Why It's Important To Track Buyer Sentiment
Emotions are what make customers leave feedback after experiencing a company's service. Buyer sentiment analysis can act as a sales strategy that helps you understand your customers better and make better decisions that generate more sales.
Gaining access to the right data can enable you to make proper decisions that will increase buyers' satisfaction and strengthen their loyalty. For instance, when you track buyer sentiment on social media platforms, you discover the crucial problems your customers have, and you take appropriate steps to solve that problem.
Customer Sentiment Analysis - Defined
Customer sentiment analysis is the process of discovering the feelings of customers towards your company's service or product to help you make better business decisions. Customer sentiment analysis requires automation and focuses on online engagement platforms. The process works by using codes, algorithms, and Natural Language Processing to automatically recognize text patterns and classify them as either neutral, positive, or negative reviews.
This software generally uses two parameters to categorize and determine buyer sentiment. The parameters include Polarity, which suggests whether the emotion is positive or negative, and Magnitude, which indicates the extent of the sentiment. Lots of businesses have used customer sentiment analysis to increase their customers' satisfaction and consequently maximize profits.
Why It's Important To Track Customer Sentiment
Understanding your customers' feelings towards your brand is the basis of enhancing customer satisfaction. Here are some reasons why you should track customer sentiment.
To Provide Excellent Customer Service
Customer service is an essential aspect of business management. It's not unusual to see a customer return to patronize a certain brand again after experience good customer service. Studies reveal that up to 80% of customers would switch to an alternative brand when they experience poor customer service. How would you know the status of your customer service? That's what sentiment analysis does; it gives you an insight into the aspects that discourage and please customers. For instance, when you see lots of negative feedbacks on delayed response times, you make relevant decisions to hasten response time.
To Enhance Your Consumer Products and Services
Customer sentiment analysis through surveys, social media posts, or reviews can give you ideas on how to improve your product or service. For instance, customers may mention missing functionalities or provide comments on how to make the product better. You can craft ideas from these comments and inscribe them into your business management model.
As a Means of Optimizing Your Marketing Strategy
Brands get significant ideas from customer sentiment analysis to help them enhance their marketing strategy. It enables you to conform with trends by analyzing customers' feelings toward a new feature, functionality, software, or product. Additionally, you can be one step ahead of your competitor by addressing the product's downsides in the negative comment of the analysis before releasing the product.
To Monitor Your Company's Reputation
Customer sentiment analysis allows you to monitor how customers generally perceive your business. Brands with a good reputation are likely to generate more sales. Positive comments can boost your brand's reputation while negative comments can hurt it, but with customer sentiment analysis, you can quickly address the complaints and minimize the negative review.
How Do You Perform Customer Sentiment Analysis
Customer sentiment analysis is usually an automated process. There are several ways to build your customer sentiment analysis models that conform with your business. Here they are;
Collect Customer Data
Customer data is the most crucial aspect of customer sentiment analysis. The data is helpful to structure and test your sentiment analysis model. You can source data online through:
Live chats are one of the most effective ways to gather customer data. Live chats usually provide accurate data that can help you create and test your customer sentiment model. These data can be collected after launching new products, after onboarding processes, or after customer support tickets have been rectified. You can collect customer data by asking customers to leave feedback after a live chat.
Social Media Platforms
Social media is one of the easiest places to get data as customers usually express themselves more; they also tag and mention brands in engagements. Twitter is a popular platform for performing sentiment analysis because it provides historical and real-time data. Data on social media platforms can be collected through their APIs.
Several sites provide reviews, such as Amazon, Tripadvisor, Capterra, and Google play. You can use a web scraper to help you filter data and give you only relevant ones.
With online surveys, you can collect data on customers' experiences with your product or service. Online survey tools such as Google Forms r SurveyMonkey can allow you to convert answered surveys into XCL or CSV files. Online survey data are usually collected after the onboarding process and even from past customers.
Chatbots have become increasingly popular as a customer service provider due to their advanced intelligent features. Nowadays, chatbots can hold conversations just like humans would do. You can use chatbots for customer sentiment analysis through Machine Learning and Natural Language processing. By integrating chatbots into your website, you can collect data during conversations or after the support ticket has been resolved.
You can collect data by conducting market research. Market research helps you understand current trends and what works best for your customers. Performing buyer sentiment analysis on current trends can remove the skepticism you may have while dealing with markets you are unfamiliar with.
Use Sentiment Analysis Tools
After gathering your data, the next step is to classify the data into neutral, positive, and negative. Online tools like TensorFlow and SpaCy allows you create and test sentiment analysis model. Software developers would find these tools easier to navigate. If you don't have knowledge of machine coding, you can use SaaS software. Saas software is beginner-friendly with a simple user interface. Here are some SaaS tools that you can use for sentiment analysis: Meaning Cloud, IBM Watson, Amazon Comprehend, Lexalytics, and Google Cloud NLP.
Whether it's to express product/service satisfaction or displeasure, every buyer's opinion is a chance for brands to know how their customers perceive them. Hence with customer sentiment analysis, companies can gain insight into their products/services and use it to make relevant decisions to satisfy their customers.