying it helped), before/after comparisons (concrete results), time-savings calculations (show the math), and success stories (real examples).

Motivation requires seeing value fast, so structure adoption for quick wins. Day 1: simple task that delivers immediate benefit. Week 1: first tangible result. Month 1: measurable improvement.

For a reporting tool, this might look like: Day 1 is building your first basic report in 10 minutes (quick win). Week 1 is replacing a manual spreadsheet with an automated report (time saved). Month 1 is presenting the exec team with insights only possible through the tool (career win).

Early wins create motivation momentum.

Incentives and Recognition

Create positive consequences for adoption.

Extrinsic motivation includes recognition (leaderboards, badges, shout-outs), rewards (swag, gift cards for power users), and competitions (team with highest adoption wins).

Intrinsic motivation taps into mastery (learning new skills), autonomy (control through better tools), and purpose (contributing to team success).

Management reinforcement looks like executives using the product visibly, usage discussed in 1-on-1s, adoption metrics tracked and celebrated, and non-adoption having consequences (expectations set).

One sales team saw adoption jump from 40% to 84% when the VP of Sales publicly used the CRM in meetings, a weekly leaderboard showed top users, Rep of the Month required CRM data to prove results, and non-users couldn't attend quota review without data.

Capability Barriers: Solutions

When customers want to adopt but can't (skills, time, resources).

Skills and Resource Constraints

Common capability gaps include skills gaps (feature requires technical knowledge users don't have, no time or resources to develop skills, learning curve too steep for busy users) and resource gaps (implementation requires dedicated time users don't have, needs additional tools/systems not available, requires team coordination that's hard to achieve).

Advanced analytics required SQL. Small teams without analysts couldn't adopt it because they had no SQL skills, couldn't hire for it, and couldn't learn fast enough. That's a capability barrier.

Technical Prerequisites

Hidden requirements block adoption.

Common prerequisites include clean data (if data is messy, features don't work), integrations (if systems don't connect, features are useless), infrastructure (enough licenses, right permissions), and platform compatibility (works on desktop but not mobile).

Discovery question: "What do you need before you can use this successfully?"

Solutions: Simplified Workflows, Better Enablement

Lower the bar by reducing complexity. Create "simple mode" and "advanced mode," provide no-code alternatives to technical features, and offer templates and pre-built configurations.

For the SQL barrier, one company built a visual query builder (no SQL required) and created 20 pre-built reports (just customize parameters). Analytics adoption jumped from 18% to 62%.

For high-value, high-complexity features, consider done-for-you services where the CSM sets it up for the customer initially, you provide a configuration service, or you offer a managed service tier.

Don't require all-or-nothing. Phase 1 is basic usage (low effort, quick value). Phase 2 is intermediate (once comfortable). Phase 3 is advanced (over time).

For marketing automation, this might be: Phase 1 is pre-built email campaigns (just customize). Phase 2 is building custom emails. Phase 3 is complex automation workflows. Gradual increase in complexity as capability grows.

Gradual Complexity Introduction

Use a progressive disclosure strategy.

Week 1 should be just the essentials: 3 core features only, simple workflows, pre-configured setup.

Month 1 adds intermediate features once the basics are mastered. Still guided, templates still available.

Month 3+ unlocks advanced capabilities: power user features, full flexibility and customization.

The benefit is that you never overwhelm. You build capability incrementally.

Environmental Barriers: Solutions

When the individual is willing but the organization prevents adoption.

Organizational Resistance

Common patterns include leadership not using the product (if the boss doesn't use it, the team won't prioritize it, lack of executive sponsorship), silos (one department adopts while others don't, cross-functional workflows break down), competing tools (different teams use different tools for the same purpose, data fragmentation, unclear which tool is "official"), and change resistance ("We've always done it this way," politics and turf protection).

Process and Policy Constraints

Examples include compliance requiring certain processes that the product doesn't support, IT policy blocking certain integrations, procurement rules preventing expansion, or contract limitations preventing full deployment.

Discovery question: "What organizational factors prevent full adoption?"

Solutions: Stakeholder Engagement, Change Management

Get leadership bought in by demonstrating ROI at the executive level, making an executive the champion, and having the exec mandate usage (top-down reinforcement).

Executive actions should include publicly using the product in meetings, requiring teams to report via the product, setting adoption goals and tracking them, and removing competing tools.

Marketing automation adoption was stuck at 35% until the CMO required all campaign reporting via the platform, used platform dashboards in exec meetings, and set a goal of 80% adoption in Q2. They hit 79%.

Get all stakeholders involved by mapping who needs to adopt for success, getting buy-in from each department, and aligning on shared goals and processes.

One CRM failed when sales adopted it but marketing didn't sync leads to it. It succeeded after a joint sales-marketing kickoff where they agreed on the lead process and both departments committed.

You can't succeed if five tools do the same thing. Consolidate onto one platform, decommission legacy tools, migrate data and users, and make the new tool the official system of record.

Executive Sponsorship

Why it's critical: it signals importance (if an exec cares, the team cares), removes organizational blockers, provides resources and priority, and enforces accountability.

How to secure it: Build a business case (ROI, strategic value), present to an executive (not just mid-level), get public commitment, and maintain regular exec engagement (don't just get buy-in and disappear).

Executive sponsorship actions should include kicking off the project personally, monthly check-ins on adoption progress, recognizing high adopters publicly, and addressing barriers escalated by the team.

