Customer Satisfaction Score (CSAT)

What Is a Customer Satisfaction Score (CSAT)?

A Customer Satisfaction Score (CSAT) is a metric that measures how satisfied customers are with a specific interaction, product, or experience. It is the most widely used customer service KPI, typically captured through a short post-interaction survey that asks customers to rate their experience on a scale (most often 1 to 5). CSAT gives support teams a direct, real-time pulse on service quality, making it essential for tracking the impact of changes to workflows, staffing, and AI customer service deployments.

Unlike broader loyalty metrics such as Net Promoter Score (NPS) or Customer Effort Score (CES), CSAT focuses on a single moment. That specificity makes it powerful for isolating what works and what does not across channels, agents, and AI Agents.

How to Calculate CSAT

The standard CSAT formula uses a "top-box" method. After collecting survey responses on a 1 to 5 scale, count only the positive ratings (4 and 5) and divide by the total number of responses:

CSAT (%) = (Number of Satisfied Responses / Total Responses) x 100

For example, if 200 customers respond and 150 rate a 4 or 5, your CSAT is 75%. Some organizations use a 1 to 10 scale, counting the top two or three boxes as "satisfied." The key is consistency: pick a scale, define the threshold, and measure the same way every time so trends are meaningful. Trigger surveys immediately after an interaction for the most accurate feedback.

Industry Benchmarks

A "good" CSAT score generally falls between 75% and 85%. The American Customer Satisfaction Index (ACSI) reported a national average of 77.0 in Q1 2025 and 76.9 in Q4 2025 across 400+ companies in 40+ industries. Top performers in retail and e-commerce often exceed 80%, while industries like telecommunications and utilities trend closer to 70 to 74%.

Industry research: According to the American Customer Satisfaction Index (ACSI), the 2025 national customer satisfaction average holds at roughly 77 on a 100-point scale, with wide variance by sector. Companies that invest in AI-powered support and first contact resolution consistently outperform their industry average.

Context matters when interpreting benchmarks. A 78% CSAT in a high-complexity B2B environment may be stronger than an 82% in simple retail returns. Always compare against your own historical trend and your specific industry peers.

Why CSAT Matters for Support Teams

CSAT connects directly to business outcomes: satisfied customers repurchase more, churn less, and refer more. Research shows over 50% of consumers will switch to a competitor after just one bad support experience.

For teams deploying AI Agents, CSAT is the ultimate proof point. Tracking CSAT by channel (human agent vs. AI Agent vs. self-service portal) reveals where AI is delivering and where it needs refinement. CSAT also ties to other critical metrics: a high resolution rate and low average handle time (AHT) correlate with higher CSAT, while rising ticket volume without added capacity erodes it.

CSAT vs. NPS vs. CES

CSAT, NPS, and CES each measure different dimensions of the customer experience. CSAT captures satisfaction with a specific interaction. NPS measures long-term loyalty by asking how likely a customer is to recommend your company. CES gauges how easy it was to get an issue resolved. The best support operations track all three, but CSAT is the most actionable for daily service management because it ties to individual touchpoints.

Because CSAT can be measured after every interaction (unlike quarterly NPS), it lets teams spot problems fast, whether a new AI workflow is underperforming or a particular issue type is dragging down satisfaction.

The Maven Advantage: AI That Drives CSAT Up

Maven AGI is built around the principle that resolution drives satisfaction. When an AI Agent truly resolves a customer's issue on the first interaction, CSAT follows. That is why Maven focuses on resolution rate as the north star, not deflection.

Maven proof point: Mastermind, an EdTech company, achieved a 93% live chat resolution rate with Maven AGI, deployed in just 6 weeks. When customers get real answers on the first try, satisfaction scores reflect it.

Maven AGI's approach integrates with 100+ systems to give AI Agents full context on every interaction. The platform's AI Copilot supports live agents with real-time suggestions, further improving outcomes. And because Maven tracks resolution and CSAT together, teams can see the direct relationship between AI performance and customer happiness. Explore how leading analysts frame the connection between AI and satisfaction in ACSI's industry benchmarks and McKinsey's research on gen AI in customer care.

Frequently Asked Questions

What is a good CSAT score?

A good CSAT score falls between 75% and 85%, though this varies by industry. The national ACSI average is approximately 77%. E-commerce and retail often exceed 80%, while telecom trends lower. The most important benchmark is your own trend over time.

How often should you measure CSAT?

Measure CSAT after every customer interaction for the most actionable data. Post-chat, post-call, and post-ticket surveys give you real-time visibility into service quality. Aggregate the results weekly or monthly to identify trends, and segment by channel, issue type, and agent (human or AI) to pinpoint improvement opportunities.

Can AI-powered support improve CSAT scores?

Yes, when the AI genuinely resolves issues rather than deflecting them. AI Agents that provide accurate, personalized answers on the first interaction improve both first contact resolution and CSAT simultaneously. Maven AGI customers like Papaya Pay achieve 90% autonomous resolution, which directly lifts satisfaction because customers get fast, accurate answers without waiting in a queue.

What is the difference between CSAT and resolution rate?

CSAT measures how the customer feels about the experience. Resolution rate measures whether their problem was actually solved. The two are closely related: a high resolution rate is the strongest driver of high CSAT. However, CSAT can also be influenced by factors like wait time, tone, and ease of interaction, which is why tracking both metrics together gives the clearest picture of service performance.

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