Use Cases

Approximately two and a half exabytes of unstructured data are created daily on the internet right now. To put this into perspective, the amount of unstructured data that was created in the past two days is equivalent to the same amount of data that was created from the beginning of humankind through the end of 2003.

Around 80% of all available data over the internet are unstructured and the growth rate gap between unstructured and structured data is only widening. Humans have two ways to process, understand, and harness the informational content of these vast, relatively untapped content sets – manual processing, which is infeasible, or automatic processing, where NLP comes into play.

How can NLP help you?

  1. Insights from Earning Calls. Analysis of the historical relationship between a stock’s sentiment changes vs. its forward returns. The other use case is creating a heat-map of industry-level sentiment trends.
  2. Customer Service. Automation tickets classification all incoming customers’ requests. Rapidly detect disgruntled customers and surface those tickets to the top. There is also a possibility to quickly discover new trends in customers’ questions.
  3. Social Networks Monitoring. Analyze Tweets and/or Facebook posts over a period of time to detect the sentiment of a particular audience. Automatically route social media mentions to team members best fit to response.
  4. Creditworthiness Assessment. Banks in developing countries can assess the scoring of clients with no credit history based on customers’ digital footprints. NLP can analyze geo data, social media activity, browsing behavior and generate a credit score highly predictive of customer further activity.
  5. E-commerce Reviews. Reviews have the power to gain customer trust, and they encourage people to interact with the company. Massive analysis of reviews can also help understand trends and improve products from users’ feedback.