Technical Barriers: Solutions

When the product itself blocks adoption (UX, performance, bugs).

UX Friction and Complexity

Common UX barriers include too many clicks to complete tasks, confusing navigation, unclear labeling, inconsistent patterns, poor mobile experience, and an overwhelming number of options.

Discovery methods include session recordings (watch users struggle), user testing (observe friction points), support tickets about "how to do X," and time-to-complete metrics (slow equals friction).

Performance and Reliability Issues

Technical problems kill adoption.

Performance issues include slow load times (more than 5 seconds), laggy interactions, and timeouts during workflows.

Reliability issues include frequent crashes, data loss, features that don't work, and integrations that fail.

User response: stop trying. It's too frustrating.

Solutions: Product Improvements, Workarounds

The ideal solution is to fix the product by prioritizing UX improvements, fixing performance bottlenecks, resolving bugs, and improving reliability.

The reality? Product improvements take time.

Interim solutions include documenting known issues and how to avoid them, providing alternative approaches, and having CSMs help navigate friction (workarounds). You can also offer managed services where CSMs do the hard part for customers temporarily until the product improves.

Manage expectations by being transparent about limitations, committing to a timeline for fixes, and keeping customers informed of progress.

CSMs are the voice of the customer, so escalate adoption-blocking issues with data: how many customers are affected, impact on adoption and retention, revenue at risk, and competitive disadvantage.

CSM Escalation to Product Team

Run an effective escalation process.

Document the issue: what's broken or difficult, how many customers are affected, adoption impact (usage data), workarounds if any, and customer quotes (real voice).

Quantify business impact: ARR at risk if not fixed, expansion opportunities blocked, churn likelihood, and competitive losses.

Escalate with urgency by submitting to the product team with evidence, requesting prioritization, and getting commitment on a timeline.

Close the loop by updating customers on progress, beta testing the fix with affected customers, validating the solution works, and communicating resolution.

Your job as a CSM is to make the product better by surfacing what blocks customers.

Barrier Prioritization and Action Planning

You'll find multiple barriers. You can't fix everything at once.

Impact vs Effort Matrix

Prioritize barrier removal using four quadrants.

Quadrant 1 is high impact, low effort (do first). These affect many customers and are easy to fix. Quick wins. A feature buried in a menu that you move to a prominent location has high impact (many customers don't find it) and low effort (UI change only). Do it immediately.

Quadrant 2 is high impact, high effort (plan and execute). These affect many customers but are hard to fix. Strategic initiatives. Building a no-code version of a feature that requires technical expertise has high impact (capability barrier blocks adoption) and high effort (significant product development). Roadmap it for next quarter.

Quadrant 3 is low impact, low effort (nice to have). These affect few customers but are easy to fix. Do if capacity is available. Rewriting unclear documentation for a niche feature has low impact (few use it) and low effort (just documentation). Backlog it, do when time permits.

Quadrant 4 is low impact, high effort (don't do). These affect few customers and are hard to fix. Not worth it. Custom development for an edge case feature request has low impact (1-2 customers) and high effort (engineering months). Defer or decline.

Quick Wins vs Strategic Initiatives

Quick wins (0-30 days) include communication fixes (awareness barriers), documentation improvements (knowledge barriers), UI tweaks (technical barriers), and CSM process changes (environmental barriers).

Strategic initiatives (3-6 months) include product UX overhauls, new features to reduce capability barriers, organizational change management programs, and platform performance improvements.

Balance both. Quick wins maintain momentum. Strategic initiatives solve deep problems.

Ownership and Accountability

Assign owners for each barrier type. Awareness barriers go to Marketing or CS Ops. Knowledge barriers go to Education or Enablement. Motivation barriers go to CS Leadership or Product Marketing. Capability barriers go to Product or Education. Environmental barriers go to CS Leadership or Sales. Technical barriers go to Product or Engineering.

Track progress by having owners commit to timelines, provide regular status updates, and measure barrier reduction through adoption metrics.

Measurement and Validation

How do you know a barrier is removed?

Before: Feature X has 12% adoption. Barrier is awareness (67% didn't know it existed).

Action: In-app announcement, email campaign, CSM mentions in calls.

After (60 days later): Feature X has 34% adoption. Survey shows awareness increased to 81%.

Validation: barrier reduced, adoption increased. Success.

Keep measuring. Don't assume a barrier is fixed and move on. Track over time. New barriers may emerge as adoption grows.

The Bottom Line

Adoption doesn't fail because customers are lazy or unwilling. It fails because barriers block them—barriers you can identify and remove.

Teams that systematically identify and remove barriers achieve 50-70% higher feature adoption (versus hoping adoption happens), 30% faster time to value (barriers removed early), 25% fewer support tickets (friction eliminated), and higher retention (value realization unlocked).

Teams that ignore barriers and just push harder on training experience stagnant adoption despite more education, frustrated customers and CSMs, wasted resources on wrong solutions, and preventable churn.

The fundamentals: six barrier types (awareness, knowledge, motivation, capability, environmental, technical). Each requires a different solution (more training doesn't fix awareness or motivation). Discover barriers through data plus customer conversations. Prioritize highest impact, lowest effort first. Measure to validate barriers are actually removed.

Build your barrier identification and removal process. Your adoption depends on it.

Ready to remove what's blocking adoption? Explore adoption fundamentals, product adoption framework, and feature adoption strategy.

Learn more:

Tara Minh

Operation Enthusiast