Text Analytics & NLP

The significant growth in the volume and variety of social data and accumulation of unstructured text customer engagement data from multiple touch points. Time to explore and depend on technologies like text analytics and Natural Language Processing (NLP) to extract meaningful classification, modelling and rating and sentiment analysis of such real-time data. NLP and text analytics enables to classify open-ended feedback in the field of customer feedback management, using text and sentiment analysis.


Difficult to classify open-ended customer engagement data from social platforms and CRM systems across the enterprises. The manual reading, understand and classify text need to have someone to read the text, note the contents, and categorize it. Market researchers, for example, often categorize, or “code,” the free-text responses in surveys, and customer engagement data from CRM system. If an organization is only receiving small volume data, possible to have manual review and coding. However, this is not scalable to the real-life millions of data generating every day.


Predictive Customer Modelling which will benefit you to stay informed about the health of each engagement by monitoring communication using Natural Language Processing (NLP) and predictive customer engagement analytics in real-time. The NLP based analytics & dashboards provide an at-a-glance window into your operations and enables you to manage reviewing, reduce cost of operations, and improves efficiencies, rationalize costs and enhance competitiveness, we recommend integrated Natural Language Processing system and Logica Infotech Services Data Scientists, Artificial Intelligence and Text Analytics & NLP consultants have deep domain expertise, process improvement expertise.


Many useful applications are helping customers like for customer engagement analysis based on text analytics and sentiment analysis to classify and aggregate insights for our customers, helping them to optimize resources and initiate actions. The solution automates the reading, classification and rating of survey responses using NLP algorithms. Fast, consistent, and programmable, NLP engines identify words and grammar to find meaning in large amounts of text.

Customer engagement analysis

integrated customer insights analytics solution, primarily driven by data visualization from primary and secondary customer engagement data sources. Using primary customer engagement data from your CRM, Campaigns and Loyalty Programs, it provides a multi-channel, automated workflows based predictive data analysis solution - allowing brands to connect analyze with their customer data and get rich insights about customers engagement patterns and use them for analytics for customer acquisition.

Social Media Listening

Use Sentiment Analysis & Text Analytics through file upload, process APIs, to analyze tons of social text data in to understand the conversations surrounding products, brands, people and services. social posts are full of complex abbreviations, acronyms, and emoticons.

Personalized Engagement

The algorithm classifies customer segments and analyzes your audience data and creates personalized marketing messages for every customer.

Customer Clustering

More effective customers targeting, by automation of upcoming service renewals, suggesting service upgrades, marketing campaigns classification and rating of survey responses using NLP algorithms.

Supervised Learning

The process of algorithm learning from training datasets and by supervising the learning process and as the algorithm is trained it is then possible to make predictions about new observations, significantly lower cost per customer acquisition.

Unsupervised Learning

Unsupervised learning is to model the underlying structure or distribution in the data, detecting patterns in the training data from various aspects of customer experiences, such as CRM, Customer Support, App Store Reviews, Online Surveys and CEM systems.