What Is Customer Effort Score (CES)?

Last Updated September 22, 2026

Customer Effort Score, or CES, is a customer experience metric used to measure how much effort a customer feels they had to expend to complete a task, get an answer or resolve an issue. It is especially useful for service journeys because customers often value ease and resolution more than an elaborate interaction.

How CES is measured

A common CES survey asks customers to rate how easy it was to handle their request, often using a five- or seven-point scale. Organizations may phrase the question differently, so comparisons are only meaningful when the wording and scale remain consistent.

A simple CES average can be calculated by adding all response scores and dividing by the number of responses. Some teams instead report the percentage of customers who selected favorable responses.

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CES vs. CSAT vs. NPS

When Customer Effort Score is most useful

• After a support interaction.
• After self-service or chatbot completion.
• After onboarding or account setup.
• After a return, refund or billing process.
• After a transfer between channels.
• After a high-friction digital task such as authentication or form completion.

What creates high customer effort

Customers experience effort when they repeat information, search unsuccessfully, wait through unnecessary transfers, encounter inconsistent answers or must contact the company multiple times. Effort can also come from a broken policy or back-office process even when the agent performs well.

That is why CES should be linked with repeat contact, transfer rate, journey data, interaction analytics and customer intent.

How to improve CES

1. Find the journeys with the lowest effort scores or highest abandonment.
2. Read open-ended feedback and analyze conversations for the reason.
3. Identify whether the friction comes from knowledge, policy, routing, systems or product design.
4. Fix the underlying step rather than only the symptom.
5. Measure whether both customer effort and operational outcomes improve.

AI and customer effort

AI can reduce effort through better self-service, intent-based routing, faster knowledge retrieval and automated workflow completion. It can also analyze unstructured conversations to find effort signals among customers who never complete a survey.

Automation can increase effort if it traps customers in a bot or forces them to repeat themselves. Measure the entire journey, not just containment.

Also related

• Churn Rate
• Customer Acquisition Cost
• Customer Retention Rate
• First Call Resolution
• Promoter
• Resolution Rate