Customer Effort Score: How to Measure & Improve It [2026]

For enterprise executives navigating the digital transformation, the Customer Effort Score (CES) remains the most effective predictor of customer loyalty and churn mitigation in service interactions. Indeed, research shows that exceeding expectations offers only marginal returns; instead, minimizing customer effort—the "work they must do to get their problem solved"—is the key driver of loyalty.

In 2026, with the proliferation of Generative AI, the challenge for organizations is no longer if to automate, but how to architect conversational systems that inherently reduce friction. This article examines the CES framework, its predictive power, and the architectural shifts required to embed low-effort service at the core of enterprise operations.

What is the Customer Effort Score (CES)?

The CES was developed and popularized by a team of researchers from The Corporate Executive Board (CEB), which is now part of Gartner. The metric and its core philosophy were detailed by Matthew Dixon, Karen Freeman, and Nicholas Toman, introduced to a wide audience in their influential 2010 Harvard Business Review article, “Stop Trying to Delight Your Customers.”

The key finding from their study of over 75,000 customer interactions was that delighting customers (aiming for high satisfaction) did not significantly increase loyalty, but reducing customer effort (minimizing friction) was highly effective at mitigating disloyalty and driving retention. This led to the development of the CES metric to measure this specific aspect of the customer experience.

How to Measure Customer Effort Score?

CES is measured by asking a single, transactional question: “How much effort did you personally have to put forth to handle your request?”. It is scored typically on a 1 (very low effort) to 5 (very high effort) scale. 

What is a Good Customer Effort Score?

A “good” CES is one that trends towards low effort (closer to 1 on the 1-to-5 scale). More important than an absolute number is the trend. A decreasing CES over time demonstrates that organizational efforts are successfully mitigating friction.

The Predictive Power of CES

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According to Harvard Business Review, the CEB study found that CES outperformed both Customer Satisfaction (CSAT) and the Net Promoter Score (NPS) in predicting customer loyalty following service interactions. 

• Low Effort Outcomes: Customers reporting low effort were highly likely to repurchase (94%) and increase spending (88%). Critically, only 1% of this group would speak negatively about the company.
• High Effort Outcomes: Conversely, 81% of customers who had a hard time solving their problems reported an intention to spread negative word of mouth.

CSAT vs NPS vs CES

While the CES framework argues for efficiency, it does not fully dismiss the idea of positive experiences. CES is primarily a tool for mitigating disloyalty. The table below outlines the exact differences between CES, NPS, and CSAT.

Why is the Customer Effort Score Important to Enterprises?

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CES provides compelling commercial and operational intelligence that’s strategically important to enterprises. 

1. High Predictive Power for Loyalty and Repurchase

CES is highly predictive of future customer behavior, especially the intention to remain a customer and spend more. This direct correlation between service design and future revenue makes CES an essential metric for the CFO.

2. Drives Operational Efficiency and Cost Reduction

Focusing on reducing customer effort necessarily drives the simplification of internal processes, leading to substantial financial benefits. By eliminating high-effort scenarios like repeated contacts and transfers, enterprises reduce the cost to serve.

3. CES Provides Actionable, Touchpoint-Specific Insights

CES is a transactional metric, providing immediate and clear guidance for operational teams. Because CES is measured directly after a service interaction, a low score instantly flags the specific process (e.g., the IVR menu or self-service flow) that requires optimization.

How to Design Customer Service for Low Effort?

Minimizing effort requires solving the structural issues that cause high friction: repeated contacts, channel switching, and having to repeat information. For enterprises leveraging AI, this necessitates architectural integration of low-effort design.

Strategy 1: Forward Resolution via Automated Workflows

Study shows that the biggest cause of excessive customer effort is the need to call back. Even if the primary issue is solved, 22% of repeat calls involve downstream issues related to the original problem.

• Implementation Focus: Conversational platforms must support the design of complex, branching workflows that guide customers to solutions for commonly related issues (e.g., following an address change with suggested next steps for new checks). Bell Canada reduced "calls per event" by 16% using this strategy.

Strategy 2: Minimizing Channel Switching via Omnichannel Consistency

A significant friction point is when customers, frustrated by self-service, are forced to switch channels (e.g., calling after failing on the website). 

• Implementation Focus: Platforms should enable the development of a single conversational logic base that deploys reliably across multiple channels (web chat, voice IVR). Furthermore, the design must ensure that the customer is guided to the best-suited channel, such as nudging technically savvy users toward online communities.

Strategy 3: Seamless Human-Agent Handoff (Context Preservation)

When an AI cannot resolve an issue, the handoff to a human agent is a critical CES moment. A failed handoff forces the customer to repeat information.

• Implementation Focus: The conversational platform must be architected with explicit, configurable triggers for handoff (e.g., high emotional signals, complexity exceeding scope). Crucially, the system must automatically generate and transfer a concise, human-readable summary of the interaction history and steps taken for the agent's display. 

How to Improve Your Company’s Customer Effort Score Fast

To achieve rapid, systemic improvement in CES, enterprises must transition from fragmented tooling to an integrated conversational architecture.

With AI adoption accelerating, the platform you choose to build your conversational experience on is the architectural key to reducing CES, mitigating disloyalty, and controlling operational costs. Voiceflow is positioned as the platform of choice for enterprises because it provides the architectural tools necessary to address the root causes of high CES by enabling scalable, collaborative, and context-aware conversational design.

Voiceflow empowers teams to quickly implement architectural fixes—like automated multi-step Forward Resolution and sophisticated Context Preservation during handoffs—that directly target the structural causes of high effort, particularly repeat calls, channel switching, and having to repeat information.

We encourage your team to book a free demonstration today to see how the platform’s unique capabilities can be applied to your most high-effort customer journeys.