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4 sentiment analysis examples to inspire your teams

You know sentiment analysis can help you understand your customers better. And that your competitors are already using this technique to tempt them over to their side.  

But what does it look like in real life? How can you apply it to your business to improve the customer experience and boost satisfaction? 

We’ve put together a list of 4 real-life sentiment analysis examples to dispel your doubts.

Last updated

23 Sep 2022

We’ll walk you through each example and show you how to apply it to your business. And give you tips on choosing the right type of sentiment analysis for your customers, business, and goals.

Want to know what customers really think and feel about your brand?

Hotjar’s product experience (PX) insights tools let you peek behind the curtain of customer behavior.

4 sentiment analysis examples

User sentiment analysis involves identifying the thoughts and feelings behind customer comments in unstructured data like survey responses or help center interactions. 

The user sentiment analysis process involves turning these subjective opinions into actionable, objective insights. This lets you improve the customer experience and boost customer satisfaction, loyalty, and retention.  

We’ve chosen 4 sentiment analysis examples relating to the most common data sources: 

  • Social media posts 

  • Customer support requests 

  • Customer feedback from surveys, forms, etc. 

  • Text from emails, customer reviews, call transcripts, etc.  

These real-life case studies will show you how to extract and analyze data from each source. And how to apply insights to the benefit of your customers.

Let’s take a look at them.

1. Social media sentiment analysis: Nike 

Social media sentiment analysis looks at the meaning behind tweets, Facebook posts, YouTube comments, and other social media. It tells you what people are saying—and how they feel—about your brand online. 

How Nike used social media sentiment analysis  

Sportswear retailer Nike used social media sentiment analysis in 2018 when it backed NFL player Colin Kaepernick who ‘took the knee’ during the US national anthem. His actions generated controversy and criticism, including from then-president Donald Trump. But Kaepernick also got a lot of support, which Nike capitalized on by sponsoring him to use the #justdoit hashtag in his tweets. 

This was a risky move: Nike needed to keep tabs on public opinion to make sure its reputation wasn’t in danger. It used Sentieo to gauge reaction to its campaign by analyzing tweets and related news before and after the inclusion of the #justdoit hashtag.

Initial reactions were negative and included #boycottNike hashtags from certain customer segments. But, over time, this was replaced by overall positive sentiment from the general public. And Nike also discovered that purchase intent was positively affected, which was a win-win. 

#Tracking social media mentions let Nike monitor public opinion during its sponsorship of Colin Kaepernick. Source: Sentieo
Tracking social media mentions let Nike monitor public opinion during its sponsorship of Colin Kaepernick. Source: Sentieo

How social media sentiment analysis can help your business 

Social media sentiment analysis helps your brand actively engage with its community over social media. 

It lets you take the pulse of public/customer sentiment and opinion–before and after launching a campaign—and monitor campaign performance. You can also use it to watch what influencers are saying about your brand or your market. 

All this helps you stay in line with customer expectations and build brand trust and reputation. It also lets you move with the times as society and your audience evolve. 

And if you do misjudge public appetite for a particular campaign, monitoring social media sentiment lets you quickly swing into crisis management mode to minimize any damage.  

Sentiment analysis enables businesses to precisely identify positive or negative attitudes about their product or service and take appropriate action. Businesses can gain insights by reading millions of comments and opinions made on social media.

Ronen Ben-Dror
Director of Client Development, Blue Valley Marketing

 How to use social media sentiment analysis: 

  • Install user sentiment analysis software like Talkwalker, Sentieo, and Critical Mention (which also alerts you to mentions of your brand in the news). Use these tools to take the temperature of public opinion before a campaign or event so you can benchmark reactions to it. 

  • Find out what different customer segments think of your product or new release. For example, a B2C app developer might monitor social media sentiment among early adopters—and make improvements before rolling it out to the wider community. 

  • Track new trends to identify when you need to be part of the conversation. 

  • Monitor what people say about the competition to find out how you can improve your products. For example, if you sell online courses and see people complaining that a competitor’s sign-up process is too complex, you’ll know to make yours that much simpler.   

2. Customer support sentiment analysis: a mobile carrier

Customer support sentiment analysis looks at chatbot and help center interactions. You can record and transcribe calls and add them to any chatbot interactions. Then, analyze the whole thing to gauge sentiment. 

These sources are an often-overlooked goldmine of information that can help you improve customer retention metrics

How a mobile carrier used customer support sentiment analysis  

In this Repustate case study, a large mobile provider used customer support sentiment analysis to spot customers at risk of churning. First, it installed speech-to-text software to transcribe each call center interaction. Then, it used Repustate to analyze each call for sentiment and mentions of specific products and services. 

