In today’s fiercely competitive world, businesses must dig deeper and develop a greater understanding of customer preferences and market trends by applying innovative options like artificial intelligence and machine learning.
(EN) As natural language processing technology continues to evolve into a robust, user-oriented tool, businesses find that NLP can guide their marketing and overall business strategies toward successful outcomes.
NLP improves business intelligence in numerous ways but text analysis is its primary benefit. Raw textual data is often unstructured and is therefore unused by the very businesses that collect it. Until recently, it was nearly impossible to analyze unstructured textual data at scale. Today, NLP can make sense of raw data by detecting patterns across scattered text and then structuring patterns in a way that makes the data analytically viable.
NLP in Healthcare
The success of the healthcare industry depends on accurate diagnosis, objective decision-making, the application of new and evolving knowledge and the use of predictive models to guide support services and medical personnel. When integrated with health IT systems, data mining helps to reduce subjectivity and improve diagnosis and treatment while improving predictive models. Once set in motion, data integrated healthcare IT systems are capable of improving responses to medical emergencies on both the individual and global scale.
Data integrated healthcare systems assisted a Canadian health monitoring platform in recognizing the magnitude of the COVID-19 crisis weeks before national and international agencies informed the public. Using an AI-driven algorithm, the platform mined textual data using NLP. The technology was designed to scour foreign journals and newspapers, plant and animal disease networks and government statements.
On December 31, 2019 the Canadian platform BlueDot notified its users of an emerging threat in Wuhan. Almost ten days later, on January 9th the World Health Organization officially notified the world of the flu-like outbreak and the cluster of pneumonia cases present in Wuhan. The US Centers for Disease Control and Prevention released its concerns on January 6. Users of the NLP-powered platform were provided with an early warning that allowed them to avoid danger zones like Wuhan.
NLP for hiring and recruitment
Human resource offices are more efficient when they employ NLP processes in their software development to sift through databases and resumes. Hiring teams define the terms and scope of semantic analysis and NLP software searches relevant synonyms and requirements. This frees up staff time and turns up relevant resumes and suitable candidates in a non-biased fashion. On the recruitment side, NLP-based software helps recruitment teams craft gender-neutral and bias-proof job descriptions which can further diversify the candidate pool. As COVID-19 has forced teams worldwide to work from home, AI-enhanced CRMs and smart time trackers help supervisors manage productivity.
NLP for advertising
Advertisers seek new ways to analyze the massive digital footprints customers and potential customers leave behind on social media, emails, text messaging, engine searches and daily browsing behavior. NLP software is an insightful tool that matches simple keywords across a broad range of channels, honing in on ad placement optimization. Using NLP, advertising departments can spend their budgets efficiently, target relevant leads and build a high ROI. NLP’s ability to sense ambiguity and context within textual messaging and word-usage is constantly improving and bringing added value to advertising strategists.
NLP for market intelligence
Advertisers may focus on individual behaviors but they also require robust data analysis that assists in a greater understanding of overall market changes and developments. However, monitoring a vast amount of textual data in the form of blogs, websites and social media posts can be overwhelming. NLP-based software uses a powerful algorithm that is capable of scouring social media content, customer reviews and comments. The raw data is converted into meaningful insights regarding changes in market and overall customer attitudes.
One of the promising areas of NLP is its application for data mining and sentiment analysis for demand forecasting for the retail industry.
With a large enough sample size of customer feedback, we can use NLP modeling to notice changes in customer purchasing decision-making and identify goods quickly being bought out of stock.
Conversational AI is one of the rising trends now. Voice-enabled devices, such as the Amazon Echo and Google Home, are common in homes. There were 3.25 billion voice assistant devices around the world in 2019. Natural language processing is an essential element of these devices. Voice-enabled AI is powered by a computer’s ability to understand voice-to-text transcriptions. A greater capacity for textual understanding leads to greater accuracy in the response to voice-enabled commands. Alexa skills development is a growing tech trend that reveals various business use cases from personal applications to enterprise smart mirror solutions.
Customer Service and Support
Customer service automation is most recognizable in the form of chatbots that have been successfully used by e-commerce sites for several years. NLP-powered chatbots free up human customer service agents for more complex tasks while automated chatbots answer routine customer questions. Over the years, e-commerce and other websites have seen a rise in conversions due to the ease with which customers receive answers to basic questions. NLP-driven algorithms also direct customers to other resources which further assists in lead generation and capture.
As seen in the examples above, NLP can enhance customer service, accelerate product time to market and increase revenues. Whether your business is seeking improved hiring and recruiting processes, deeper customer risk-assessment and behavior predictions, improved market intelligence or optimized advertising campaign, NLP is designed to help your business achieve its goals.
Fuente: Serhii Maksymenko