What is Customer Sentiment Analysis and 6 Ways It Improves the Customer Experience
We often discuss the value you can extract from unstructured customer data. But how do you use that data to improve the customer experience (CX) in immediate, tangible ways? The answer lies in customer sentiment analysis.
Customer sentiment analytics is a trending topic in the CX space, and for good reason. “Sentiment analysis,” Bain & Company recently reported, “is a powerful way to keep a pulse on customers and even the broader population to understand changing needs and anxieties, and new moments of truth.”
In today’s competitive marketplace, companies must leverage customer sentiment analysis to capture valuable, actionable customer insights that will improve the customer experience and benefit the entire business.
What is customer sentiment analysis?
Customer sentiment analysis refers to the automated process of discovering and measuring how customers feel about your product, brand, or service. Today, advanced technologies, including Artificial Intelligence (AI) and Natural Language Processing (NLP), extract these sentiments directly. To extract them, they mine the unstructured data contained within support tickets, phone calls, feedback forms, social media, chatbots, and other channels.
An AI-powered analytics tool such as SupportLogic can be integrated into a company’s existing ticketing system, such as Zendesk or Freshdesk, to continually capture the unstructured data contained within support interactions. The analysis of that data yields real-time, actionable insights to support teams to better serve customers.
According to researchers at McKinsey, real-time analytics have helped companies “reduce average handle time by up to 40 percent, increase self-service containment rates by 5 to 20 percent, cut employee costs by up to $5 million, and boost the conversion rate on service-to-sales calls by nearly 50 percent—all while improving customer satisfaction and employee engagement.”
From personalized customer interactions to reducing escalations, customer sentiment analysis benefits support teams in a myriad of ways. This article looks at the top ways these analytics can improve the customer experience—and with it, the health of your business.
1. Predict and prevent escalations
According to a PwC survey, 80% of customers say that an essential element of positive customer experiences is “knowledgeable help and friendly service.” Customer sentiment analysis enables agents to provide more knowledgeable, positive, and proactive service—which, in turn, helps prevent escalations.
A tool like SupportLogic uses NLP and AI to extract, analyze, and provide a statistical correlation of a customer’s real-time feelings. Is the customer frustrated or confused? Did they ask to speak to a manager about an unresolved issue that is likely to escalate? Customer sentiment analysis “takes the temperature” of a customer and provides a real-time, panoramic view of each one. This, in turn, empowers agents, providing actionable insights they need to better serve customers in the moment.
The benefits are significant. When business analytics platform Qlik partnered with SupportLogic to create a more seamless customer service experience, they began using customer sentiment and attention metrics. Using proactive AI, Qlik reduced customer escalations by 30% in just six months.
Real-time analytics have helped companies “reduce average handle time by up to 40 percent, increase self-service containment rates by 5 to 20 percent…and boost the conversion rate on service-to-sales calls by nearly 50 percent—all while improving customer satisfaction and employee engagement.” —McKinsey
2. Resolve cases faster and reduce backlog
Customer sentiment analysis also provides an agile, practical way to tackle the dreaded case backlog. By better capturing the topic and nuances of each support ticket, customer sentiment scores help streamline the case assignment process. Tickets can be routed more effectively to the right agent or agents, which ultimately leads to faster resolutions.
When it comes to support, customers care about speed and efficiency. In a 2020 Zendesk survey, 72.5% of consumers said that a speedy resolution matters the most when they have an issue to resolve with a company.
Using an advanced analytics tool like SupportLogic’s SX Case Assignment can reduce resolution time by 25%. And the time-to-value for clients is fast. In fact, customers typically start seeing significant improvements with backlog management and case resolution in a matter of weeks—not months.
3. Reduce churn
Sentiment scores provide clear signals and alerts when a customer is angry, frustrated, or in danger of churning. With real-time intelligence, an organization can immediately prioritize the ticket, better understand where a customer needs the most help, and send it to the right support engineer.
