Customer Effort Score
Definition
Customer Effort Score (CES) is a customer experience metric that measures the ease of a customer interaction — specifically, how much effort the customer had to put in to get their issue resolved or complete a task. The standard CES survey asks: 'How easy was it to [resolve your issue / complete your task]?' on a 1-7 scale from 'Very Difficult' to 'Very Easy'. CES was developed by the Corporate Executive Board (now Gartner) after research showed that reducing customer effort is a stronger predictor of loyalty than delighting customers. High effort predicts churn; low effort predicts retention.
Why It Matters
CES cuts to the core of what drives customer loyalty in support interactions: ease of resolution. Customers do not expect to be wowed by support — they expect their problems to be resolved quickly and easily. High-effort experiences (multiple contacts, transfers, repeated explanations, complex processes) are correlated with churn and negative word-of-mouth. CES is particularly valuable for evaluating AI chatbot and self-service experiences, where the goal is to make assistance as frictionless as possible. A self-service resolution that requires 15 steps has high effort even if it technically worked.
How It Works
CES surveys are sent immediately after a defined interaction — typically ticket closure or chat session end. The survey asks the effort question and optionally follows up with open-ended feedback. CES scores are aggregated and analyzed to identify high-effort interaction types — these become priorities for process simplification, better self-service content, or AI automation. For AI chatbot optimization, CES scores on bot-handled interactions identify where the conversation flow creates unnecessary steps, confusion, or back-and-forth that could be streamlined.
Customer Effort Score — Survey and Distribution
Survey: "How easy was it to resolve your issue today?"
Score Distribution
CES Score
5.2
out of 7
Correlation to churn
Real-World Example
A 99helpers customer implements CES surveys after each AI chatbot interaction and finds that the overall CES score is 5.1/7. Analyzing low-effort (6-7) versus high-effort (1-3) interactions, they discover that chatbot conversations involving account changes have average CES of 3.2 — driven by a requirement to verify identity through a multi-step process. They streamline the verification to a single authentication step. Account change CES improves to 5.8, and chatbot abandonment rate on account change tasks drops by 45%.
Common Mistakes
- ✕Confusing CES with CSAT — CSAT measures satisfaction with the outcome; CES measures effort of the process; both are valuable but distinct
- ✕Optimizing only for low effort without ensuring resolution quality — making it very easy to close a ticket without resolving the issue improves CES but destroys CSAT
- ✕Not tracking CES by channel — effort varies significantly across self-service, chat, email, and phone; aggregate CES hides important channel-specific insights
Related Terms
Customer Satisfaction Score
Customer Satisfaction Score (CSAT) is a metric that measures how satisfied customers are with a specific interaction, product, or experience, typically collected through a simple post-interaction survey asking customers to rate their satisfaction on a numeric scale.
Net Promoter Score
Net Promoter Score (NPS) is a customer loyalty metric that asks customers how likely they are to recommend a company to others on a 0-10 scale, classifying them as Promoters, Passives, or Detractors.
Customer Experience
Customer experience (CX) is the overall perception a customer forms from every interaction with a brand across the entire customer journey, from first awareness through purchase, onboarding, support, and renewal.
Deflection Rate
Deflection rate is the percentage of potential support contacts that are resolved through self-service, AI chatbots, or automated tools without requiring a human agent, measuring the effectiveness of automated and self-service support.
Self-Service Rate
Self-service rate measures the percentage of customers who successfully resolve their issues independently through knowledge bases, FAQs, AI chatbots, or other self-service tools without contacting a human agent.
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