Categorizing (or tagging) surveys is one of the fundamental tasks you’ll need to perform when working with customer (and employee) experience. It’s also an activity that takes up a significant amount of time. On the other hand, it is crucial to have feedback properly categorized to be able to work with it effectively. InsightSofa addresses this with AI survey tagging. The tagging process is lightning-fast, requires no human labor, and is incredibly accurate. How does AI tagging work? Every company is different and requires different categorization. Therefore, InsightSofa offers a place where you can prepare your own tags as needed. Tags can be organized hierarchically, meaning you can use multiple levels of tags. Each tag should represent one of the categories into which you want to divide the feedback. By defining the categories (tags) for the surveys, InsightSofa AI goes through all feedback (including all questions, answers, open comments, etc.) and examines whether any of the created tags characterize the given survey. If so, it assigns the appropriate tag to the survey. InsightSofa AI can assign multiple tags if it makes logical sense. If it assigns a sub-tag, the parent tag is automatically added to the survey as well. The result of this sophisticated activity is the Survey Tagging Report (see below): V tomto reportu máte veškeré získané reporty rozřazené do témat (štítků), které jste si sami definovali. Tím, že jsou štítky víceúrovňové si můžete sloupec rozkliknout a dostat se do rozřazení druhé úrovně (což Vám přináší ještě přesnější data). In this report, you have all obtained reports categorized into the themes (tags) you defined. Since the tags are multi-level, you can expand the column to access the second level of categorization (which provides even more precise data). Like any other report, this one also has a tabular listing. This listing allows you to work with exact data (numbers) or export the results to Excel for further processing outside of InsightSofa.

What is the Overall Experience Score (OES)? The Overall Experience Score (OES) is an innovative methodology for measuring and managing customer and employee experience, developed by InsightSofa. This methodology uses artificial intelligence to analyze the entire survey, including all questions and answers, to assign an overall survey rating on a scale from 0 to 10. Unlike traditional methodologies like NPS, CES, or CSAT, which focus on a single question, OES provides more detailed and accurate data for managing companies. More information about this methodology can be found here. How does the Overall Experience Score work? InsightSofa’s artificial intelligence analyzes surveys by reviewing all questions and answers from the collected survey. Based on this analysis, it assigns several ratings on a scale of 0 – 10 for each survey, from the perspectives of: Customer and employee satisfaction Likelihood of customer and employee recommendation Ease of interaction with the company Relationship with the company (loyalty) Thus, each completed survey receives 4 OES Scores on a scale from 0 to 10: Overall Experience Score Trend Report – What is it used for? The Overall Experience Score (OES) methodology revolutionizes the measurement and management of customer and employee experience. By analyzing the entire survey and assigning ratings based on this, it is the most accurate methodology currently available. The OES Trend Report displays the development of the overall customer opinion over time, and can be viewed from the following perspectives: Customer and employee satisfaction Likelihood of customer and employee recommendation Ease of interaction with the company Relationship with the company (loyalty) For example, if you select the perspective of “Customer Satisfaction,” the OES Trend Report will show the development of your customers’ overall satisfaction based on all the feedback they provided (including sentiment analysis). The Overall Experience Score trend report can be tracked for the entire company or for specific segments. While the report for the whole company provides a “big picture” overview, segments are more useful for managing the company (e.g., what is the sentiment for a particular product, personnel, country, region, etc.?). Filters above each InsightSofa report allow you to display the specific segment you want to monitor. Like all InsightSofa reports, the OES Trend Report includes a tabular section that helps you work with precise data or export results to Excel. For each displayed segment, you can generate a summary with one click, showing what respondents are most concerned with, as well as your strengths and weaknesses for that segment.

