Understanding why customers are interested in a business products and services may be difficult. Regardless of the time and resources that business managers allocate to assessing customer data, obtaining meaningful customer insights can be an uphill climb, one that frequently delivers limited results. For example, consider a manager who deploys text analytics in the hopes of finding out how customers feel about a brand, its products and its services. Text analytics enables a manager to collect customer feedback from many online sources, including blog posts and social networks. It even allows managers to organize all of the customer data that is available into data sets that are accessible at any time. Although text analytics provides a superior data collection service, it fails to provide managers with immediate access to actionable customer insights. Instead, managers will need to complete data mining if they want to transform customer data into meaningful insights. Data mining requires a manager to examine customer data sets and search for insights that are hidden within them. By doing so, a manager can identify customer behaviors and trends and use this information to deploy actionable business improvements. However, data mining often proves to be a complex and time-consuming process, especially for a manager who lacks data mining expertise. And if a manager employs data scientists to perform data mining, he or she may be forced to pay substantial fees to hire these data experts as well.Managers who want to avoid data mining – without sacrificing data analysis – now can leverage Self-Service Text Analysis in combination with text analytics. Together, Self-Service Text Analysis and text analytics empower managers with unprecedented sentiment analysis capabilities. Reap the Benefits of Self-Service Text Analysis Sentiment analysis capabilities ensure that business managers can explore customer feedback and find out whether customers feel positively, negatively or neutrally about a brand, its products and its services. Thus, these capabilities are exceedingly valuable, particularly for managers who are searching for fast, easy ways to deploy meaningful business improvements. Today, Self-Service Text Analysis offers a data analysis service that boasts sentiment analysis capabilities. The service is available for free, making it a viable option for managers at companies across the globe. Plus, Self-Service Text Analysis eliminates the need for data mining, empowering managers to transform customer feedback into customer insights with ease. Self-Service Text Analysis uses a simple upload process that enables managers to generate sentiment analysis reports based on customer feedback. That way, managers can leverage text analytics to obtain large customer data sets and upload this information via Self-Service Text Analysis to produce in-depth reports that highlight customer behaviors and trends in a reader-friendly format. With Self-Service Text Analysis, managers can review interactive PDF (iPDF) reports that illustrate consumer sentiment and other customer data via charts, graphs and other visuals. Each interactive PDF (iPDF) report may contain dozens or hundreds of pages of customer insights – all of which are based on the customer feedback that a manager obtains via text analytics. Furthermore, Self-Service Text Analysis guarantees that managers can generate interactive PDF (iPDF) reports in just minutes. The service requires a manager to upload an Excel spreadsheet that contains user-generated content, and within about 15 minutes of the upload's completion, he or she will receive an interactive PDF (iPDF) report. Therefore, managers won't have to wait long to retrieve meaningful customer insights that they can use to drive their companies forward. Sentiment analysis reporting makes it simple for managers to uncover hidden trends within large customer data sets. Thanks to text analytics and Self-Service Text Analysis, managers can reap the benefits of sentiment analysis reporting for years to come. Summary Business managers want consumer sentiment insights, but obtaining these insights could prove to be difficult. In many instances, text analytics services enable managers to collect customer data from across the web, but evaluating large customer data sets can be overwhelming for those who lack data mining expertise. Fortunately, managers can utilize the combination of text analytics and Self-Service Text Analysis for unparalleled sentiment analysis reporting. Text analytics and Self-Service Text Analysis together enable managers to assess consumer sentiment and other customer data, ensuring that managers can optimize the value of customer feedback consistently.