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Customer Experience

Founder, Oxaide

Master Customer Effort Score (CES) measurement, benchmarks, and improvement strategies. Research-backed methods for reducing customer effort and driving loyalty.

December 5, 2025
12 min read
AI Desk Team

Customer Effort Score measures how easy or difficult it is for customers to accomplish what they want. Research shows it is the strongest predictor of customer loyalty—more than satisfaction, more than delight.

The insight is counterintuitive: you do not win customer loyalty by exceeding expectations. You win by removing friction.

This guide covers everything about CES: how to measure it, what the benchmarks are, and most importantly, how to reduce customer effort.

What Is Customer Effort Score?

The Definition

Customer Effort Score (CES) measures the amount of effort a customer had to expend to:

  • Get an issue resolved
  • Complete a purchase
  • Find information
  • Use a product feature
  • Accomplish any goal with your company

The Research Behind CES

The concept comes from the book "The Effortless Experience" by Dixon, Toman, and DeLisi (CEB/Gartner), based on research with 97,000+ customers across industries.

Key findings:

  • 96% of customers who have high-effort experiences report being disloyal
  • Only 9% of customers with low-effort experiences report disloyalty
  • Delighting customers does not build loyalty—reducing effort does
  • Every increase in effort increases likelihood of churn by 12%

CES vs. CSAT vs. NPS

Metric Measures Question Scale
CES Effort "How easy was it to..." 1-7 (effort scale)
CSAT Satisfaction "How satisfied were you..." 1-5
NPS Loyalty "How likely to recommend..." 0-10

When to use CES: After specific interactions (support tickets, purchases, feature use).

When to use CSAT: After support interactions, general satisfaction pulse.

When to use NPS: Relationship-level measurement, quarterly or biannually.

How to Measure CES

The Standard CES Question

The most widely used CES question:

"To what extent do you agree with the following statement: [Company] made it easy for me to handle my issue."

Scale: 1-7

  • 1 = Strongly Disagree (high effort)
  • 7 = Strongly Agree (low effort)

Alternative wording:

"How easy was it to [specific action]?"

Scale: 1-7

  • 1 = Very Difficult
  • 7 = Very Easy

Calculating CES

Method 1: Average Score

CES = Sum of all responses ÷ Number of responses

Example: 50 responses totaling 285 → CES = 5.7/7

Method 2: Percentage Low Effort

Low Effort % = (Responses 5-7 ÷ Total responses) × 100

Example: 40 out of 50 responded 5-7 → 80% low effort

Method 3: CES Index (effort index)

CES Index = % Low Effort (5-7) - % High Effort (1-3)

Example: 80% low effort, 10% high effort → CES Index = 70

2025 Benchmarks

Average CES Score (1-7 scale):

Industry Excellent Good Needs Work
E-commerce 6.0+ 5.3-6.0 Under 5.3
SaaS 5.8+ 5.0-5.8 Under 5.0
Financial Services 5.5+ 4.8-5.5 Under 4.8
Telecommunications 5.0+ 4.3-5.0 Under 4.3
Healthcare 5.3+ 4.5-5.3 Under 4.5

Low Effort Percentage:

Performance % Low Effort (5-7)
Excellent 80%+
Good 65-80%
Average 50-65%
Poor Under 50%

When to Survey

Best timing: Immediately after the interaction ends.

Survey CES after:

  • Support ticket resolution
  • Purchase completion
  • Self-service interaction
  • Onboarding milestone
  • Feature first use

Avoid surveying:

  • During active problem resolution
  • After every single interaction (survey fatigue)
  • For partial/incomplete interactions

Survey Best Practices

1. Keep it short CES survey should be 1-3 questions maximum:

  • The CES question (required)
  • Open-ended "What would have made this easier?" (optional)
  • Issue categorization (optional)

2. Respond to low scores When someone reports high effort (1-3), trigger:

  • Immediate acknowledgment
  • Follow-up from support lead
  • Root cause investigation

3. Track by segment Measure CES by:

  • Channel (chat, email, phone)
  • Issue type
  • Customer segment
  • Agent/team
  • Time of day

The Seven Sources of Customer Effort

The research identifies seven primary drivers of customer effort. Understanding these helps you target improvements.

