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As we shift from a product-centric to a customer-centric landscape, companies need to focus more on customer satisfaction. Customer experience has become the need of the hour, regardless of whether you’re a product-based or a service-based business.
Over the years, businesses have relied on customer feedback to tailor their services. This approach is reactive and could possibly lead to poor customer satisfaction.
With sentiment analysis, you can proactively monitor customer experiences. Here’s how you can improve customer satisfaction with sentiment analysis.
What is Sentiment Analysis?
“What is sentiment analysis” is the first question that may cross your mind. The definition of sentiment analysis can vary, and more often than not, it’s complicated. It refers to the process of studying and quantifying subjective information using text analysis, computation linguistics, and natural language processing.
But in a nutshell, sentiment analysis is nothing but the process of identifying sentiments of a provided piece of content. It helps you determine whether a written text has a positive or negative emotion or whether it emanates fear, anger, happiness, or sadness.
By sentiment analysis, you can identify what your customers think about your brand or products. You can use this opinion to make necessary changes and improve customer satisfaction.
But, how to perform sentiment analysis? This question has daunted brands for years, and rightly so. It has been a complex process that requires expert knowledge of AI algorithms and languages like R and Python.
However, the process has been significantly simplified now. Several software solutions are available that help you conduct sentiment analysis without any prerequisite technical skills.
Why Is Customer Satisfaction Important?
Customer satisfaction is the cornerstone of business success. It lays the foundation for customer loyalty and helps you identify unhappy customers. Furthermore, it enables you to identify why your customers aren’t happy and how to provide them with the desired experience.
A company with a high customer satisfaction score is likely to attract more customers and generate greater profits.
How to Use Sentiment Analysis to Improve Customer Satisfaction?
By understanding how your customers feel about your brand, you can make informed decisions to improve their experience. Here’s how you can use sentiment analysis to increase customer satisfaction.
1. Path Analysis to Predict Failure
Many companies don’t offer any products. Instead, they provide services. While services are more flexible to offer than products, measuring customer satisfaction for services can be a hurdle.
Path analysis can be an excellent tool to anticipate the failures of a product or service. It helps you predict the customer’s purchasing path, which helps you analyze how your customers respond to your services.
2. Product Development
Creating a product or service that resolves your customers’ problems can be challenging. But what’s more difficult is to decide on a competitive price. The price shouldn’t be so low that it curbs your profits. But it shouldn’t be too high either. You should always look for the middle ground.
Sentimental analysis of social media networks like Twitter can help you understand how your customers are responding to different prices. You can also combine social analysis with affinity analysis to obtain in-depth insights into how your product fits your customers’ requirements.
3. Customer Service
Customer service is one of the key elements of customer satisfaction. No matter how great your product or service is, your customers will always have some issues. Therefore, it’s critical to have a well-trained customer support team in place that resolves your customers’ problems.
But sometimes, it’s not possible for your support team to accurately determine how your customers are feeling. This can lead to improper use of words and tone, resulting in a bad customer experience.
Sentiment analysis can help you resolve this issue. By conducting proactive sentiment analysis after a new product launch, you can determine your customers’ general mood. You can then utilize this sentiment to predict customer behavior when they contact your customer support team.
4. Channel Management
Retailers can reduce operational costs by shutting down retail outlets and replacing them with cost-effective channels like telesales and e-commerce. But customers may prefer retail outlets over digital channels. In such cases, switching your sales channels can turn out to be detrimental to your business.
Using geospatial analytics, you can determine the response rate of your customers for various types of outlets. This way, you can identify stores that your customers love and remain open, along with those that aren’t popular and can be closed.
Conclusion
If used correctly, sentiment analysis can help you understand your customers’ voices and how they feel about your brand and products. With this data, you can tailor your products and customer services to provide your customers with the best experience.
Customer satisfaction is essential for every business, and sentiment analysis can help you streamline your customer satisfaction efforts.