The Sentiment Segment Report displays the sentiment analysis of free-text comments from customers or employees. In this report, artificial intelligence plays a crucial role. It reads all comments, recognizes the text using a language model, and assigns an appropriate sentiment to each free comment. These sentiments are: Positive Neutral Negative The recognition of customer sentiment is highly accurate. It can handle complex sentences where one half may seem positive but the other half may not. The LLM is trained for this and objectively assigns the predominant sentiment of the comment. Additionally, InsightSofa’s AI approaches each comment with a completely consistent methodology. The result is an objective assignment of sentiment across all comments. How to Use the Sentiment Segment Report? The Sentiment Segment Report provides a quick overview of the sentiment distribution of customers (or employees) within a selected segment. For example, if you want to see the sentiment after purchasing products, you would select “Products” as the segment. You will immediately see how satisfied customers are after purchasing products, with products displayed side by side. The same can be done for Branches, Staff, Services, Countries, etc. The Sentiment Segment Report shows two important indicators in one. The circle indicates sentiment (how positive the mood is), and the column shows how many free comments (texts) the sentiment was derived from. This allows you to quickly see the relevance of the data obtained. Using filters, you can further specify the analysis of the obtained sentiment. For example: How are customers feeling after using our services (one by one), but only in Germany. The goal of this report is to quickly identify which product/service/person generates the most dissatisfaction and click on that column. InsightSofa will then show you the exact reasons why this is happening, allowing you to implement corrective measures. Like any other InsightSofa report, the Sentiment Segment Report also includes a tabular section. This is useful for precise numerical analysis or further data manipulation in Excel. For each selected segment, you can generate a summary of all comments into a short text that quickly analyzes hundreds and thousands of comments, summarizing the most important issues customers are addressing. It highlights your strengths and weaknesses for each segment. How Does InsightSofa Categorize Sentiment? InsightSofa categorizes sentiment into 7 categories. These categories are useful for batch sentiment analysis. Each comment is labeled as positive (1), neutral (0), or negative (-1). The resulting sentiment is then calculated as the arithmetic average of these measured sentiments. The sentiment categories according to InsightSofa are: Extremely Dissatisfied Dissatisfied Slightly Dissatisfied Neutral Slightly Satisfied Satisfied Extremely Satisfied Why is Measuring Sentiment Important? Tracking the evolution of sentiment in free-text comments in customer or employee experience measurement is crucial for understanding the deeper and often hidden opinions and feelings that affect satisfaction and loyalty. This process allows organizations to gain an authentic and unvarnished view of what their customers or employees truly think. Regularly monitoring sentiment helps identify trends and patterns that may signal changes in mood or attitudes, allowing for quick responses to negative feedback or reinforcing positive experiences. Additionally, it provides valuable insights that can lead to innovations and improvements in processes, products, or work environments. Ultimately, understanding sentiment and its development helps build stronger relationships, increase satisfaction and loyalty, contributing to the long-term success of the organization.  

The AI Sentiment Evolution Report displays the sentiment analysis of free-text comments from customers or employees. In this report, artificial intelligence plays a key role. It reads all comments, recognizes the text using a language model, and assigns an appropriate sentiment to each free comment. These sentiments are: Positive Neutral Negative The recognition of customer sentiment is very accurate. It can handle complex sentences where one half may seem positive but the other half is not. The LLM is trained for this and objectively assigns the predominant sentiment of the comment. Additionally, InsightSofa’s AI approaches each comment with a completely consistent methodology. The result is an objective assignment of sentiment across all comments. How to Use the Sentiment Evolution Report? The Sentiment Evolution Report shows the ratio of positively, neutrally, and negatively inclined customers (or employees). Over time, you can see how these ratios change. It is ideal for tracking and predicting trends. The goal of the organization is for the green area (positively inclined) to continuously increase at the expense of the yellow and red areas. This indicates that customers or employees feel better and better after interacting with your company. The Sentiment Evolution Report can be tracked for the entire company or for specific segments. While the report for the whole company provides a “big picture” overview, segments are more useful for managing the company (e.g., what is the sentiment for a specific product, staff, country, region, etc.?). Filters above each InsightSofa report allow you to display the specific segment you want to monitor.   How Does InsightSofa Categorize Sentiment? InsightSofa categorizes sentiment into 7 categories. These categories are useful for batch sentiment analysis. Each comment is labeled as positive (1), neutral (0), or negative (-1). The resulting sentiment is then calculated as the arithmetic average of these measured sentiments. The sentiment categories according to InsightSofa are: Extremely Dissatisfied Dissatisfied Slightly Dissatisfied Neutral Slightly Satisfied Satisfied Extremely Satisfied Why is Measuring Sentiment Important? Tracking the evolution of sentiment in free-text comments in customer or employee experience measurement is crucial for understanding the deeper and often hidden opinions and feelings that affect satisfaction and loyalty. This process allows organizations to gain an authentic and unvarnished view of what their customers or employees truly think. Regularly monitoring sentiment helps identify trends and patterns that may signal changes in mood or attitudes, allowing for quick responses to negative feedback or reinforcing positive experiences. Additionally, it provides valuable insights that can lead to innovations and improvements in processes, products, or work environments. Ultimately, understanding sentiment and its development helps build stronger relationships, increase satisfaction and loyalty, contributing to the long-term success of the organization.  

