Customer sentiment: How to measure, analyze, and act on it

You pick up on it instantly: the relieved customer, the frustrated one, the one who’s been bounced around too many times. 

But what if you could turn the understanding you get from talking to customers into actionable insights? Look at it this way: 58% of customers are willing to pay more for better customer service. That means customer sentiment isn’t just a nice-to-have metric — it directly impacts your bottom line.

Maybe you think collecting the data to measure customer sentiment is something only enterprises can afford and have the bandwidth for. But it’s just as possible for small businesses. 

In this article, we’ll cover everything you need to know about customer sentiment: what it is, how to analyze it, and how to start collecting the data you need. We’ll also share some tips on what to do with the information you find.

What is customer sentiment?

Customer sentiment measures your customers’ emotions and attitudes about your company or service. You can collect it across all customer interactions. For example:

• Phone 
• Chat
• Email
• Social media platforms and forums
• Reviews and brand mentions 
• Survey responses

Sentiment is generally categorized three ways: positive, negative, or neutral. But it also has varying levels.

A mildly satisfied customer and a genuinely delighted one both register as “positive.” But they behave very differently. A delighted customer recommends you to friends. A mildly satisfied one might only stick with you as long as it’s convenient for them. 

What is customer sentiment analysis?

Customer sentiment analysis is the process of quantifying raw sentiment data. It means looking for patterns across all your customer touchpoints so you can accurately identify how customers feel. Then, you can fix the negative, repeat the positive, and become the kind of business people want to hire. As you can imagine, this isn’t the kind of task you’d do manually. Instead, businesses use automations and sentiment analysis tools to speed things up. 

There are a few ways to use these tools to measure the sentiment of your customers:

• AI-driven sentiment analysis looks at the emotional tone and what the customer says. Then it assigns an overall sentiment. AI uses advanced call intelligence technology to help it understand and process language. Paired with machine learning algorithms, it can interpret the customer’s feelings.

For example, if a customer says, “I love how easy it is to call customers with Quo,” the interaction would have a positive sentiment. Or if a customer says, “This app keeps crashing! I’m so frustrated,” As you can guess, that has a negative sentiment. 

• Word-based sentiment scoring is more rigid than artificial intelligence. Rather than looking at the context of the conversation, a word-based approach would look for specific words, like “frustrated.” Then it assigns a sentiment to that customer interaction based on those words. 

So how do real businesses use customer sentiment analysis in action? 

Common sentiment analysis use cases

Businesses across industries track customer sentiment. It can help with everything from product development to managing brand reputation. For small and growing service businesses, it involves:

• Spotting unhappy customers so you can follow up and remediate bad experiences, preventing customer churn
• Understanding what customers want so you can improve your service or offer something new 
• Identifying which part of your service customers love most so you know what to invest more in 
• Coaching your team based on real customer opinions so you can offer a better experience 
• Measuring the impact of recent marketing strategies so you know if they attracted the right customers

Benefits of customer sentiment analysis

You’re gathering all of this data about customer sentiment… but what’s the overall benefit for your business? 

Better understanding of customers’ needs and expectations

For many customer support teams, CSAT scores are a “North Star” metric. They aim to have the highest score possible and may assume that if they have a good score, customers are happy. 

While CSAT is one indicator of customers’ feelings, not every customer will complete the survey. You’re only getting some insights from customers willing to take the time to answer.

With voice call sentiment analysis, you can look for keywords that come up. This includes repeated service requests or common billing problems. Understanding the root cause of customers’ feelings and pain points allows you to do more with the data.

Offer a better customer experience

According to Qualtrics, 72% of people say they would pay more for a better experience with a company. Understanding customer sentiment is how you start improving.

By analyzing patterns across multiple interactions, you can identify recurring problems. For example, slow response times that take multiple calls to resolve, or a question your team keeps getting asked without a good answer. From there, you can take action to help deliver five-star customer service. You may need to:

• Fix issues in your service or process that customers keep running into
• Update how you communicate, including response times, follow-up cadence, and tone
• Improve internal training so reps are better equipped to answer questions and delight customers
• Provide more targeted customer service coaching for specific reps or your entire team

💡Related: Lay the foundation for quality assurance, or QA, with this customer service quality assurance checklist.

Improve customer retention

Four out of five consumers have switched brands due to a poor experience. Analyzing customer sentiment helps you find and fix the friction before that happens and retain more customers.

Understanding what frustrates your customers, what they value, and what keeps them coming back is how you run a business that holds onto them.

