10 Sentiment Examples for Improving Customer Satisfaction [+ Tools]
Getting user feedback is a crucial step of the market research process. However, sentiment analysis takes things a step further to get a clearer view of your brand reputation in the eyes of multiple customer segments.
In this guide, we’ll go over what sentiment analysis is, why you should do it, and look at 10 sentiment examples!
- Sentiment analysis helps you monitor the opinions, emotions, and feelings (sentiment) of customers towards your product or brand.
- Sentiment analysis makes it possible to compare your product to competitors, evaluate the impact of your product/marketing efforts, and gather actionable growth insights.
- You can collect feedback for analysis through in-app surveys, online reviews, social media mentions, and customer interviews.
- Streamlined onboarding, lower user friction, and targeted marketing are just a few examples of sentiment analysis being applied to improve a SaaS customer journey.
- Tools like Userpilot, Brand24, and MonkeyLearn can help you conduct your sentiment analysis more efficiently, plus gather more detailed insights.
- If you want to gather both qualitative and quantitative data for your sentiment analysis, book a Userpilot demo today to see how!
What is sentiment analysis?
Sentiment analysis — also known as opinion mining — is used to analyze data that tells you how customers feel about your product or company. This could include analyzing sentiment for online reviews manually, using social media monitoring tools, or a combination of the two.
Customer sentiments are frequently used as a customer feedback mechanism for SaaS companies to make improvements to their product based on how customers feel. Tracking sentiment can also help you with feedback analysis and interpreting responses to in-app surveys.
Why should you perform sentiment analysis?
Performing sentiment analysis for your own business offers a few benefits since you’ll be able to:
- Better understand how customers feel and use that to guide your improvement efforts.
- Assess how your products/services are perceived in comparison to your competitors.
- Evaluate the impact of your product and marketing strategies in increasing customer satisfaction.
- Use detailed insights to target your growth marketing efforts and PLG strategy.
How to collect customer feedback and opinions for sentiment analysis?
Collecting customer feedback is a key part of the sentiment analysis process. That being the case, let’s look at four ways to gather both positive and negative feedback from happy/unhappy customers online so you have enough user feedback to draw accurate conclusions!
Trigger in-app surveys to collect contextual feedback
In-app surveys are the best way to actively gather actionable insights into customer’s opinions. You can collect insights on their brand perception and overall product experience or ask about specific aspects/features of the solution.
There are two main survey types to be aware of: transactional surveys and relationship surveys.
Transactional surveys are triggered by user interactions to ensure that they appear in the most contextual moments and gather relevant feedback. You could trigger transactional surveys right after onboarding flows, support interactions, or other key events.
Relationship surveys collect feedback that focuses on the relationship between your customers and the product itself. These surveys measure the overall health of the relationship between the business and its customers.
Relationship surveys are best for startups that don’t have enough customers to accurately gauge public opinion during the early stages of their journey. On the other hand, large companies should use a combination of the two to get the full picture.
Monitor customer opinions on review sites
While review websites like G2 may serve as a double-edged sword (hosting both negative and positive sentiment), they can be a great source for measuring the sentiment of your customers without needing to regularly survey them.
G2 is best used to browse general reviews and gauge overall sentiment, while different platforms like Product Hunt are ideal for gauging product release sentiment from your earliest customers. User-generated content on these sites often ranks on Google as well, so addressing negative sentiment can help you mitigate bad reviews in the future.
As a bonus, G2 also lets you sort reviews by star rating or filter by specific keywords. This makes it easy to view feedback from both sides of the sentiment spectrum and identify patterns in the issues/benefits that multiple customers have experienced with your product.
Perform social media monitoring for brand mention
Tracking and analyzing mentions of your brand across various social media platforms can help you gauge overall sentiment. Social media monitoring is also an effective way to spot negative market trends early and nip a potential PR crisis in the bud.
If your sentiment analysis model shows primarily negative attitudes from your customers on social media, starting a new marketing campaign to reinvigorate the brand reputation amongst customers could be a worthwhile effort.
Conduct customer interviews for valuable insights
Having your customer support or success representatives conduct follow-up interviews is the next logical step in customer feedback analysis. This not only helps you get clarification on the initial feedback submitted, but also gets respondents to elaborate further on their thoughts.
There are real-world examples of interviews being conducted in person, but phone calls, video conferencing, and virtual focus groups tend to be the most common approaches. Regardless of the setting, it’s essential that you ask the right questions.
Asking open-ended questions will encourage customers to freely express their thoughts, feelings, and experiences with your product. Prioritize responses that are specific and actionable then relay that feedback to your product or marketing teams.
10 sentiment analysis examples to enhance customer experience
Now that you understand what sentiment analysis is, it’s time to apply that knowledge in the context of your business. Here are 10 examples of sentiment analysis that you can use to increase customer satisfaction in your own company!
Refine onboarding processes and resources
Finding out how customers feel about the onboarding process and looking at onboarding flow data will give you a holistic view of which areas you can improve upon. Completion rates, drop-off points, and high-friction areas can guide your refinement strategy or help you create better onboarding content.
Detect user friction or confusion across the customer journey
Triggering customer effort surveys throughout different stages/touchpoints of the customer journey can help you drill down on user friction. Analyzing metrics like the customer effort score (CES) can help you address specific issues or remove friction altogether.
By reducing the friction in your in-app flows or making specific features easier to use, you’ll be able to improve user sentiment while simultaneously improving the broader product experience. This means that reducing friction through sentiment analysis is a mutually beneficial process for all parties involved.
