Automatic analysis of customer statements, feedback and open-ended responses

Introduction

In today's world of data and advanced technology, it has become particularly important to understand and use information coming directly from customers. Developments in artificial intelligence (AI) and natural language processing (NLP) are opening up new opportunities in this area, enabling automated analysis of open-ended responses. These advanced solutions allow companies not only to understand the needs of customers, but also to capture market trends, save resources and accurately analyze what is crucial for making informed and accurate business decisions.

Automatic categorization of statements

Companies face the challenge of not only analyzing and understanding unstructured data - from customer reviews to social media posts to emails, the results of various surveys and other sources of feedback - but also processing and interpreting it effectively. Until now, specialized researchers have painstakingly categorized this data, expending considerable energy and time that could be spent on in-depth analysis and conclusions. Thanks to the developed technology using advanced algorithms in the YourCX panel, the automatic categorization of statements, thanks to the fact that it is integrated into all mechanisms, has never been so efficient, relevant and useful to use.

The system analyzes text for keywords, phrases and context using advanced language models, so it accurately classifies responses into specific categories. This process takes place automatically and in real time, for each language separately. What's more, it is done without the use of external resources, ensuring data security and protecting against potential leakage of sensitive information.

Automating these processes allows companies to respond more quickly and accurately to rapidly changing market needs and customer preferences. This is invaluable for increasing the efficiency and effectiveness of business operations.

Automatic Assignment of Sentiments and Emotions

Automatic topic detection is not enough, it's also good to know what customers' attitudes are toward these topics. YourCX's algorithms are capable of assessing the tone and emotional attitude of statements, allowing you to quickly and accurately assess whether feedback is positive, negative or neutral. Recognizing emotions - such as joy, anger or sadness - gives an even more complete picture of what customers really think and feel. This ability is invaluable for gaining a deeper understanding of respondents' unspoken needs or concerns. Particularly useful with the vastness of data from, for example, Google Maps Opinions.

Application in practice

Automatic analysis of open-ended responses is applicable to many aspects of a company's operations, especially when there are many sources of textual information and the statements to be analyzed are in the thousands:

• Customer Satisfaction Surveys: This technology is invaluable for analyzing large amounts of customer feedback. It helps companies understand what their customers value and what needs improvement.

• Google Maps Feedback: Opinion analysis allows companies to quickly understand how their locations, services or products are perceived by customers. This allows them to better manage their online reputation and respond quickly to market needs. It also allows them to instantly assess the problems of competitors operating in the same market

• Employee Opinion Analysis: In internal surveys, it allows the identification of common problems and opinions, which is essential for the development of the work environment and organizational culture.

• Market Research: By quickly identifying trends and consumer preferences, companies can better adapt their offerings and strategy to changing market needs.

Benefits for companies

Automated opinion analysis brings many benefits to companies:

• Marketing and Sales: A better understanding of customers' emotions allows them to create more engaging and effective marketing campaigns and personalize their offerings.

• Product Management: Feedback from customers is crucial for product development and improvement.

• Customer Service: Using sentiment analysis allows faster identification of problematic topics and proactive resolution of customer issues.

• Human Resource Management: Analyzing employee responses helps identify organizational issues and influences the development of company culture.

• Finance: Automated analysis of customer statements is much faster and, above all, cheaper than manual analysis by skilled researchers

Examples of use in specific industries

E-commerce, online retailer.

Challenge: XYZ received hundreds of customer reviews every day through a variety of channels, such as its website, social media and review sites. The company was struggling to process and analyze this data quickly, delaying its response to customers and making it difficult to identify areas for improvement.

Solution: The introduction of automatic categorization of open-ended responses allowed the company to quickly and accurately analyze reviews and take a proactive approach in responding to them. As a result, the company was able to easily identify common themes and issues, as well as obtain information on customer sentiment toward specific products as well as increase the assortment of brands with which customers were particularly satisfied.

Theresults: the store improved the quality of its customer service, responding quickly to negative feedback and using the collected data to optimize its assortment and marketing strategies.

Travel industry, travel agency

Challenge: the company needed a better understanding of customer preferences and expectations to customize its offerings and improve customer satisfaction.

Solution: Automated categorization allowed the company to analyze feedback and reviews left by customers on various platforms, including the website, social media, travel sites and various forums.

Results: With the insights gained, the company adjusted its travel packages, improving those that were most popular and eliminating offers that were not popular or that caused major problems. The company also saw an increase in customer satisfaction and referrals.

Financial industry, bank

Challenge: The bank wanted to improve its services by responding to customer feedback and inquiries in a more efficient and personalized way.

Solution: automated categorization of open-ended responses helped the bank analyze large volumes of customer feedback, both from online channels and face-to-face interactions in branches.

Results: the bank improved the quality of its services by personalizing offers and responding quickly to customer concerns. The bank also saw an increase in customer trust and satisfaction.

Summary

Automated analysis of open responses is not just a technology of the future - it is an approach that is already transforming the way companies collect and interpret data. With it, companies can analyze large amounts of data quickly and efficiently, providing valuable information that can be used at various levels of the organization. From strategic planning to day-to-day operations, these tools provide a rich source of information that can significantly contribute to improving a company's performance and strengthening its position in the market.

In the digital age, where competition is fierce and customers are increasingly demanding and aware, having knowledge of their needs and preferences is key. Automated open response analysis provides this knowledge in a fast, efficient and scalable way. It's a tool that every company, regardless of industry or size, should implement to stay competitive and respond to rapidly changing market needs.