When talking to a customer, you probably have a gut instinct about how they feel. They’re delighted when you answer a question, frustrated when something goes wrong, or confused when something doesn’t work as expected.
What if you could turn those gut instincts 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.
Collecting the data to measure customer sentiment might seem like something only enterprise companies do, but it’s just as important for small businesses. When you understand customer sentiment, you can improve customer relationships and prevent negative word-of-mouth or bad reviews.
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.
What is customer sentiment?
Customer sentiment measures your customers’ emotions, attitudes, and feelings about your company, product, or service. It’s collected across all customer interactions, including phone, chat, email, social media platforms, and reviews.
Customer sentiment can be measured in a few ways:
- AI-driven sentiment analysis looks at what the customer says and assigns an overall sentiment. Using advanced call intelligence technology that helps computers understand and process language — along with machine learning algorithms — AI can interpret the customer’s feelings.
For example, if a customer says, “I love how easy it is to call customers with OpenPhone,” the interaction would have a positive sentiment. If a customer says, “This app keeps crashing! I’m so frustrated,” 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”) and assign a sentiment based on those words.
- Customer reviews should also be factored into customer sentiment. A conversation doesn’t always capture how the customer actually feels. Or, the customer may not interact with your team, but will leave a review. From reviews, you might get customer opinions that you can’t capture in satisfaction surveys.
Customer sentiment vs customer satisfaction
Customer satisfaction is slightly different from customer sentiment. A customer satisfaction score (CSAT) measures how happy a customer is with a specific interaction on a scale of 1 to 5. This information is gathered via a survey like this:
“How would you rate your overall satisfaction with the service you received?”
- Very unsatisfied
- Unsatisfied
- Neutral
- Satisfied
- Very satisfied
The responses are averaged to get an overall customer satisfaction score.
Why the distinction matters
CSAT asks customers to rate a specific interaction. While it’s helpful to know how customers feel after talking to people on your customer service team, it might not reflect customers’ overall feelings about your company or products. They can have a positive satisfaction score but a negative sentiment, and vice versa.
Customer sentiment can give deeper insights beyond satisfaction scores, helping you understand the root causes behind customer emotions.
What is customer sentiment analysis?
To dig into customer sentiment, you have to collect and analyze data from all the available sources. Customer sentiment analysis looks for patterns across your support tickets and calls, surveys, online reviews, community discussions, and more. Sentiments are categorized as positive, negative, or neutral.
With sentiment analysis tools, you can better understand what’s working, what you need to improve, and the “why” behind customer feelings.
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 who are willing to take the time to answer (or dissatisfied customers).
With voice call sentiment analysis, you can look for keywords that come up, such as repeated feature requests or common product problems. Understanding the root cause of customers’ feelings and pain points allows you to do more with the data.
More effective support processes
By analyzing patterns across multiple interactions, you can identify recurring problems that happen during calls, emails, or chats. For example, you might notice that customers get frustrated because it takes support a while to respond or it takes multiple attempts to resolve an issue.
Knowing this, you can refine your support processes, such as:
- Improving internal training so reps are better equipped to answer questions and delight customers
- More targeted customer service coaching for specific reps or your entire team
- Developing a customer service training manual that reps can refer to
- Creating better scripts so reps can respond to repetitive questions efficiently
- Expanding your knowledge base or help articles so customers can self-serve
Any of these will create a better customer experience because you’re giving customers the information they need as quickly as possible.
Related: Lay the foundation for quality assurance (QA) with this customer service quality assurance checklist.
Improved product or service offering
If you hear customers request the same thing over and over — such as a new feature or a service you don’t currently offer – it’s an opportunity to create something new. When you meet customer expectations, you’ll improve the overall customer sentiment (plus improve customer retention).
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? The good news? You can start gathering insights with the tools you already have. Here’s how.
1. Gather information
First, identify all your sources for customer sentiment, such as phone calls, emails, online review sites, survey responses, and social media posts.
With OpenPhone, you can directly manage and track sentiment for customer calls using AI call tags. Call tags can automatically flag customer sentiment (such as a negative sentiment or an issue that needs escalation). 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.
Support reps can also manually leave detailed information after a call in OpenPhone. This can be added to either the customer contact notes or as an internal comment in the conversation inbox (example: “Customer was frustrated with XYZ.”)
You can also manually track sentiment from other sources using simple methods — such as starring emails with strong positive or negative feedback, keeping a log of social media mentions and reviews, or tagging customer interactions in your CRM.
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. If you’re a spreadsheet wizard, you can create a system to summarize the sentiment from each source and merge the information for a clearer overview.
Another option is to use ChatGPT to analyze sentiment. Just make sure you remove customer-sensitive information before uploading your data. You can use prompts like:
-
- Summarize customer sentiment from these sources and categorize the feedback into positive, neutral, or negative.
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- Analyze this set of customer feedback and identify the top three recurring frustrations.
3. Scale up
When you start seeing a higher volume of support requests you may want to use a customer support ticketing system such as Zendesk or Intercom. Ticketing systems can use auto-tagging features or AI-driven sentiment analysis to categorize your customer support interactions.
You may also consider using a customer feedback platform like Survicate to measure Net Promoter Score℠ (NPS) and other metrics. Net Promoter Score helps you measure customer loyalty by asking, “How likely are you to recommend the business to a friend or family?”
NPS is considered a growth metric because the more promoters you have, the more likely you’ll gain new business by word of mouth and recommendations. A high NPS means you’ve likely solved underlying issues with your product or service. It’s a leading indicator that’s especially helpful as you scale customer support.
Get started with customer sentiment analysis using OpenPhone
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 OpenPhone 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.
To see how OpenPhone can benefit your small business, you can sign up for a free seven-day trial.
FAQs
Customer sentiment is based on the words a customer uses in a conversation. If a customer says, “I’m unhappy with this product,” it would have a negative customer sentiment.
Customer sentiment is usually categorized into three groups: positive, neutral, and negative. Companies often use a scale of 1-5 or 1-10, with lower numbers indicating the most positive sentiment and higher numbers representing the most negative sentiment.
Customer sentiment is used to capture how a customer feels about a company, product, or service. Net Promoter Score, on the other hand, is a metric that measures customer loyalty and the likelihood the customer would recommend the company or product to their friends or family.
