Different industries use the same NLP techniques and their combinations to solve different use-cases
We research, design & build AI technologies to help our clients solve real-world problems using data
Data in the text form is abundant, and it’s the most common unstructured data type. Companies have access to thousands, if not millions, of internal documents. It is only to be increased by every chat, email, or meeting within the organisation. The value in these and other accessible bodies of text can be leveraged to create value through many downstream tasks. Our text analytics platform KNOW MORE currently supports text and audio format data with 19 customisable solutions such as automated communication, sentiment analysis, named entity recognition, semantic search, and text summarisation.
CTO, Contoso Pty Ltd
I placed an order for an m.2 SSD and samsung m5 monitor for pickup expecting to have it within an hour or two (like their competitors). It’s been 24 now and my order is still processing. The item was in stock when I placed (and paid) for my order.
The live-chat feature on their website offers virtually no help. How much longer will this company continue to use Covid as an excuse for poor customer service? I can understand if the shop is busy but surely some transparency is in order.
When I spoke with the live chat operator they tried to charge me an extra $10 for ‘express pickup’ despite already waiting 24 hours. For comparison I placed an order with Amazon and it was ready for pickup within an hour with no additional charge. I won’t be doing business with this company again and would recommend anyone else not to either.
Different industries use the same NLP techniques and their combinations to solve different use-cases
The best customers, we’re told, are loyal ones. They cost less to serve, they’re usually willing to pay more than other customers, and they often act as word-of-mouth marketers for your company. Win loyalty, therefore, and profits will follow as night follows day.
Identify profitable customers and understand the reasons for their loyalty on a scale
Semi-supervised customer segmentation, sentiment analysis and named entity recognition
Businesses can train NLP models utilizing their existing documentation resources. Then, the NLP-backed financial statement analyzer swims through hundreds of these documents to extract and consolidate the most relevant, insightful information.
Use contact centre transcriptions to understand customers. Identify money laundering or other fraudulent situations.
Text to speech, speech to text and audio classification for automated ticket creation.
Text processing in healthcare could boost patients’ understanding of EHR portals, opening up opportunities to make them more aware of their health. NLP can be the front-runner in assessing and improving the quality of healthcare by measuring physician performance and identifying gaps in care delivery.
Finding similar patterns in doctors’ reports; identifying patterns in patient claims data
Summarizing lengthy blocks of narrative text, such as a clinical note or academic Journal articles by identifying key concepts or phrases present in the source material
Legal research lies at the heart of the legal profession. Any legal advice attorneys provide has to stay in line with constitutional, statutory (as created by legislators), and case law (as created by judges).
Identify topics and keywords in the discovery document and find patterns in the defendant’s communications
NLP-powered legal search engines can translate plain language into “legalese,” making it easier to sift through relevant documents and cases.
The insurance industry generates large amounts of text data due to claims, insurance policies, and customer relationships This makes it difficult for insurance CIOs to take advantage of their unstructured data using traditional techniques. Emerging technology that understands and analyzes contextual data contained in texts can be beneficial to insurance practices.
Claims processing is a core activity within the insurance sector that is at the centre of many pain points.
Insurance agents can use NLP during phone calls, for instance, to recognise a client’s speech and automatically fill out a claims form. Overall, NLP technology analyses both speech and text faster than humans can. Employees then simply require to manually verify the results.