Improved product or service offering

Let’s say you hear customers complain about the same thing over and over again. Maybe your pricing is confusing, or they wish you offered more services. – 

That’s an opportunity to improve and create something new. When you meet customer expectations, you’ll improve the overall customer sentiment. This also feeds into your retention rates.

How to measure sentiment as a small business owner

Now that you know why customer sentiment matters, let’s get into the nitty-gritty — how do you actually measure it?

1. Gather information 

First, identify all your sources for customer sentiment, like phone calls, emails, and online review sites. 

The most basic way to start is manually. For example, you could star emails with strong positive or negative feedback or keep a log of social media mentions and reviews. You might also tag customer interactions in your CRM. This is a low-lift way to begin building a picture of how customers feel.

But manual tracking is hard to do consistently, especially across multiple channels. It’s easy to fall behind, and the longer you leave it, the more signals you miss. 
With Quo, formerly OpenPhone, you can speed this up and save hours each week. A great way to analyze multiple conversations at once is to connect Quo to Claude. This is available on Claude Pro or Team and gives you a conversational interface to get insights faster.

You can ask the AI to analyze phone calls for qualitative and quantitative data points. Try questions like:

You can also manage and track sentiment for customer calls using AI call tags. Call tags can automatically flag customer sentiment, like a negative sentiment or an issue that needs escalation. 

This makes it easy to prioritize specific calls. That way, you can follow up with a customer before it turns into a negative review or you lose their business. You can configure the tags to flag calls however you’d like. 

2. Organize and analyze

To get a full picture of customer sentiment, you’ll need to analyze data across all your sources. You should also track sentiment over time.

You can paste the customer sentiment data from your emails, phone calls, and other sources into Google Sheets. Are you a spreadsheet wizard? You can create a system to summarize the sentiment from each source and merge the information for a clearer overview.

If you don’t have time to compile data by hand or aren’t comfortable with spreadsheets, you can use Claude. Ask Claude to do the analysis across all your Quo conversations at once:

3. Level up to automatic, proactive monitoring

You can’t make lasting change to your business if you only analyze customer sentiment once or twice. To see results, you need to keep at it. 

Why are we insisting on this? Because at the small business scale, catching one or two at-risk customers a week this way can have a real revenue impact for you. A flagged call becomes a same-day follow-up instead of something you notice three weeks later in a bad review.

But you might not always remember or have the time to analyze customer sentiment.

To save time, you can set up scheduled tasks with Claude Cowork to automatically surface sentiment trends. This can be daily, weekly, or monthly — whatever fits your business. 

For example, you can instruct Claude to:

Once you hit a level of high call volume where you need more than a phone system and an AI-powered assistant, you can add dedicated infrastructure. For example, you can get a customer support ticketing system like Zendesk or Intercom. Use these to auto-tag and categorize support interactions at higher volumes.

You can also consider a customer feedback platform like Survicate to start measuring Net Promoter Score^®. NPS is a growth metric that tracks how likely customers are to recommend you. It’s also a strong indicator of whether you’ve solved the underlying issues driving negative sentiment in the first place.

💡Related: Learn how we scaled customer support to serve 58K+ customers, and how you can too.  

How to take action based on customer sentiment insights

Collecting and analyzing sentiment data is only useful if it changes how you act. Here’s how to close the loop:

1. Identify and prioritize the right issues. Look for patterns across your data. A single frustrated caller might be an outlier. Five callers frustrated about the same thing in two weeks is a signal worth acting on immediately. Prioritize issues that show up repeatedly and affect the most customers first.
2. Follow up with the right customers. Use your data to find the conversations that need a response. Use prompts like, “Which customers with negative sentiment haven’t heard back from us in the last seven days?”
3. Track whether things are actually improving.  Compare sentiment data over time to see if your efforts are working. Use prompts like, “Have complaints about [specific issue] increased or decreased since [date]?”
4. Use positive sentiment too. Negative signals get the most attention, but positive patterns are just as actionable. Let’s say customers consistently mention loving a specific part of your service. That’s something to double down on, highlight in your marketing, and protect when making operational changes.

Get started with customer sentiment analysis using Quo

You’ve got so much data about customer sentiment at your fingertips. You just need to start collecting it so you can analyze the information and act on your findings.

You can easily use Quo to gather customer sentiment from your phone calls. Not only can you use AI call tags and internal comments, but you can also dive deeper by listening to call recordings or reading call transcripts with AI summaries.

You can also connect Claude to Quo for even richer, faster insights. Ask Claude to analyze sentiment across all your calls at once, spot recurring themes, and turn them into clear next steps for your team.

To see how Quo can benefit your small business, you can sign up for a free seven-day trial.

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