Customer Effort Score (CES)
Customer effort score (CES) is a metric that measures how much effort a customer had to exert to get their issue resolved, their question answered, or their request fulfilled through a support interaction.
In Depth
Customer effort score has emerged as a more powerful predictor of customer loyalty than traditional satisfaction metrics. Harvard Business Review research found that 96% of customers who have high-effort experiences become disloyal, compared to only 9% of those with low-effort experiences. The metric is typically measured on a 1-7 scale after an interaction, asking customers to rate the statement: 'The company made it easy to handle my issue.' What drives high effort? Multiple transfers between agents, having to repeat information, long wait times, confusing self-service options, and requiring multiple contacts to resolve one issue.
AI eliminates virtually all of these friction points. An AI agent never transfers you to another department mid-conversation — it has access to all systems simultaneously. You never repeat your information because the AI reads your full history instantly.
There are no wait times at 2 AM or during holiday rushes. GuruSup customers consistently report CES improvements of 40-60% after AI deployment, with the average score moving from 4.2 to 6.1 on a 7-point scale, because the AI removes the operational friction that makes support feel like work for the customer.
Related Terms
CSAT Score
CSAT (Customer Satisfaction Score) is a metric that measures how satisfied customers are with a specific interaction or overall service, typically collected through post-interaction surveys.
First Contact Resolution (FCR)
First contact resolution (FCR) is the percentage of customer support inquiries that are fully resolved during the initial interaction, without requiring follow-up contacts, transfers, or escalations.
Average Handle Time (AHT)
Average handle time (AHT) is the mean duration of a customer support interaction from start to finish, including talk time, hold time, and any after-call work required to resolve the issue.
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