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client satisfaction


This Is How NLP Can Help Managers Better Understand Client Satisfaction

#artificialintelligence

When managers make strategic decisions, an important question that needs to be addressed is why and how their clients are satisfied. The corresponding answers need to be included in decision-making processes to increase user satisfaction. Clients' written comments can be a useful source to achieve this objective. However, this strategy is too broad to incorporate all the factors influencing clients' opinions. Artificial Intelligence (AI) has proven to be one of the most efficient resources to extract key results from vast amounts of data.


Paralegals v. Artificial Intelligence - Friend or Foe? - The Legal Assistant

#artificialintelligence

As technology progresses, so does our fear of being replaced by artificial intelligence (A.I.). A.I. has already made its presence known in the legal field igniting worry about our job security. The topic of Attorneys and paralegals v. Artificial Intelligence is hitting the headlines with ever-increasing presence. Even with the new wave of A.I. pouring into the legal industry, it does not necessarily mean that paralegals will ever become obsolete. While A.I. is by some, portrayed as an enemy, it also brings something of value to the legal field.


10 Real-World Examples of Machine Learning and AI [2017]

#artificialintelligence

Machine learning helps financial services firms track customer happiness. By analysing user activity, smart machines can spot a potential account closure before it occurs. They can also track spending patterns and customer behaviour to offer tailored financial advice. Another application of machine learning is market analysis. Smart machines can be trained to track trading volatility or manage wealth and assets on behalf of an investor.


10 Real-World Examples of Machine Learning and AI [2017]

#artificialintelligence

Machine learning helps financial services firms track customer happiness. By analysing user activity, smart machines can spot a potential account closure before it occurs. They can also track spending patterns and customer behaviour to offer tailored financial advice. Another application of machine learning is market analysis. Smart machines can be trained to track trading volatility or manage wealth and assets on behalf of an investor.


10 Real-World Examples of Machine Learning and AI [2017]

#artificialintelligence

Machine learning helps financial services firms track customer happiness. By analysing user activity, smart machines can spot a potential account closure before it occurs. They can also track spending patterns and customer behaviour to offer tailored financial advice. Another application of machine learning is market analysis. Smart machines can be trained to track trading volatility or manage wealth and assets on behalf of an investor.


10 Real-World Examples of Machine Learning and AI [2017]

#artificialintelligence

Machine learning helps financial services firms track customer happiness. By analysing user activity, smart machines can spot a potential account closure before it occurs. They can also track spending patterns and customer behaviour to offer tailored financial advice. Another application of machine learning is market analysis. Smart machines can be trained to track trading volatility or manage wealth and assets on behalf of an investor.