1. Repeat Contact

Definition: Customer has to contact you multiple times for the same issue.

Impact: Each additional contact doubles perceived effort.

Causes:

  • Issue not fully resolved
  • Waiting for follow-up that never comes
  • Information not passed between agents
  • Customer needs to re-explain

Solutions:

  • First Contact Resolution focus
  • Proactive follow-up
  • Complete resolution verification
  • Context preservation across contacts

2. Channel Switching

Definition: Customer must change channels to get help (started on chat, has to call).

Impact: Channel switching increases effort 1.5x.

Causes:

  • "You need to call for this"
  • Technical limitations of channel
  • Lack of agent authority on certain channels
  • Chatbot failures

Solutions:

  • Channel consistency (resolve in started channel)
  • Warm handoffs when switching is necessary
  • Equal authority across channels
  • Seamless escalation without restart

3. Transfers

Definition: Customer is passed between departments/agents.

Impact: Each transfer increases effort significantly.

Causes:

  • Incorrect initial routing
  • Specialized departments required
  • Agent skill gaps
  • Organizational silos

Solutions:

  • Skill-based routing
  • Broader agent training
  • Warm transfers with context
  • First-contact empowerment

4. Repeating Information

Definition: Customer has to explain their issue multiple times.

Impact: One of the most frustrating experiences for customers.

Causes:

  • No context passed during transfers
  • Agent does not read ticket history
  • Different systems not connected
  • Poor documentation

Solutions:

  • Unified customer view
  • Context displayed before transfer
  • Integration between systems
  • AI-assisted context summary

5. Robotic Service

Definition: Agent follows script without addressing actual customer need.

Impact: Customers feel unheard and frustrated.

Causes:

  • Over-scripting
  • Lack of agent empowerment
  • Metrics focused on speed over quality
  • Inadequate training

Solutions:

  • Flexible guidelines vs. rigid scripts
  • Agent judgment empowerment
  • Quality-focused metrics
  • Active listening training

6. Generic Service

Definition: One-size-fits-all approach regardless of customer history or context.

Impact: Customers expect personalization.

Causes:

  • No access to customer history
  • Volume pressure prevents personalization
  • Systems do not surface relevant context
  • No customer segmentation

Solutions:

  • Customer context available to agents
  • Personalization flags in system
  • VIP/high-value treatment tiers
  • AI-powered personalization

7. Policies That Frustrate

Definition: Company policies that create unnecessary barriers.

Impact: Even perfect execution of bad policy creates effort.

Causes:

  • Legacy policies never revisited
  • Legal/compliance over-caution
  • Internal convenience over customer convenience
  • Lack of customer feedback loop

Solutions:

  • Regular policy review with CES data
  • Customer advocacy in policy decisions
  • Exception frameworks for obvious cases
  • Continuous policy improvement process

Reducing Customer Effort: Strategy and Tactics

Strategic Approach

1. Identify highest-effort touchpoints Use CES surveys to find where effort is highest.

2. Understand root causes Analyze the seven sources for each high-effort area.

3. Prioritize by impact and feasibility Not all improvements are equal. Focus on high-impact, achievable changes.

4. Measure improvement Track CES changes after each intervention.

Quick Wins (Implement in 1-2 weeks)

Reduce repeat contacts:

  • Add "Is there anything else?" before closing
  • Proactive follow-up on complex issues
  • Resolution verification surveys

Reduce information repetition:

  • Display customer history to agents
  • Pass context in all transfers
  • Pre-populate known information

Improve communication:

  • Set clear expectations for resolution time
  • Proactive status updates
  • Clear next steps in every interaction

Medium-Term Improvements (1-3 months)

Self-service enhancement:

  • Answer top 20 questions in knowledge base
  • Improve search functionality
  • Add chatbot for common issues

Process simplification:

  • Reduce steps in common workflows
  • Eliminate unnecessary verification
  • Empower agents to resolve without escalation

Channel optimization:

  • Enable resolution in customer's preferred channel
  • Reduce "please call us" redirections
  • Seamless cross-channel experience

Long-Term Transformation (3-12 months)

System integration:

  • Unified customer view across all systems
  • Real-time context sharing
  • Predictive issue detection

Policy overhaul:

  • Customer-centric policy review
  • Exception framework development
  • Continuous improvement process

Culture shift:

  • Effort reduction as key metric
  • Agent empowerment program
  • Customer voice in decision-making

CES and AI Customer Support

How AI Reduces Effort

Instant response: No waiting reduces effort immediately.