The Sentiment Overview Report displays the sentiment analysis of free-text comments from customers or employees. In this report, artificial intelligence plays a crucial role. It reads all comments, recognizes the text using a language model, and assigns an appropriate sentiment to each free comment. These sentiments are: Positive Neutral Negative The recognition of customer sentiment is very accurate. It can handle complex sentences where one half may seem positive but the other half is not. The LLM is trained for this and objectively assigns the predominant sentiment of the comment. Additionally, InsightSofa’s AI approaches each comment with a completely consistent methodology. The result is an objective assignment of sentiment across all comments. How to Use the Sentiment Overview Report? The Sentiment Overview Report displays the distribution of your customers’ or employees’ sentiment over a specific period (from date – to date). At a glance, you see the overall sentiment of customers (or employees) and its breakdown into positive, neutral, and negative customers (or employees). With one click, you can display all “positively inclined” customers (or employees) and analyze in more detail why this is the case. The Sentiment Overview Report includes another very useful feature, which is AI Comment Summarization. With one click, you can see a summary of all comments (for example, only in the segment of negatively inclined customers). What do they think are your strengths? What are the weaknesses? And what do they write about the most? These are questions you’ll have available with just one click. The Sentiment Overview Report can be tracked for the entire company or for specific segments. While the report for the whole company provides a “big picture” overview, segments are more useful for managing the company (e.g., what is the sentiment for a specific product, staff, country, region, etc.?). Filters above each InsightSofa report allow you to display the specific segment you want to monitor.   How Does InsightSofa Categorize Sentiment? InsightSofa categorizes sentiment into 7 categories. These categories are useful for batch sentiment analysis. Each comment is labeled as positive (1), neutral (0), or negative (-1). The resulting sentiment is then calculated as the arithmetic average of these measured sentiments. The sentiment categories according to InsightSofa are: Extremely Dissatisfied Dissatisfied Slightly Dissatisfied Neutral Slightly Satisfied Satisfied Extremely Satisfied Why is Measuring Sentiment Important? Tracking the evolution of sentiment in free-text comments in customer or employee experience measurement is crucial for understanding the deeper and often hidden opinions and feelings that affect satisfaction and loyalty. This process allows organizations to gain an authentic and unvarnished view of what their customers or employees truly think. Regularly monitoring sentiment helps identify trends and patterns that may signal changes in mood or attitudes, allowing for quick responses to negative feedback or reinforcing positive experiences. Additionally, it provides valuable insights that can lead to innovations and improvements in processes, products, or work environments. Ultimately, understanding sentiment and its development helps build stronger relationships, increase satisfaction and loyalty, contributing to the long-term success of the organization.  

The Sentiment Trend Report displays the sentiment analysis of free-text comments from customers or employees. In this report, artificial intelligence plays a crucial role. It reads all comments, recognizes the text using a language model, and assigns an appropriate sentiment to each free comment. These sentiments are: Positive Neutral Negative The recognition of customer sentiment is very accurate. It can handle complex sentences where one half may seem positive but the other half is not. The LLM is trained for this and objectively assigns the predominant sentiment of the comment. Additionally, InsightSofa’s AI approaches each comment with a completely consistent methodology. The result is an objective assignment of sentiment across all comments. How to Use the Sentiment Trend Report? The Sentiment Trend Report shows the evolution of your customers’ (or employees’) sentiment over time. This allows you to easily track whether the overall sentiment among your customers is increasing or decreasing. If it is increasing, it might be time to launch some marketing campaigns. If it is decreasing, more attention needs to be paid to retention efforts. The Sentiment Trend Report can be tracked for the entire company or for specific segments. While the report for the whole company provides a “big picture” overview, segments are more useful for managing the company (e.g., what is the sentiment for a specific product, staff, country, region, etc.?). Filters above each InsightSofa report allow you to display the specific segment you want to monitor. Like every report in InsightSofa, the Sentiment Trend Report also has a tabular section. This is useful if you want to work with the data, export it to Excel, etc. How Does InsightSofa Categorize Sentiment? InsightSofa categorizes sentiment into 7 categories. These categories are useful for batch sentiment analysis. Each comment is labeled as positive (1), neutral (0), or negative (-1). The resulting sentiment is then calculated as the arithmetic average of these measured sentiments. The sentiment categories according to InsightSofa are: Very Dissatisfied Dissatisfied Slightly Dissatisfied Neutral Slightly Satisfied Satisfied Very Satisfied Why is Measuring Sentiment Important? Tracking the evolution of sentiment in free-text comments in customer or employee experience measurement is crucial for understanding the deeper and often hidden opinions and feelings that affect satisfaction and loyalty. This process allows organizations to gain an authentic and unvarnished view of what their customers or employees truly think. Regularly monitoring sentiment helps identify trends and patterns that may signal changes in mood or attitudes, allowing for quick responses to negative feedback or reinforcing positive experiences. Additionally, it provides valuable insights that can lead to innovations and improvements in processes, products, or work environments. Ultimately, understanding sentiment and its development helps build stronger relationships, increase satisfaction and loyalty, contributing to the long-term success of the organization.