Finally, it produced an overall customer sentiment score for each customer. Any low scores—or ones that dipped below a certain threshold for too long—triggered an automatic message of apology to the customer. 

Call center operators were able to access a summary of the customer score and previous interactions the next time the customer called, which helped them offer relevant solutions or promotions. 

How customer support sentiment analysis can help your business

For many customers, the quality of their interactions with your brand is almost as important as the product itself. And many unhappy customers won’t bother complaining to customer support. They’ll just leave and you’ll never know why. 

Analyzing customer support sentiment lets your customer-facing teams—like sales and customer support—improve their services to boost retention and brand reputation

Customer sentiment analysis helps marketing teams create content to address common customer concerns. For example, case studies can show how other, similar, users have achieved success with your product. At the same time, product teams can act fast to fix bugs, UX and UI issues, and remove barriers to conversion or adoption.

We used data from sentiment analysis to improve our service by looking at complaints that our online Support chat was slow. I found that the majority of the complaints were coming from users who were on the free trial. I looked at how we could speed up the chat for those users and made some changes. We also implemented a system where users could pay to have their chat questions answered faster. This helped to improve our service and keep our customers happy.

Brandon Wilkes
Marketing Manager at, The Big Phone Store.

How to use customer support sentiment analysis: 

  • Install a chatbot on your website to answer simple questions. You can set it up to divert customers to the right support agent by collecting simple information about their issues. Then, use a natural language processing (NLP) tool like Thematic to analyze sentiment in the interactions. 

  • Make it easy for customers to contact you from anywhere on your website or digital product. Enable multiple channels, like email or SMS to cater to different user profiles. Everyone hates it when companies hide their contact details, and some users prefer to talk to a person over the phone. 

  • Monitor, record, and classify incoming support tickets by user, topic, etc. 

  • Record and transcribe incoming calls using tools like Otter or Rev. You can useinsights from these calls to improve your product. For example, if you’re running a vacation rental listings page and numerous customers complain about uncommunicative owners, you can incentivize faster response times. By fixing problems with your product, you’ll be able to cut your call center costs.

#NLP tools like Thematic detect keywords in all your incoming messages to identify common themes. Source: Getthematic.com
NLP tools like Thematic detect keywords in all your incoming messages to identify common themes. Source: Getthematic.com

3. Customer feedback analysis: TechSmith

Customer feedback analysis involves analyzing the sentiment behind answers to open-ended survey questions. Asking open-ended questions (as opposed to close-ended ‘yes/no’ or ratings) adds valuable qualitative insights (the why of customer behavior) to quantitative data (the what).  

But open-ended questions yield a lot of subjective information. So you need survey sentiment analysis to turn it into objective, actionable insights. 

How TechSmith used customer feedback sentiment analysis  

SaaS provider TechSmith used survey sentiment analysis and Hotjar tools to gather customer feedback to improve its product and website.  

First, it used Google Analytics to identify its most important website pages. Then, it turned to heatmaps to identify when visitors clicked on certain elements or scrolled beyond a certain point. 

Segmenting users based on activity, it placed surveys at strategic points and asked questions like: “What’s your biggest frustration with this page?” or “What do you find most valuable about this service?” 

Once the results were in, TechSmith used a spreadsheet to analyze them. This allowed it to tie customer sentiment into specific behaviors; make changes to onsite UX and UI; improve its products; and run A/B testing on the website to see which content or features customers preferred.  

#Gathering customer feedback lets you spot common issues that frustrate users of your website. Source: Hotjar.com
Gathering customer feedback lets you spot common issues that frustrate users of your website. Source: Hotjar.com

How customer feedback sentiment analysis can help your business

It’s not enough to know what your customers do on your site. You also need to know what they’re thinking and how they’re feeling while they’re doing it. So surveys are a great way to collect feedback in their own words. 

When you understand your customers better, you can achieve empathy and improve your copy, product, onboarding flows, and customer service. You can also remove barriers to conversion and boost repeat purchases. 

How to use customer feedback analysis: 

  • Use heatmaps and session recordings to understand how users navigate your site. i.e. where they rage-click, get frustrated, or drop off. You can also spot any areas or features that aren’t getting the attention you’d expect—and find out where in the customer journey to place surveys to get the insights you need.  

  • Identify which customer segments to target. For example, if you’re a B2B SaaS provider wanting to boost product adoption, you can gather information about the challenges facing new users. This lets you tailor onboarding flows to help users to realize value sooner.  

  • Use surveys and feedback widgets (by asking open-ended questions after ratings) to collect insights in the wild. The types of survey you can use include customer effort, customer satisfaction, point of conversion, and exit intent. 

