Customer reviews play a key role in determining the success of your brand, especially online. According to BrightLocal, 93% of local customers use online reviews to determine whether a local business is “good” or “bad”. By using sentiment analysis to analyze customer reviews, you can protect your brand’s reputation online and gain a competitive advantage.
What Is Customer Review Analysis?
Customer review analysis involves examining feedback text with natural language processing to extract valuable insights, such as the level of satisfaction. With text analytics tools, you can easily analyze large volumes of customer reviews. These tools use techniques such as sentiment analysis, content classification, and content summarization. Sentiment analysis is a popular technique used for analyzing customer reviews.
Why Customer Sentiment Analysis Works
Customer sentiment analysis categorizes reviews as either positive, negative, or neutral. It combines natural language processing and machine learning techniques to assign sentiment scores, which represent a numerical scale ranging from positive to negative. As a result, you can automatically determine whether a customer has had a negative or positive experience.
How Customer Review Sentiment Analysis Can Protect Your Brand
Using sentiment analysis to analyze customer reviews will allow you to:
1. Respond to negative customer reviews in a timely way
Spiegel Medill Research Center discovered that 82% of shoppers specifically seek out negative reviews. Although negative customer reviews can hurt your brand’s reputation, handling them well can show customers that you care. With a sentiment analytics tool, you can automatically detect polarity in consumer reviews and reply to negative feedback in a timely way.
2. Increase brand loyalty and reduce customer churn
In addition to responding to negative reviews, sentiment analytics tools will help you increase your brand loyalty and reduce your overall customer churn. Prospects will also appreciate that you genuinely care about the experiences of your existing customers, making them more likely to purchase.
3. Improve the quality of your products and services
Listening to your customers’ voices will help you know what they like and don’t like about your products and services. This will give you a better understanding of their requirements with insights on what’s working and what you have to improve on, helping you become more competitive.
4. Identify trends and make predictions
Besides tracking the polarity of customer reviews, sentiment analysis can help you identify trends. For example, you will be able to identify changes in sentiment in correlation with the season of the year, the time of the day, or the addition of a new feature. This will help you understand what causes variations in demands, allowing you to make better predictions for the future.
5. Recognize new market segments
With sentiment analysis, you can identify variations in sentiment in correlation with the location of the customer. For instance, if a number of customer reviews from a particular location are negative with a recurring keyword, such as a menu item, you can tailor your menu to resolve their issues. Moreover, you will get to recognize a new market segment, allowing you to tailor your product and service offerings to suit their special needs.
In addition to protecting your brand’s reputation online, sentiment analysis is a great way to perform competitor analysis and discover their strengths and weaknesses.
The Benefits Of Customer Feedback Text Analysis
1. Handles large volumes of data
Customer feedback is valuable for decision making. However, it can be difficult to analyze feedbacks, especially when you have hundreds or more. With text analysis, you can extract key insights from large volumes of customer reviews that will help you improve your customer experience.
2. Considers the context of the review
Although ratings give you an idea of a customer’s experience, it is quantitative and lacks context. However, text analysis provides a more accurate rating while considering the context of the customer’s qualitative review—especially when their feedback answers a number of open-ended questions.
3. Makes your team more productive
Review analysis removes the need for your team to take on the redundant and repetitive task of monitoring customer reviews. As a result, they will have more time to focus on the more productive tasks that require higher levels of skills. Your customer service support will also be able to track negative customer reviews more efficiently.
4. Identifies trends in bad experiences
Review analysis makes it easier for you to determine the common cause of bad experiences. For example, if a series of negative reviews have recurring keywords such as “checkout”, it could be the root cause of their dissatisfaction.
5. Extracts customer insights reliably
Text analysis uses AI algorithms and models that have been trained with large volumes of data. Thus, text analytics tools are reliable for extracting valuable consumer insights.
Nadee is a freelance B2B tech copywriter. She writes marketing content for B2B technology companies around the world. Her customer-centric approach ensures that your audience can relate to her words. To learn more, get in touch.
