At the heart of your business, where everything gets its shape, rise, and downfall - is customer sentiment. Customers today are very expressive and keep sharing their feelings about the businesses they deal with and the products they use. Whether positive or negative, these customers don't hold back when expressing their opinions. They communicate their opinions about the goods and services they utilize through mobile applications on various platforms. These platforms include Twitter, Facebook, the App Store, Google Play forums, review websites, and blogs.
"The top-of-mind challenges that brands should be sure to manage to include: - Capturing the voice of the customer only in surveys and not investing in a qualitative study of the customer. Underestimating the power of customer human emotions and how these drive customer decision-making in choosing a brand. Using sales or operational efficiencies as the only measures of customer success and ignoring the negative sentiments, the share of wallet, and churn metrics as part of the equation," says Marlanges Simar, Senior Director of Customer Experience, Walgreens, according to Clootrack’s CX report.
When customers interact with your goods, services, or brand, customer sentiment analysis can monitor emotions in real-time. It uses Natural Language Processing (NLP) or a collection of algorithms that can determine whether a customer is feeling positive, negative, or neutral. Customer interactions are analyzed using sentiment analysis algorithms, which typically use polarity and magnitude to determine whether and how strongly the customer expresses positive or negative feelings.
Is Sentiment Analysis Important For You?
Sentiment analysis makes it possible to enhance the customer experience, raise customer satisfaction, and increase long-term loyalty.
- Sentiment analysis helps assess customer happiness and concerns that need prior attention.
- Customer sentiments are essential to carry out a fundamental analysis of their behavior, perception, and intent.
- You can sync customer sentiment analysis with other sets of customer data and insights to refurbish the existing data.
- You can decipher customer sentiments and facilitate your teams with relevant knowledge for achieving greater customer engagement.
- You can successfully dodge multiple and inaccurate interpretations of customer sentiments using a foolproof analysis.
So, discovering the factors influencing customer satisfaction and utilizing them to provide a superior experience allows you to understand better customers' perceptions of your brand and overall experience.
The 4 Steps of Customer Sentiment Analysis
Customer sentiment analysis can be very beneficial to your business. But where do you start? You can build sentiment analysis models that are specific to the requirements of your business using a variety of traditional and online tools.
Step 1: Choose Your Feedback Channels
Decide on your preferred feedback channel, such as support conversations, customer reviews, and survey results. The most valuable source of information for customer feedback is support conversations. The greatest source of customer insight is the support ticket logs from emails, calls, and live chats, which offer unbiased, qualitative comments.
For this exercise, you should be able to export your chat or email logs, so take a small sample and get acquainted with it. Since most customers read customer reviews before making a purchase, they are a major factor in driving sales. This makes it crucial for business success to understand the causes of bad evaluations.
The most popular methods for gathering customer feedback are NPS and CSAT. A strong use case for AI-powered sentiment analytics is understanding the factors that underlie both positive and negative sentiment at scale. NPS surveys are currently seen as biased feedback, so you'll need to put a lot of effort into ensuring your results are useful.
Step 2: Gather Customer Data
Data is the most crucial component of customer sentiment analysis. It will be used to train your sentiment analysis model and, once it is ready, to test it. Companies can obtain sentiment data from a variety of sources, such as:
- Online Surveys. You can use online tools like Google Forms, SurveyMonkey, or Typeform. You can export all responses from these tools as a CSV or XSL file.
- Product reviews. You can find reviews on platforms like Google Play, Amazon, Capterra, G2 Crowd, Tripadvisor, etc.. Using a web scraper to collect specific data for you automatically is the best approach to obtaining product reviews from various websites.
- Social media posts. Customers frequently tag and mention your business on Twitter, Facebook, Instagram, and other social media. Since you can gain insights from both past and present mentions, sentiment analysis of Twitter is a well-liked data source. The Twitter API allows developers to gather data.
Step 3: Label The Feedback
Once you have all of your customer feedback data in one location, you need to decide how to organize it into negative, positive, and neutral categories. You may choose to do it manually. You can use two spreadsheets. One to keep the labels, you'll need to code the feedback, and another to hold the feedback you've already collected. Or, you can use various AI tools. With AI technology, sentiment analysis models can automatically categorize customer feedback as either positive or negative, saving you a tonne of time and effort compared to manually analyzing these comments.
Step 4: Present The Results
A customer sentiment analysis's reporting format is almost as crucial as the analysis itself. Others must not only comprehend your sentiment analysis report but also take action. Your representation of customer feedback should genuinely connect with the audience and give them the confidence that they can take this input seriously.
10 Ways Brands Can Benefit From Sentiment Analysis
Sentiment analysis aims to paint a complete picture of the customer experience. Every touchpoint should be integrated, including call reasons, survey results, emails, chats, CRM, service history, and payment history. Every customer's journey through the buying cycle should be properly considered, and you should engage with them through their preferred channel. Here are a few ways you can put customer sentiment analysis to use:
1. Reduce Complaint Resolution Time
When a consumer has a query for customer service, 90% of customers consider an "instant" response vital. 60% of customers believe 10 minutes to be "instant." You can provide dissatisfied consumers with a quicker and better resolution with sentiment analysis. With its potential to flag negative comments or communications for swift reactions, sentiment analysis adds a crucial component to customer service. This allows you to reply quickly and, hopefully, put an end to the issue before it escalates. Sentiment analysis is used in this situation, along with social media monitoring and other technologies that feed into it in real-time.