When SupportLogic client Fivetran introduced a customer sentiment score, the company saw a 25% reduction in customer churn. And the benefits extend beyond real-time interactions and customer retention. As VP of Customer Success Kevin Hodgkins noted in a recent webinar: “The most important business outcome for us is increased revenue.” With a 25% reduction in customer churn, Hodgkins and his team could “tie revenue very directly to our customer success organization.”
4. Increase customer loyalty, retention, and advocacy
Measuring sentiment is also crucial to engaging customers and increasing their loyalty and advocacy. When businesses have a greater understanding of customers’ emotional signals—what makes them happy, excited, dissatisfied, or indifferent—they can leverage that data into smarter business decisions—or course-correct unfavorable ones—to increase customer loyalty.
To understand the value of customer loyalty, look no further than Apple, which has channeled a number of factors—including unrivaled customer satisfaction and emotional connection—into a value of $352 billion. MBLM’s 2020 Brand Intimacy Study ranked Apple as the third top-performing brand based on customer emotion and loyalty, with the highest score for “Can’t live without.”
When a company focuses on an actionable metric like customer sentiment score to actively improve the customer experience, this can also yield CSAT and NPS improvements. “When customer sentiment score is high,” explained Kevin Hodgkins of Fivetran, “it directly drives improvements in the more traditional metrics around service.” As a result of this, Fivetran was able to increase CSAT from 90% to 95% in just six months. Fivetran has also seen a significant increase in their Net Promoter Score (NPS).
5. Improve products and services
Product performance is vital to a company’s current and long-term success. PwC found that 32% of consumers will abandon a company they love after just one bad experience, and more than half (59%) will leave after several negative experiences.
Sentiment metrics provide vital insights that can be used to monitor product performance, as well as improve products and services. After all, you only get one chance to make a good first impression—and this adage holds especially true for businesses today.
Customer sentiment analysis helps identify the root causes of customer issues, enabling support teams to both retain at-risk customers and prevent others from having similar negative experiences. If your real-time analytics reveal that customers are getting tripped up by the same recurring error, for instance, your engineering team can be alerted to fix the bug immediately. Similarly, if sentiment scores show user frustration with the software updating process, this could be an important indication that a redesign is needed.
A company needs to understand customer feelings about its products and services—not just now, but also over time. By continuously monitoring customer reactions, sentiment analysis helps track significant shifts in consumer behaviors and attitudes. That, in turn, can galvanize important business tweaks such as pricing adjustments, enhanced product launches, and better marketing strategies.
6. Personalize and enhance customer interactions
In today’s tech-savvy world, personalization is more critical than ever, as customers increasingly expect personalized interactions that are tailored to their individual needs and desires. And it’s good for business. According to a Gartner study on the impact of personalization, companies that “focus their personalized messaging around helping consumers can expect 16% more impact on commercial outcomes than those that don’t.”
Sentiment analysis provides support agents with context around individual customers—including past interactions, frustrations, and expectations—so they can customize communications accordingly. Context is everything. Harvard Business Review put it succinctly when they said: “A key component of becoming a living business is conveying exactly the right message, experience, or offer to customers in exactly the right context.”
For example, imagine that a customer is having issues with the latest release of a cloud security application. The product isn’t working properly, and when they call customer service, they are greeted with:
“Hello, thanks for calling Acme. How may I help you?”
“Good afternoon, John. Glad you called! I see that you’re having a software provisioning issue and you’ve had no luck with the latest version. I’m looping in one of my engineers as we speak to get this resolved right now. I also see that you have a question about renewal next month, so let me help clarify that while we’re on the phone.”
Get started now with customer sentiment analysis
For today’s support teams, success depends on “serving a customer’s most relevant needs in the moment.” In a highly competitive market where a buyer can churn at any time, real-time customer sentiment analytics is no longer a “nice-to-have.” It is essential to gaining a deeper understanding of customers, driving brand loyalty, and empowering your company to compete and thrive far into the future.