Text Analytics 101

Published on Mar 14, 2024 by Alec Kotopoulos

Text Analytics Is The Workhorse Of AI When Conducting Market Research With Customers

Text analytics is a pivotal part of market research at the forefront of AI’s involvement in improving research insights. But how does text analytics work, and why is it important for customer experience and decision-making processes? From mechanics to benefits, here is a comprehensive review of text analytics—technology that is revolutionizing the way businesses deal with data.

Understanding Text Analytics: First, text analytics is the science of turning written text into business insights. Mechanically speaking, the combination of deep learning and natural language processing (NLP) technology trains computers to understand human language in all forms and contexts. But parsing words is not all that is required; instead, understanding their meaning, context, and sentiments is needed.

Deep learning is a branch of machine learning that attempts to mimic the learning process of the human brain. It uses neural networks in recognition of patterns and language nuances, hence understanding the text as a human being. This includes deeper analytical tools that can tease out patterns and insights from complex data sets, such as customer sentiment and social media buzz.

Natural Language Processing (NLP)

Natural language processing is technology that allows computers to understand and interpret human language. Whether a person wants to process written text or understand speech, NLP bridges the gap between human communication and machine understanding. It allows text analytics software to go through customer surveys, reviews, and verbatims to turn unstructured data into structured, analyzable information.

Role of Text Analytics in Customer Experience

Text analytics transforms customer experience management into a new dimension where organizations can better understand what is influencing customer feedback. It enables companies to comb through large volumes of data quickly. First, this leads to trend and sentiment identification. It also allows for analyzing emotional tone from the text data when relevant to determine if the customer's response is positive, negative, or neutral. Finally, it provides a deeper understanding of customer sentiment at scale, which guides strategies that are more sophisticated and agile.

Benefits of Text Analytics for research

Text analytics can bring about many advantages when incorporated into the business process as listed below:

  • Superior Customer Understanding: Highly accurate and useful knowledge about a customer's needs, motivations and perceptions equates to more informed decision-making, which can help your company set itself apart in the marketplace.
  • Efficient Data Processing: With the analysis, resources are optimally employed, and the time saved can instead be used to rapidly deliver more strategic decisions.
  • Data-Driven Decisions: Text Analytics can be leveraged to inform new product development, improve brand awareness and loyalty, enhance customer satisfaction and to inform go to market strategies.
  • Enhanced Customer Experience: Text analytics can bring life to the customer journey by making tangible key pain points which when clarified and acted upon lead to a more optimal customer experience.
  • Competitive Advantage: Staying ahead of market trends and customer preferences keeps the organization both relevant and competitive.

How Text Analytics Works: From Data to Decisions

A good example of how Text Analytics works involves any local restaurant manually scanning Yelp reviews to fish out areas of improvement. With text analytics in place, translating the qualitative feedback into quantitative data is performed at scale rendering patterns and trends that might not be obvious otherwise. These prescriptive data can lead to action steps (e.g., menu, ambiance, service, pricing, etc.) changes that yield higher spending and greater loyalty.

Synergy between Text Mining and Analytics

Text mining provides an organization with a cache of unstructured data. Unfortunately, the process of searching and reviewing feedback is labor intensive and inefficient. Text Analytics, however, allows for the interpretation of data and gives depth to the information behind the customer feedback. Combining text mining and text analytics enables a business to reveal both problems and opportunities while understanding the root causes behind them, which makes the whole solution exercise highly effective.

Text Analytics - A Glimpse of the Future

Given a world characterized by continuous data generation, the capability to analyze and act on textual information means a game changer for any business. Text analytics when used in market research provides a window into customers' minds, and it provides companies with adaptability, innovation, and success in the dynamism of market conditions.

Alec Kotopoulos is the VP of Business Development at Socratic Technologies. With over 25 years of experience within Fortune 100 firms where he led market research and data analytics groups, Alec has supported strategic decision-making and research efforts for leading Financial Services, Retail/CPG and Biopharmaceutical companies worldwide. At Socratic, Alec, together with our expert research team, works closely with an array of clients to help ensure the delivery of business centric, needle moving research.

You can contact Alec at [email protected]