How a Business can use Automated Systems to Process Written Human Language in Order to Enhance Customer Services Online
Nurmi, Tommy Nam (2020)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2020060416824
https://urn.fi/URN:NBN:fi:amk-2020060416824
Tiivistelmä
This thesis focuses on the use of Natural Language Processing (NLP) and how it can be used to leverage competitive advantage. The main concern of NLP is how business are able to effectively process data through clear cut frameworks, use this pipe-line process in order to solve business problems involving customer services, and assist in the enhancement of customer oriented business strategies.
This topic is relevant because NLP and big data is recognized by business giants such as Amazon, Microsoft, and Google, as a critical tool to enable clear insights into Natural Language Understanding (NLU) which assists in the decision making process. By understanding customer expectations and sentiments through data, businesses are able to differentiate themselves from the competition, building a unique selling point (USP) through the cumulative efforts of utilizing NLP models to garner insights and sentiments from unstructured data.
The effective use of NLP tools and techniques by businesses requires the formation of clear objectives and metrics where quality data will be processed, and a suitable model will be deployed and evaluated. This requires an effective framework, which will determine the success of a quality NLP project in the scope of business. Qualitative research methods are utilized in this evaluation using secondary resources.
NLP is a function that helps businesses gain competitive advantage. This thesis examines the framework, limitations, and feasibility of NLP. This is significant because businesses can use the frameworks and evaluative arguments provided to support decision making, as well as clarify the different ways NLP can be leveraged. A form of text clustering in the field of NLP referred to as sentiment analysis and topic modelling will be explained and examined through case studies. It was determined through the various case studies of Utopia Analytics, Dex, and Finnish government that the integration of systems which utilize NLP enables business to differentiate from the competition and create value for society. How effectively NLP can be utilized to enhance business functions will depend on quality data preparation, deployment of correct NLP models, and evaluation of the whole process under an approachable business framework.
This topic is relevant because NLP and big data is recognized by business giants such as Amazon, Microsoft, and Google, as a critical tool to enable clear insights into Natural Language Understanding (NLU) which assists in the decision making process. By understanding customer expectations and sentiments through data, businesses are able to differentiate themselves from the competition, building a unique selling point (USP) through the cumulative efforts of utilizing NLP models to garner insights and sentiments from unstructured data.
The effective use of NLP tools and techniques by businesses requires the formation of clear objectives and metrics where quality data will be processed, and a suitable model will be deployed and evaluated. This requires an effective framework, which will determine the success of a quality NLP project in the scope of business. Qualitative research methods are utilized in this evaluation using secondary resources.
NLP is a function that helps businesses gain competitive advantage. This thesis examines the framework, limitations, and feasibility of NLP. This is significant because businesses can use the frameworks and evaluative arguments provided to support decision making, as well as clarify the different ways NLP can be leveraged. A form of text clustering in the field of NLP referred to as sentiment analysis and topic modelling will be explained and examined through case studies. It was determined through the various case studies of Utopia Analytics, Dex, and Finnish government that the integration of systems which utilize NLP enables business to differentiate from the competition and create value for society. How effectively NLP can be utilized to enhance business functions will depend on quality data preparation, deployment of correct NLP models, and evaluation of the whole process under an approachable business framework.