Customer Experience (CX) is an AI-generated score that measures how customers feel about their support experience - across both Fin and human interactions. It gives support leaders and teams full visibility into customer sentiment, without relying on surveys.

In this article, you'll learn about the challenges the CX Score aims to solve, how to access and interpret your scores, and best practices to maximize its value.

Note: The Customer Experience (CX) Score is currently in open beta and available to all Fin customers who meet the following criteria:

Have imported conversations from your source platform (e.g. Zendesk or Salesforce) which you can toggle on and off.
Have deployed Fin.

What challenges does the CX Score help solve?

The CX Score is helping support leaders and teams address the following issues:

Surveyed CSAT is incomplete and biased - It captures feedback from a small, self-selecting group, often over representing extreme opinions.
Customers score AI and human agents differently - Customers tend to score AI support more harshly, making it hard to assess AI fairly.
Disengaged customers go unmeasured - Customers who don’t respond to surveys - including those who had a neutral or frustrating experience - are often left out of satisfaction metrics.
There’s no scalable way to measure satisfaction across all AI conversations - Without full coverage, teams struggle to track trends, identify friction points, and improve overall support quality.
Survey design can skew results - Small changes, like survey timing or phrasing, impact scores without support quality having changed.

The CX Score addresses these gaps by scoring every meaningful interaction—without relying on surveys—so support teams can get a fuller, more consistent view of customer sentiment across both Fin and teammate conversations.

Note: Fin needs to be set live to see your CX Score across all conversations.

How CX Score works

The CX Score uses machine learning to score every meaningful conversation. It analyzes signals like customer sentiment, resolution status, and service quality to predict whether the customer was satisfied.

Customer sentiment - looks at the tone and language the customer uses throughout the conversation to understand how they’re feeling.
Resolution status - reflects whether the customer’s questions or issues were clearly addressed, even if they didn’t explicitly confirm it. The model evaluates all the issues raised during the conversation and assesses how many were resolved.
Service quality - considers how helpful, clear, and timely the responses were—across both Fin and teammates. This includes tone, depth of knowledge, ability to resolve issues, and speed of response.

These signals are gathered across all three areas to generate a score ranging from 1 to 5, where 1–3 are considered negative and 4–5 are considered positive. The CX Score is then calculated as follows:

Number of positive Customer Experience ratings [4s and 5s] / Total number of Customer Experience ratings × 100.

Specific criteria for CX Score

A conversation will receive a CX rating once all of the following conditions are met:

The conversation has been closed.
It includes at least 2 replies from the customer.
It includes at least 2 replies from Fin.
There is enough conclusive information in the conversation to determine a rating.
The conversation is over messenger or email (not phone).

This gives you a consistent, objective view of customer satisfaction without relying on survey responses. To keep scores accurate, it automatically filters out spam.

How to access your CX Score

Performance report

To see your CX Score, go to Analyze > Performance and you will see the Customer Experience (CX) score chart toward the top of the report.

You'll see the percentage of positive customer ratings out of all ratings received for conversations handled exclusively by Fin, without any human agent involvement.

This score reflects how satisfied customers are with Fin's service. Click Drill-in to view the conversations behind Fin’s CX Score, along with a summary that highlights key moments and explains why each score was given.

Topics Explorer

From Analyze > Topics Explorer you can track performance by topic. Each topic includes CX Score so you can see which issues are handled well and which need attention.

Focus where it matters most by identifying high-volume, poor customer experience topics and click on them to see the tree map and line charts broken down by subtopics. This enables you to make targeted improvements to the most impactful subtopics by addressing the root cause of the volume and negative CX.

Note: You must have enough eligible conversations to start seeing topics with CX Scores. Learn more about AI-generated topics and subtopics.

Getting the most from your CX Score

To maximize the value of your CX Score, we recommend the following:

Action	What to check
Track trends and patterns	Are scores improving or declining after changes in support content, workflows, or product updates? Do certain categories (e.g., AI Agent vs. Teammate) perform better over time?
Investigate low-scoring conversations	Are common themes emerging in low-rated interactions? Are customers dissatisfied with specific responses or resolution times?
Explore AI-generated explanations	What were the main concerns, resolution status, and sentiment for specific interactions? Are there common friction points affecting satisfaction?

FAQs

How is the CX Score different from CSAT?

Traditional CSAT surveys offer a narrow and often biased view of customer satisfaction. Response rates are low, feedback tends to reflect only extreme experiences, and AI support is often rated more harshly than human-led conversations.

I don’t agree with some of the CX Scores. What can I do?

Just like with CSAT, if you believe a CX Score isn’t accurate or shouldn’t be counted, you can tag the conversation (e.g., with “exclude_from_cx”). Then, use that tag to filter out those conversations in your reports.

Can CX Score be used to measure individual teammate performance?

Yes, CX Score can help assess individual teammate performance, especially when a teammate handles the entire conversation from start to finish. In these cases, the rating can reasonably be attributed to that teammate’s work. However, in conversations involving multiple participants (e.g., Fin starts the conversation and a teammate finishes it), the CX Score reflects the overall customer experience rather than individual contributions.

It's also worth noting that surveyed CSAT wasn’t perfect for agent-level attribution. The CSAT survey typically goes to the customer at the end of the conversation and is worded as feedback on the last person involved. However, customers may be rating the entire experience—including Fin and earlier agents who responded to the conversation.

Why can’t I filter by CX rating on some charts in the Custom Report?

"Customer Experience (CX) rating" and "Customer Experience (CX) explanation" attributes are only available on metrics that are derived from Conversations dataset.

Understand customer experience at scale with the Customer Experience (CX) Score