Are you looking to improve your brand reputation online? Why not implement an Artificial Intelligence (AI) solution to help you monitor your customer sentiments?
People conduct sentiment analysis on customers’ speech or written words to determine whether they are positive, negative or neutral about their brand interactions. It has become increasingly common for businesses to use artificial intelligence platforms to investigate how people feel.
What possibilities exist in this fascinating and evolving area? Let us find out.
Why Customer Sentiment Analysis Matters in Brand Reputation
Customer sentiment analysis is essential for understanding how people feel about your brand, products, or services. By analysing online communications like social media posts, reviews, and comments, businesses can gauge public opinion and customer satisfaction. To do so, you should consider using AI-powered sentiment analysis tools.
Examples here include Talkwalker, which excels in social media monitoring and AI-powered sentiment analysis; Brandwatch, known for tracking mentions and sentiment across various platforms; and MonkeyLearn, offering customizable machine learning models for comprehensive text analysis. Other notable tools are Qualaroo, which integrates with websites to capture and analyse user feedback in real-time, and Sprout Social, which provides robust social listening and sentiment analysis features.
By using such insights, companies can maintain and enhance their online brand reputation, allowing them to address issues promptly, and to make data-driven decisions to improve customer experience.
Examining Feedback Across All Channels
AI is exceptionally well-suited for sentiment analysis because it can efficiently process massive amounts of data. Many customers connect with businesses through email, live chat interfaces, social media and more. Those channels collectively receive information that company leaders can use to determine how people feel about a brand.
A furniture business took this approach by implementing an AI-powered omnichannel listening solution. Executives hoped to use it to eliminate data silos and improve sharing feedback across teams.
Brand representatives have unlocked new insights about people’s wants and needs by analyzing customer feelings this way. This allows employees to work together to fulfill them, increasing the chances shoppers will show ongoing loyalty rather than considering other outlets.
The chosen AI platform allows users to generate search results from related topics, meaning people can run analyses without inputting exact keyword phrases or spelling things correctly. The technology’s features and user-friendliness allow company officials to use artificial intelligence in powerful ways to suit their business needs, learning more about customers in the process.
Responding Appropriately to Customers’ Emotions
It’s not always easy for a brand representative to gauge how someone feels from a single email interaction or phone call. However, AI sentiment analysis tools monitor more aspects of the conversation than humans can consciously achieve, giving employees the advantage when knowing what to say to calm upset customers.
Some companies have also deployed tools to detect people’s feelings in real time, allowing customer service agents to understand when and how to best help them. Anyone who has worked in a call center knows how quickly someone’s emotions can change depending on how the exchange progresses. Sentiment analysis tools could help an agent understand that someone is getting more upset sooner, allowing the professional to diffuse the situation.
One commercially available product uses an AI bot to transcribe all conversations, saving managers from listening to every interaction from start to finish during reviews. The sentiment analysis component includes a real-time assistant bot that supports representatives in quickly addressing concerns. Users receive real-time coaching, increasing the chances of successfully resolving problems and leaving customers satisfied with the interactions.
Such tools should make conversations less stressful and more productive for everyone because they increase understanding and aid agents in getting to the root of the problem faster. Such outcomes elevate brand perceptions by positioning companies’ representatives as problem-solvers committed to making things right.
Customers are more likely to remember everything that went well rather than focusing on the initial issues that upset them. Those successes collectively strengthen positive opinions. Research indicates approximately 80% of people feel more emotionally connected to brands when customer service agents solve their problems.
Gaining Richer Insights into Customers’ Experiences
Brands have unprecedented opportunities to interact with customers from anywhere. One of the strongest examples of this comes from virtual assistants. Many companies have branded chatbots and voice recognition tools that provide people with positive experiences while getting valuable information about them. What are the top reasons for interacting with a chatbot instead of picking up the phone or emailing the customer service department? Sentiment analysis platforms can reveal those details.
Research indicates the intelligent virtual assistant market will be worth $35.1 billion by 2025, illustrating the consumer interest and various business use cases for the technology. Depending on how companies use sentiment analysis tools, they can get insights about people’s feelings through online and offline channels. One benefit of examining virtual assistant conversations is that they could occur at any time of the day or night worldwide.
Brands can also apply sentiment analysis tools to learn more about shoppers’ in-store experiences. One example comes from Coles, an Australian supermarket brand. Customers reviewed their shopping trips by filling out surveys, but employees found a disconnect between numerical scores and issues experienced. A shopper might choose a high number but mention that their favorite cereal was not in stock or they could not find a parking place.
Executives dealt with the matter by deploying an AI solution that could categorize the expressed sentiments into up to 40 themes and provide stores with the top three areas for improvement. Leaders can also see how customers’ feelings change based on the time of day, the number of staff on shift or other parameters.
Are You Ready to Try Sentiment Analysis?
These examples show how AI can significantly improve and expedite sentiment analysis efforts, helping people get useful insights to build and maintain their brands. Since the technology has gradually become more commercially available, it is now accessible to more company leaders interested in exploring what it can do.
Eleanor Hecks is editor-in-chief at Designerly Magazine. She was the creative director at a digital marketing agency before becoming a full-time freelance designer. Eleanor lives in Philly with her husband and pup, Bear.
Excellent post! I appreciate how well you addressed this subject. Both the writing and the thoughts were excellent. We appreciate you sharing your knowledge and anticipating more from you to read. Keep up the superb work!
This is a great read on leveraging AI for customer sentiment analysis! The integration of AI into monitoring brand reputation can truly transform how businesses understand and respond to customer feedback. By utilizing advanced algorithms, companies can gain deeper insights into consumer emotions and trends, allowing for more proactive and tailored responses. It’s exciting to see how AI is not only enhancing customer service but also driving strategic improvements. Thanks for sharing these valuable insights!
“Excellent post! 🤖📊 Implementing AI for customer sentiment analysis seems like a game-changer for brand reputation. I’m eager to see how these tools can provide deeper insights and improve customer engagement. Thanks for sharing these innovative strategies!”