Deliver targeted in-app marketing campaign
By conducting text analysis (either manually or through artificial intelligence/machine learning natural language processing algorithms), you’ll get a better idea of the type of human language that your customers use and respond to.
This will help you tailor your marketing messages (both in-app and on social media) and special offers in a way that’ll appeal to your customers. It’ll also help you align your messaging with their emotional state, preferences, and sentiment.
To get the most out of every campaign, you should create sentiment segments for your customers, such as “happy customers” or “dissatisfied customers”, and then tweak the language accordingly. You can also have a segment for “neutral users” that you’ll use as your control when A/B testing campaigns.
Guide product updates and enhancement efforts
Knowing which parts of your product aren’t meeting expectations can guide the direction of future product updates and enhancement efforts. This expectation aspect-based approach to product improvement will help you improve sentiment over time with tangible implementations of feedback.
Your company’s customer service team will usually be one of the richest sources of enhancement suggestions from customers. You can even use solutions with machine learning algorithms and natural language processing to automate the process of sorting customer support tickets.
Aspect-based sentiment analysis lets you identify the sentiments, emotions, or issues within text. You can then use those sentiment filters to segment customers and send targeted follow-up messages to unhappy users.
Other than support representatives, your customers themselves can also offer actionable feedback. Customer feedback can help you segment users with similar problems, add product suggestions to your roadmap, and then send out targeted announcements.
Prioritize feature development based on user requests
As the above examples of sentiment analysis have shown you, understanding what your product lacks (perhaps through in-app feature request surveys) is a core part of the process. As such, there are a few practices you need to adopt:
- Looking at feedback to understand what’s lacking.
- Treating feedback and sentiment as a subtle feature request — then making the necessary changes.
- Leveraging product growth platforms like Userpilot to gather feedback for further sentiment analysis:
Refine and expand customer support materials
Self-service customer support is mutually beneficial, but this model only works if there’s an abundance of resources that users can use to solve their own problems. Look at the feedback data from your sentiment analysis to identify content gaps, prune confusing articles, and find opportunities to improve.
Publishing help articles is only the first step in building a knowledge base, you also need to refine your customer support documentation and keep all your resources up to date over time. Userpilot lets you create an in-app resource center that customers can use to find the resources they need:
Identify factors contributing to high or low satisfaction
A crucial part of sentiment analysis is finding the factors that cause an increase or reduction in customer satisfaction. There are a few metrics you can use for customer satisfaction benchmarking, but the Net Promoter Score (NPS) is the most reliable.
In a nutshell, NPS data essentially serves as real-time sentiment analysis.
Userpilot’s NPS dashboard shows you all the data and responses in one place:
Looking at positive feedback from happy customers can tell you what you’re doing right and help you double down in the right areas. The more familiar you are with the aspects that lead to high satisfaction levels, the easier it’ll be to steer other users towards the same positive outcomes (through in-app flows).
This will lead to a better brand reputation and the opportunity to reduce churn across your user base.
Predict and proactively address potential churn from negative sentiment
While listening to your satisfied customers is important, hearing out your passives and detractors is arguably more paramount. Users who are indifferent to the product or even dislike it, will have more specific feedback on what could be improved than customers who actively praise it.
Listening to both types of feedback is the only path toward improving customer satisfaction. Furthermore, by proactively addressing the concerns of these at-risk customers you’ll be able to curb or eliminate any predicted churn.
Userpilot lets you tag qualitative NPS survey responses to help you identify common issues that are leading to negative sentiment:
Understand what customers like and dislike about competitors
Sentiment analysis has a lot of overlap with competitor analysis since both types of market research touch on product development/positioning. NPS surveys, PMF surveys, and product evaluation surveys can all help you
Feedback from these surveys may show that customers find your user interface too confusing compared to other solutions (or the other way around). The market research can also uncover any points of parity that you lack (and how that affects user sentiment).
Best customer sentiment analysis tools
The effectiveness of your sentiment analysis will only be as robust as the tools you’re using to carry it out. While it’s probably possible to gather every data point and crunch every number manually, this is hardly an efficient approach (which could even lead to inaccurate conclusions).
Here are three customer sentiment analysis tools that you should consider adding to your tech stack:
Userpilot is a digital adoption platform with three plans starting at $249/month.
Its features and benefits include:
- Sentiment analysis feedback collection via in-app surveys.
- Native survey analytics capabilities and sorting/filters for survey responses.
- Advanced surveying functionality (such as customization, translation, and AI-powered localization).
- Dedicated NPS surveys and analytics dashboards with response tagging.
- Other forms of analytics such as product analytics, path tracking, trend/funnel reports, and customer behavior analytics so you can get a comprehensive view of sentiment.
- Analytics dashboards that turn unstructured data into an advanced tool for driving product growth.
Brand24 is a social listening tool with four plans starting at $79/month.
Its features and benefits include:
- Brand monitoring on social media platforms.
- Real-time updating for social media mentions (on the Team plan and higher).
- Basic AI features to improve your social media presence.
MonkeyLearn is a no-code analytics platform with two plans starting at $299/month.
Its features and benefits include:
- Sentiment analysis and insights dashboards.
- No-code data visualization.
- Word cloud generator.
Sentiment analysis isn’t an overnight growth hack, many companies spend more than a decade on such efforts. However, the sooner you start applying sentiment analysis to your product development and marketing efforts, the quicker you’ll be able to reap its benefits.
If you’re ready to gain insights into how many customers might actually feel about your product, then it’s time to get your free Userpilot demo today!