In its simplest definition, text analysis is the process of going through words within a document, sentence, or sub sentence to extract relevant information. If you want to get a little bit more technical, text analysis is where you take unstructured text or data. You then use the relevant text analysis software and techniques to classify and extract meaningful information.

Think about text analysis like some kind of distillation process with the aim of finding trends or themes within the data.

Is it possible to do text analysis manually? Yes, it is; you can, for example, use an Excel spreadsheet to go through unstructured data. However, for greater efficiency, many organizations use specific software for text analysis.

Text analysis software incorporates the use of artificial intelligence, such as machine learning and natural language processing.

Text analysis yields qualitative data, while you use text analytics to get quantitative data. With the latter, you will find the use of visual cues such as graphs or charts to present findings. Eventually, you transform the quantitative data into qualitative by getting the relevant insights from the numbers.

You may find some people use the word text mining interchangeably with text analysis. While there could be subtle differences, the processes of obtaining data tend to follow the same patterns.

> Organizing Data

All the information or data you collect will not benefit you if you do not find a way to structure it. You must, for example, analyze customer feedback so that you know the areas you need to improve.

With so many avenues available for collecting feedback, you must find a way to pick only what is essential. Manually sifting through the material would be time-consuming and prone to human errors.

Text analysis helps you complete the task in the shortest time possible. It allows you to eliminate any chances of human fallibility, resulting in tainting the information you get.

> Valuable Insights for Decision Making

All the information or data you collect will not benefit you if you do not find a way to structure it. You must, for example, analyze customer feedback so that you know the areas you need to improve.

With so many avenues available for collecting feedback, you must find a way to pick only what is essential. Manually sifting through the material would be time-consuming and prone to human errors.

Text analysis helps you complete the task in the shortest time possible. It allows you to eliminate any chances of human fallibility, resulting in tainting the information you get.

> Feedback in Real-Time

The digital or online space has opened up a world where information is moving 24/7. You may be at home in bed, but customers are busy giving their feedback on your product or services.

It would not be humanly possible for you or your team to be on every platform every minute. The right text analysis software and techniques will let you know what is happening in real-time. All you need is the right training model, and the software can pick sentiments that may be detrimental to your business, allowing you to react proactively.

> Consistency

If someone were to give you mounds of data to work on every day, how do you think it would go? Fatigue, inconsistencies, and human errors would, at some point, come into play. The beauty of machines or software is, program it correctly and you can sit back and relax.

a Gathering of Data

An organization receives data from internal and external sources.

? Internal sources include emails, customer service, chat, and support tickets. Other resources are surveys, Net promoter scores (NPS), product Analytics and databases.

? External data is normally on the web and includes news reports, social media, forums, and online reviews. Companies have the option of using tools such as APIs, web scraping tools, and open data sets to get such information about their brand or company.

b Preparing the Data

You have many options for automating text analysis using appropriate software, such as natural language processing techniques. Such include

? Tokenization, parsing, and part of speech tagging
? Dependency parsing
? Constituency parsing
? Stemming and lemmatization
? Stop word removal

c Analyzing the Text Data

There are many methods available for analyzing text data.

? Text classification, tagging, or categorization requires looking at content and then assigning relevant tags. It covers areas like sentiment analysis for positive or negative content, language detection, topic detection, and intent detection.
? Similar content clustering
? Word frequency detection
? Data visualization with cues such as charts and graphs
? Text summarization for the identification of critical parts within the text

> Monitoring of social media social media can make or break your business. Feedback is in real-time and is an excellent place to collect fantastic insights. You can know how your customers feel about your brand through sentiment analysis.

> Monitoring your brand by having a pulse on what people are saying about it on the different online platforms. Analyzing brand mentions gives you insights into your standing within the industry and anything that may damage your reputation. You also get to monitor perception towards your brand. With up to 81% of online buyers researching a company before purchasing, brand perception monitoring and analysis are critical.

>You can give better customer service by streamlining processes in areas like ticketing, prioritizing urgent areas, and collecting both negative and positive feedback from the customers

> Customer feedback and voice of customer (VOC) to help with client retention by ensuring customer satisfaction. Text analysis allows you to explore open-ended questions that you collect during surveys for a clearer understanding of what the customer is really trying to tell you.

> Business intelligence by understanding things like sales trends, competitor analysis, and the overall business environment

>Assist with sales and marketing by taking care of repetitive or manual tasks. The use of insights such as intent detection will tell you which leads are likely to turn into conversions.

> Product analytics to let you know what the customers think or feel about your offerings.

It would be misleading for us to say that text analysis is a simple process. If you decide to do it manually, it is time-consuming and can be very expensive. Automating the process is expensive and may not be something that startups or smaller companies may afford.

Investing in artificial intelligence or machine learning may divert resources away from your business. You need the right partner to handle text analysis for you. Tatvam has the right tools to help you manage customer feedback.
We collect the information from different channels, filter them, and highlight what needs urgent attention or addressing. We aim to analyze and review the content so that you have actionable insights.

We use artificial intelligence to generate insights into trends and patterns that you can then utilize in your business to improve the customer experience. Tatvam will also provide you with information on what your competitors are doing. In this way, you are always in the know and can leverage the information you have to stay ahead of the pack.

The business environment is very challenging, and you receive a lot of information every single day. Not taking advantage of such can lead to the demise of a company. It also helps to have a way to sift through the tons of information, and only take those insights that will be beneficial to your business.

Text analysis will no longer be something that keeps you up on most nights with the right partner. Tatvam is the right partner for you.