24/7 availability: Customers get help when they want it.

Context retention: AI remembers everything from the conversation.

Consistent accuracy: Same correct answer every time.

Self-service enablement: Customers can resolve issues themselves.

CES Benchmarks: AI vs. Human

Metric Human Support AI Support
Average CES 5.2 5.6
Low Effort % 65% 75%
High Effort % 15% 10%

Data from companies with well-implemented AI support

Why AI scores higher on effort:

  • No waiting for human availability
  • No hold times
  • Instant information retrieval
  • Consistent process following

Where AI can create effort:

  • Poor understanding of query
  • Inability to handle exceptions
  • No escalation path
  • Frustrating loops

AI Implementation for Low Effort

Do:

  • Easy escalation to human when needed
  • Context preservation when escalating
  • Clear communication of AI limitations
  • Continuous improvement from feedback

Do Not:

  • Trap customers with no human path
  • Make customers repeat information to human
  • Over-promise AI capabilities
  • Ignore AI failure patterns

Implementing a CES Program

Phase 1: Measurement Setup (Week 1-2)

1. Choose survey tool Options: built-in support platform surveys, Delighted, SurveyMonkey, custom

2. Design survey Keep it minimal: CES question + optional open-ended

3. Determine trigger points After ticket resolution, after purchase, after feature use

4. Establish baseline Run for 30 days before making changes

Phase 2: Analysis (Week 3-4)

1. Calculate overall CES Average score and low-effort percentage

2. Segment analysis CES by channel, issue type, customer segment

3. Identify lowest CES areas Where is effort highest?

4. Root cause investigation What is driving effort in problem areas?

Phase 3: Improvement (Month 2-3)

1. Prioritize initiatives High impact + high feasibility first

2. Implement quick wins See quick wins list above

3. Track changes Monitor CES as changes roll out

4. Adjust based on results Double down on what works

Phase 4: Ongoing Optimization (Ongoing)

1. Regular CES review Weekly for operational teams, monthly for leadership

2. Trend monitoring Is effort decreasing over time?

3. Continuous improvement Regular initiative pipeline

4. Customer feedback loop Open-ended responses drive priorities

CES Dashboard Essentials

Key Visualizations

1. CES Trend Line chart showing CES score over time (weekly/monthly)

2. Low/High Effort Split Pie or bar chart showing percentage in each category

3. CES by Segment Bar charts comparing:

  • By channel
  • By issue type
  • By agent/team
  • By customer tier

4. Effort Drivers From open-ended responses, categorize and count:

  • "Had to call multiple times"
  • "Long wait time"
  • "Agent didn't understand"
  • etc.

5. Improvement Tracking Before/after comparison for each initiative

Alert Thresholds

Condition Action
CES drops below 5.0 Immediate investigation
High effort % exceeds 20% Weekly review escalation
Individual low score (1-2) Immediate follow-up
Agent CES below average Coaching trigger

Key Takeaways

  1. Effort predicts loyalty: More than satisfaction or delight
  2. Seven sources: Repeat contact, channel switching, transfers, repetition, robotic service, generic service, bad policies
  3. Measure after interactions: Not during, not too frequently
  4. Segment your data: Overall CES hides important patterns
  5. Start with quick wins: Many improvements are simple
  6. AI reduces effort: When implemented correctly
  7. Continuous improvement: CES is ongoing, not one-time

Reduce Customer Effort with Oxaide

AI customer support that minimizes effort:

  • Instant responses: No waiting, no hold times
  • 24/7 availability: Help when customers need it
  • Context preservation: No repeating information
  • Easy escalation: Seamless path to humans when needed

Try Oxaide free for 14 days


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    Founder, Oxaide | Oxaide