Natural Language Processing Makes Sense of Consulting Data

Consultants offer NLP-enhanced insights to clients

With the vast amounts of data across enterprises and organizations, executives are often eager to access and understand its value. Natural language processing, or NLP, is a software solution that can gather, parse, extract and provide insights into such data. NLP solutions review unstructured data in order to scour large amounts of content, such as: text documents, images, emails, slide sets and an abundance of social media postings. The underlying software often uses machine learning or other artificial intelligence approaches. Consultants are often working in concert with such software solutions in order to provide clients added value overviews of their own data.

Consultants can use NLP with clients in multiple ways. Various NLP software tools can perform textual identification of locations, persons’ names or entities. With those identifications, connections can be made and relationships understood throughout documents or data sets. Added value can be applied to such data, such as annotation and categorization. Not only can such solutions bring insights into data but it can also save time by automating work processes.

Examples of consultants and analysts helping clients with NLP are numerous. One case study includes a boutique consultancy using NLP to help a ratings agency automatically gather the data it needed, parsing through a massive collection of unstructured documents. The solution processed the data and parsed the key information. In fact, a totally new workflow process was enabled by the technology because is converted a complicated manual process into a more streamlined and efficient one, as well as increasing data quality.
Sentiment analysis of social media is another way that consultancies are using NLP.  Uses of NLP include automatically adding tags to product catalogs. A case study of a consultancy helping a government agency to gauge social media shows the power of this technology. The Kuwaiti government wanted to know how the public was responding to given published documents. By working with consultants and specific software solutions, they were able to gain analytics on how people responded. Twitter responses were created into an infographic, reporting key public sentiment to the government executives.

Within the financial services industry, NLP can be used in various ways. The right NLP solutions can gauge stock analysis in real-time, alert of key executive movements, analyze public sentiment of companies/brands, provide awareness of insider trading and monitor important news.

Econsultancy profiled the usage of NLP in marketing functions.  This publication highlighted the importance of finding “named entities” as a powerful tool for marketing entities. The right NLP solution can scan multiple resources, seeking out and confirming the mention of these named companies, brands or products. The positive/negative connotations and demographics of these comments/data can also be gauged by NLP.

Even customer service roles can potentially be helped by NLP technologies. An overview in TechTarget examined the use of NLP in customer service areas by using speech analytics and helping to organize the order of workflow tasks. Chatbot interactions may even be able to be examined through NLP technologies in order to improve the overall customer service experience.

Conclusion

The promise of obtaining deep insights from unstructured data, even in real-time, may be greatly intriguing to C-suite executives. As NLP continues its trajectory of powerful analytical capabilities and time savings, businesses may clamor to mine its troves of data for even greater value