  • Analyze survey datawith a spreadsheet or survey sentiment analysis tools like Quirkos, ATLAS.ti, or MonkeyLearn.

Pro tip: use Hotjar’s Survey Performance tool to see whether your survey is performing as expected. This lets you address issues to boost the number of responses you get. For example, you can check if your survey is too long or there’s a high drop-off rate after certain questions.

Hotjar’s Survey Performance tool lets you optimize your surveys and collect better insights. Source: Hotjar.com

4. Text sentiment analysis: WatchShop  

Text sentiment analysis focuses on written information from customers in website forms, email, or chatbots—and via third-party sources like review sites. 

Analyzing and unifying insights from these diverse sources helps you see the bigger picture of customer satisfaction. 

How WatchShop used text sentiment analysis  

Ecommerce retailer WatchShop used text sentiment analysis to improve its website and customer experience. 

After gathering customer data from emails, surveys, reviews, and other written sources, it used AI-tool Lumoa to give it an overall customer sentiment score. This score became a KPI that WatchShop could track. When it dropped below acceptable or benchmarked levels, the company used qualitative data analysis to go deeper into individual sources and find out why. 

Based on the results, WatchShop improved its product listing pages and removed barriers to conversion on its website. It also ran A/B testing to see which versions of its pages converted best.

Pro tip: Hotjar’s integrations with A/B testing tools like Optimizely, Omniconvert, and Google Optimize let you monitor your A/B testing directly in Hotjar. 

Use the results of your text sentiment analysis to form a hypothesis about which type of product listings pages or CTAs customers will respond to best. Then, create different versions of your pages and run A/B tests. You’ll get the results delivered right to your Hotjar dashboard. So no more switching between tools and tabs.

Integrating Hotjar with A/B testing tools lets you see test performance all in one place. Source: Hotjar.com

How text sentiment analysis can help your business 

Combined with other product experience insights, text analysis lets website and product teams improve online stages of the customer journey. 

For example, if customers regularly ask your chatbot about returns policies, or post reviews complaining that they couldn’t find it, you can rewrite copy to make it clearer. Or add a link to it from the checkout. This reassures customers and minimizes abandoned carts.  

How to use text sentiment analysis:

  • Use session recordings and heatmaps to understand how customers behave on your ecommerce site. Then, place surveys at strategic places, like your product pages or checkout, to find out what’s missing on your page and how you can improve the purchase experience.

  • Conduct customer interviews, transcribe recordings and analyze them using a tool like Dovetail. Remember to first think about which segments you want to target according to what you need to achieve. For example, if you’re a SaaS product team planning a new feature release, you could interview beta testers to get feedback. This lets you optimize it before the full launch. 

  • Collect incoming customer support emails

  • Monitor online reviews—your own and competitors’. For example, your SaaS business will want to look at G2, Capterra, etc. If you’re running an ecommerce company, your reviews will appear on distribution channels like Amazon. Tools like Luoma make it easy by connecting to rating sites like TrustPilot. 

  • Use qualitative data analysis tools to unify and analyze the text. 

  • Use a tool like WordCloud to spot frequently used words or phrases. 

How to choose the right type of sentiment analysis for your business 

There are as many sources of customer sentiment as there are ways to analyze it. To choose the right type of sentiment analysis for your business, ask yourself: 

  • Who are your customers? And where do they hang out? If you’re an ecommerce company selling to Gen Zers, you have to track your social media mentions. If you’re marketing SaaS products, you’ll want to monitor review sites for sources of user feedback to analyze.

  • What do you want to achieve? This will determine where and how to gather insights—and which users’ opinions to target. For example, if you’re looking to improve the online booking experience for tour groups, you’ll want to gather PX insights from the checkout section of your website. 

  • Which tools can deliver the insights you need? As well as data collection, you’ll need tools to unify, organize, and analyze it all. Which ones you choose will depend on your data sources and objectives. Check out our piece on user sentiment analysis software for more on this. 

Sentiment analysis examples: your roadmap to creating customer delight 

Sentiment analysis lets you put the voice of the customer front and center of everything you do. When you understand what they think and feel about your brand, you can make small changes that have a big impact.  

Use the sentiment analysis examples above to understand how to apply sentiment analysis to your business. They’ll also tell you which tools, techniques, and data sources can provide the actionable insights you need. 

And once you know that, there’ll be no stopping you.

Want to know what customers really think and feel about your brand?

Hotjar’s product experience (PX) insights tools let you peek behind the curtain of customer behavior.

Frequently asked questions about sentiment analysis