Using Text Analytics for Market Research

In today’s time, businesses receive data in millions. From comments on social media posts to reviews, there is a lot of customer data in need of analysis and sorting. If such a task is assigned to humans, it becomes impossible to achieve. Luckily, we have technologies to help us understand client sentiments. One of them is text analytics solutions which assist individuals in getting actionable insight into market trends. You could analyze surveys or any open-ended textual data to find your position in the market and that of your competitor. Text analytics for market research has gained popularity in previous years because it helps organizations visualize their performance.

In the following article, we provide detailed insight into how to perform text analytics and why market research uses text analytics.

Defining Text Analytics?

Text analytics helps decode the meaning hidden in the text. It is a qualitative research method. Whether a review has positive sentiments or negative sentiments, you can interpret hidden emotions through analytics solutions.

By using text analytics, organizations can bring improvements to their work. If your employees or customers have negative reviews about an aspect, you can introduce timely reforms or launch new strategies. This automated process can easily extract and translate vital information. You can even discover patterns and trends while performing market research. When it comes to market research, nothing can be more suitable than text analysis software. Text analysis aids individuals in market research and examines datasets in real-time.

How Does Text Analysis work?

Most analytics solutions available in the market run on the same principle. The process starts with dataset creation. You can create a spreadsheet in excel and provide it to your system. Your excel sheet will have columns like rating, demographics, and open-ended text fields. It depends on whether you are analyzing social media posts or reviews. Usually, large datasets require significant time for code assignment, but the text analysis software speeds up the process. Once all the data is available, it starts assigning emotions to each sentence. The software points out topics and detects emotions. For example, your system recognizes comments about employees and their hidden emotions.

Using Market Research Text Analytics:

Market research comprises collecting information about how well your product is doing in the market, how many people like your brand, and where you stand in the market. With the help of market research text analytics, a business can find information on the following things simultaneously:

Customer Experience Management  

Using text analytics helps find customers’ experiences. If people are pleased with your services, they come back for more. Using the data generated from the text analytics software, you could make better decisions for higher client satisfaction.

Discovering Product Success 

Text analysis also provides insight into product success. If your products need improvements, you could find suggestions by analyzing client comments. Similarly, your company could invest more in a popular product.

Determining Brand Experience 

With Text analytics, you can download conversations from multiple sources. These can be analyzed to see how effective are your marketing campaigns and what the return on investment for your brand is. Maintaining your brand image is crucial and can only be done with predictive analytics software.

Finding Negative Emotions of Customer Segments 

Text analytics handles the crucial task of identifying negative emotions. When companies find negative thoughts in time, they can prevent future crises and potential losses. Often small issues can irritate clients and push them toward your competitors. So analyzing responses and finding negative opinions should be part of your strategy.

Understanding Topic Model:

Topic modeling is a part of unsupervised machine learning and text analytics. The method allows you to scan documents, detect patterns and find clusters of similar terms. You don’t need to train your system or prepare it in advance. All you need is a dataset.

How is Text Analysis Accuracy Measured?

A significant question in text analytics is about its accuracy. We should verify that our analysis is precise and gives us accurate results. For this, we focus on two terms precision and recall. The higher the recall and precision, the higher the system’s accuracy.

Using Natural Language Processing in Text Analytics

Along with machine learning algorithms and artificially intelligent technologies, text analytics also uses natural language processing. NLP helps organize and find patterns in unstructured datasets. Normalization, lemmatization, and tokenization are some of the pre-processing tasks performed with the help of NLP.

Significance of Text Analytics:

Text analytics allows people to see sentiments in a topic and how often a topic appears in a paragraph. Your dataset might have thousands or millions of reviews. From them, you find which ones are for employees, which mention your products, and which ones are about your top-level management. Moreover, you can find the ratio of positive and negative comments and have an idea about clients’ emotions. Individuals can deploy such systems to train chatbots or manage marketing teams within an organization.

Using Text Analytics in Real-life:

Text Analytics is used in every field. Whether you need to analyze customer feedback or lengthy surveys, text-based analytics will make your task achievable. You can make derive qualitative and quantitative facts from any dataset. Customer service is one department that can use text analytics in several ways. When it comes to customer services teams, they have to answer client queries and satisfy every individual. With text analytics solutions, people will need to spend less time on repetitive questions to enhance their performance.

Another section where text analytics prove useful is the marketing department. The marketing team has to engage the audience. Using text analytics, employees can know about their leads and potential clients. Furthermore, you can find out how people feel about a service. Your marketing team could look into private messages, support tickets, phone transcripts, or live chat conversations. Once you have all the data sources and NLP training, you can gather relevant insights.

Industries Providing Text Analysis Services:

Several companies and industries provide individuals with customer management software solutions. Their advanced solutions can assist in managing and analyzing crucial data. Some of the prominent service providers are:

SAS Institute Inc.


It provides many analytics software which manages massive datasets. Their technology also helps report on data that comes in handy for decision-making.

Clarabridge, Inc.

The company provides customer experience software. Their AI-powered mechanisms analyze text from various social media platforms, chats, and emails.

IBM Corporation 

Another prominent company known for its computing and data analytic solutions is IBM Corporation. Even though the company is more famous for its computers, its analysis solutions also help people analyze relevant data.

Tools for Text Analytics:

We have multiple text analytics software, like Your CRM, Excel, and social listening tools. These three systems are for beginners who have lesser knowledge of working with analytics solutions. However, if you have adequate technical knowledge, you should use tools like Google NLP products, Amazon Comprehend, and Azure Text Analysis API. Many large organizations use these NLP-powered systems to analyze conversations. Similarly, Intent Manager by Pure Speech Technology and analytical tools from VizRefra are flexible tools that provide meaningful insights.

Performing Market Research for your Brand Using Authentic Text Analytics Solutions:

Text analytics is the modern solution for all of our problems. Whether individuals need to analyze client feedback or social media posts, nothing works better than text analytics solutions. This qualitative analysis mechanism helps decode sentiments in human language, which influences business decisions. However, the best use of text analytics is in market research, where you can find insights about a product’s success, client satisfaction, and overall brand reputation. Using suggestions from text analytic software, individuals can perform better.

Here at VizRefra, we have advanced text analysis solutions and sentiment analysis tools to help businesses achieve their goals. Our customized services help individuals efficiently upgrade their business-level execution.