2. Achieve Accurate Customer Insights
12.4% of survey participants, according to CX Experts, believe that brands don't gather essential information and insights. Controlled surveys, a common type of traditional market research, are subject to human biases, including respondents who only provide feedback after a particularly positive or negative experience. These biases can impair your ability to make data-driven judgments by skewing information.
Sentiment analysis browses the web and gathers data from blogs, social media groups, and forums that expressly discuss your market to offer you a complete view. Your machine learning models can more precisely forecast which consumers could cancel and what you can do to decrease cancellations with the help of sentiment analysis. AI, machine learning, and NLP can provide you the power to use personalized opinions as fuel for your customer retention engine and to encourage long-term customer loyalty as customer data continues to grow.
Furthermore, you can quickly determine whether adjustments to your products or services were successful by keeping an eye on consumer sentiment around your brand before, during, and after such modifications.
3. Develop Efficient Customer-Facing Employees
Your customers will be more devoted as long as you continue to improve customer service. But how can you decide if the upgrade is necessary? The issues that might or might not be present in your business might be sorted out using aspect-based sentiment analysis. 70% of customers think sustaining their business depends on service agents' expertise in sales encounters. Understanding each customer's sentiment will help you arm your agents with the information they need to communicate with customers more effectively. After that, you can direct the call of a disgruntled customer to an empowered agent to promote interaction and proactive resolution, which may enhance customer satisfaction and revenue.
Sentiment analysis interprets your customers' tone, attitude, and mood so you can interact with them at the appropriate time. You'll know who to contact, what to discuss, and which platform to use for these things. Your chatbots can be configured to use sentiment analysis to determine when to escalate a chat to an agent or send it to one of your knowledgeable team members. This is a great approach to enhancing customer service and providing enjoyable experiences.
4. Enable Customer Segmentation
With the right tools, you can use sentiment analysis to assess consumer sentiment and divide it into segments that exhibit significantly different patterns from the overall picture. After all, not all social groups are alike. Your agents frequently serve several consumers at once. The queries cannot all be manually processed and answered at once. Sentiment analysis is quite effective at determining which customer conversations are going well and which call for immediate action.
5. Personalize Customer Experience
"New data and AI-driven methods are needed to engage and influence today's sophisticated and socially hyperactive consumers. To remain relevant, brands need to provide new value for existing customers with elevated and rewarding experiences across all touchpoints while acquiring new ones with contextually tailored precision. Hyper-personalization moves an enterprise from targeting segments of its consumer base to surgically targeting individual consumers, and wowing them with signature experiences at high-value moments," states Lance Moncrieffe, AI Expert Practices Leader, Cognizant, in the Clootrack report.
With the aid of sentiment analysis, you can look at how people behave when specific subjects are discussed and determine what potential leads you might be able to pursue. 80% of businesses analyze and enhance customer experience using customer satisfaction scores. You may develop more relevant offers that resonate with your customers and provide customized experiences based on satisfaction scores and other sentiment drivers. Customers who receive offers and recommendations that are pertinent to them are more inclined to purchase from brands, according to 91% of consumers.
6. Monitor Brand Status
Depending on what's happening worldwide, opinions on companies can change dramatically and quickly. Minor misconduct that becomes public can severely harm a brand. Employing sentiment analysis, businesses can track the condition of their brands and target PR campaigns correctly, adjusting and flexing their efforts almost as quickly as public opinion.
7. Assess Market Trends
Trend monitoring keeps businesses up-to-date and self-aware. Deeper problems with a product, brand, company or the general public's perspective might be revealed by trends and patterns. Monitoring trends enables the early detection of issues before they become severe. Suppose your competitor has already introduced a new product, and you want to find out whether it has any flaws so you can fix them before introducing your own. You could also decide to target marketing initiatives at your competitors' strong points.
8. Improve Products and Services
Conducting sentiment analysis on testimonials, social media posts, polls, and other resources might indicate:
- Issues/bugs: You may see a sudden increase in negative comments reporting bugs.
- Room for improvement: Customers may frequently criticize certain features.
- Customer needs: You can hear complaints about features that aren't available or slow response times.
You might opt to redesign your product after conducting sentiment analysis on customer evaluations and learning that the majority of unfavorable comments focus on a particular feature of it.
9. Capture Real-Time Conversations
Customer sentiment analysis offers a significant chance for your brand to rope in real-time conversations about the brand among customers and relevant audiences. This can further help you spot pain points and fix them once and for all.
“Collect feedback frequently across channels, via surveys, ratings and reviews, customer service calls, focus groups, and one-on-one conversations. Analyze the responses and look for actionable insights. Listen for what you are doing well and do more of it! Then listen for what parts of the experience are missing the mark and try to fix the underlying issue.” Dan Gingiss - Chief Experience Officer, The Experience Maker, LLC - in the Clootrack report.
10. Conduct a Competitive Analysis
Customer sentiment analysis also helps brands take into account what customers think about their competitors. While many brands struggle in having a crystal clear vision of their CX goals, obtaining and leveraging rich insights via analyzing customer sentiments can turn the tables on your competitors.
The Key Takeaways
Sentiment analysis provides information on how consumers feel about your business and the possibility that they will recommend it to others. By revealing complicated behavioral patterns that quantitative methods (like surveys) alone can't always show, it can provide deep customer insight.
Sentiment analysis makes it possible to enhance the customer experience, raising customer satisfaction and increasing long-term loyalty. Negative experiences mostly challenge building consumer loyalty.
Read More: All You Need to Know About Performing Sentiment Analysis