At a time when brands are placing so much importance on customer experience (CX), conducting customer sentiment analysis can help you take your brand to the top. Customer sentiment refers to the different emotions that your customers experience—positive or negative—while engaging with your brand. In this age of instant communication, how can brands conduct customer sentiment analysis? Let’s find out.
Emotions are the foundation of strong and enduring relationships. Be it with friends, family, or customers, emotions can bring people together. Consumers undergo a variety of emotions when dealing with brands. They could be delight, excitement, happiness, joy, sadness, frustration, and anger.
Sentiment analysis is the research of words written or said by a person to determine the emotions they’re most likely feeling at the time. Analyzing people’s gestures and expressions is also an accepted method for conducting sentiment analysis.
Sentiment analysis helps brand managers and entrepreneurs understand how consumers feel and what they want from their organizations. It is an excellent way to find out what your target customers think about your company and its products or services.
Consumer sentiment analysis will be the driver for customer-centric brands and will set new standards in customer service.
Contextual conversations and timely solutions to problems improve customer emotions and have a transformational impact on CX. However, it is not practically possible to always meet your client's expectations. Sometimes, prospective clients may not be impressed with the products and services offered or pitched.
Customers expect fast service that works for them on demand at any place, time, or channel. Most customers are willing to use self-service, but they often don’t expect it to work. No wonder it is high time for businesses to get self-service right.
Sales and service teams know too well that situations that make customers unhappy can be resolved without delay, resulting in positive outcomes. However, if immediate attention is not given to miffed customers, the situation can swiftly deteriorate. This results in strained ties between the client and the brand, leading to a decline in sales and renewed purchases, low customer satisfaction
(c-sat) scores, and, ultimately, churn.
The brand’s reputation takes a hit. The brand’s PR, advertising, and marketing teams will go overdrive to revive the image — incurring huge financial costs. Sadly, no one can guarantee to restore the organization’s past glory.
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Now, imagine if your customer-facing teams have a way of knowing what the miffed client or prospect is thinking! That would be a game-changer for sure. That is why conducting a sentiment analysis of customers or prospects can help brands identify where they went wrong in their service or customer outreach program and make amends immediately.
AI and machine learning (ML) can help brands analyze people’s speech and their expressions and track behavioral patterns. Businesses can use the data from sentiment analysis to drive revenue and guide marketing efforts.
Let us understand how sentiment analysis can help brands with a scenario.
Scenario
Jean purchases a multimedia player from a leading electronics retailer. Unfortunately for her, the device stops working within a week after purchase. Upset, Jean decides to contact the brand’s customer support. She knows that the manufacturer’s warranty on her product will solve the problem. Unfortunately, all support agents are busy when Jean dials the customer care number, and now she has to wait a long time to speak to an agent.
Before making the call, Jean wanted to get her multimedia player repaired; however, the long hold time irritates her, and she disconnects the call. Frustrated with how everything turned out so far — Jean vents her anger on social media and tags the electronics brand in her posts.
Within an hour of her social media posts, Jean receives a call from a support agent. The agent tells Jean that her complaint has been acknowledged and that steps are being taken to resolve it.
The agent on the call apologizes to Jean on behalf of the company and tells her that the non-functional multimedia player will be replaced with a new model at no additional cost to her.
Jean was thrilled by the support agent’s behavior and the brand’s commitment to professionalism and decided henceforth she would make all her electronic purchases from this brand and recommend it to family and friends.
Observation
The outcome of this scenario is beneficial for both the customer and the brand. This positive outcome is the result of a successful customer sentiment analysis.
The electronics brand is serious about listening to VoC and is alert across multiple communication channels. A sentiment analysis of Jean’s social media posts identified her anger and unhappiness. That’s why the brand prioritized her issue and offered her a solution that satisfied her.
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Sentiment analysis is important for improving working conditions across industries, improving the quality of products/services, shortening turnaround times, and helping brands uphold service level agreements (SLAs). Let us look at the various ways one can conduct sentiment analysis on customers.
A sentiment analysis tool is AI software that automatically analyzes text data to help you quickly understand how customers feel about your brand, product, or service.
The sentiment analysis tool performs semantic analysis to understand and interpret written or printed matter. Semantic analysis is performed on customer reviews received or available across various channels, such as online forums, comments on product/service pages, opinion pieces, and social media, to understand whether the feedback is positive, negative, or neutral.
If you are wondering what semantic analysis is, it is a subfield of natural language processing (NLP) that attempts to understand all forms of content that are written or printed.
Insightful information such as context, emotions, and sentiments is extracted from the available data. These insights can give brands a clear picture of their customers' thinking.
Also read: Application Of Customer Sentiment Analysis In Businesses
Companies leverage audience sentiment analysis to better understand consumers, enhance decision-making, and grow their businesses. Truth be told, every organization, irrespective of size or industry, should make customer sentiment analysis imperative.
It enables you to enhance your business strategy, CX, and brand perception, helping you better understand and classify prospects and customers and make informed decisions.
ThinkOwl, the AI-powered helpdesk software, helps you keep a finger on your customers' pulse. The helpdesk’s analytics and reporting feature uses AI to keep you updated on your customers’ moods and satisfaction.
It helps you understand what’s important for your clients and your brand through semantic topic analysis, custom KPI analytics, and dedicated reports that provide comprehensive data on customer satisfaction and team efficiency. It also updates your customers' requirements with easily understood graphics/visualizations.
With ThinkOwl, you can recognize where problems arise in the customer journey and react immediately with appropriate measures. Meet client expectations, ensure there is value in what you have to offer, and amaze your customers with stellar CX. Sign up now for a 30-day free trial.