Business & Finance Technology

What Are Different Text Analytics Capabilities?

In this article, we will discuss the various Text analytics capabilities available. We will also cover their uses, from quantitative results to qualitative insights from unstructured text. We will discuss the role of Text analytics in data science platforms and customer service. In addition, we will discuss how Text analytics can help companies improve their customer service by allowing them to analyze large amounts of unstructured text quickly. The benefits of Text analytics are numerous.

Text analytics for quantitative results

When using text analytics to identify customer feedback, you’re likely looking for qualitative and quantitative results. Text analysis tools can help you construct dashboards and analyze text to find specifics. In addition, they’ll handle volume variance, so you can use them to improve customer satisfaction and brand reputation. Here are some different ways to use text analysis to get quantitative results. 

For example, if you want to measure the influence of political ideology, you can use electoral manifestos. The political parties write these documents to attract and connect with their voters. This method works well for party ideology but is not appropriate for understanding citizen opinions. In addition, this method requires a selection process. To perform text analysis, you must first choose texts from which to conclude. Once you’ve selected the texts, you can apply several different techniques. There are also other platforms that offer text analytics capabilities.

Text analytics for qualitative insights from unstructured text

Different text analytics capabilities enable companies to analyze large amounts of unstructured text and derive meaningful qualitative insights. These tools allow companies to discover insights into customer trends and product performance. They also help researchers explore literature and extract relevant information faster. They can also be used by government bodies and businesses to improve search engine performance, information retrieval systems, and user content recommendation systems. The following are some of the most popular use cases of text analytics.

Text analytics combines statistical, linguistic, and machine learning techniques to process large amounts of unstructured text. It allows businesses to make better decisions by discovering trends, patterns, and insights. These methods include sentiment analysis, entity modeling, and tagging. The key differences between these techniques can lead to unexpected results. Read on to learn more about how text analytics can benefit your business. This article will explore text analytics and how different tools can help you make the most of your data.

Text analytics for customer service

You can use various text analytics capabilities to measure the effectiveness of customer service agents. They can identify customer sentiment, keywords, text structure, and opinions by monitoring text-based conversations. In addition, different text analytics capabilities can alert agents to rudeness, inappropriate language, or other important factors that could impact customer satisfaction. These technologies can help companies better understand how their customers communicate and improve their customer service operations. By examining customer feedback, organizations can develop better customer service policies and increase staff knowledge about the product.

Text analytics can also help companies analyze open-text feedback. This type of feedback is crucial for improving the overall customer experience, and they can identify trends and questions that are not covered in customer surveys. For example, text analytics can identify issues frequently raised by customers, which could inform future marketing efforts. You can also apply these tools to user experience reports and customer questions. However, while text analytics can help companies improve their customer service, they are only effective if shared across the organization.

Text analytics for data science platforms

Depending on the nature of the data, not all text analytics platforms are made equal. Some venues have more than others, which is not always bad. Before investing in a text analytics platform, you’ll want to know your options. For example, if your data includes social media posts, you’ll likely want to focus on those. Another text analytics platform may focus on transactional data, such as email messages.

Text analysis software can provide live reports, including visual representations. Often, it will also be able to filter the data based on date, sentiment, area code, or personal information. Smart search functionality is also a must. Advanced search features let you combine results from multiple data sets and can create search strings based on the data. If you want to analyze your data quickly, choose a text analytics platform that combines these two functions.