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Customers Are Speaking – Use Text Analytics to Understand

Many consumer-facing organizations sit on a goldmine of customer feedback but don’t know how to make sense of it.

Data points arrive in tiny fragments, volunteered by customers as product reviews, social media posts, messages to customer service, app reviews, and other inbound communication channels. In raw form, it is hard to consume or act on this information, but algorithms are perfectly suited to convert these bits and pieces into rich sources of usable data, uncover meaning and intent, and aggregate the fragments into a holistic picture of what is most important to customers.


Key to this effort is Natural Language Processing (NLP), an aspect of artificial intelligence that helps computers understand text as humans can. Programmers teach machines how to break down written or spoken language into parts (e.g. nouns, pronouns, verbs, adjectives, adverbs, punctuation, pauses) and overcome ambiguities (e.g. words with multiple meanings, synonyms, misspellings, grammar). The resulting algorithms automate the process of reviewing thousands of customer messages to find commonalities and rank relative importance.


There are many potential business applications for the technology, including as a tool for prioritizing customer initiatives. Product teams can identify the biggest product usage pain points. Marketing teams can shape creative campaigns to fit the most relevant customer emotions and product selection drivers. Customer care teams can anticipate an uptick in customer support to address a specific issue. Results can be viewed over time to track trends in customer sentiment or correlated to business outcomes to explore which customer experiences have the greatest impact on the business.


NLP is at the heart of FocusKPI innovation. Our solutions are built on the most advanced data science, customized to each client’s unique business context. Contact us to learn more.






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