Future prospects on E-Commerce Product Experience based on Natural Language Processing and Machine Learning algorithms
Ambika Talawar
, Akshatha M
E-Commerce, Sentiment Analysis, Natural Language Processing, Product Experience
In the era of competition among the E-commerce brands, the customer feedback and product experience plays a vital role. An emotion intensity scanner is a natural language processing (NLP) tool used to assess the level of emotion or level of feeling within an item of text. The sentiment can be favorable, adverse, neutral, or it may be mixed. The analyzer provides an integer number or rating to the feelings, reflecting its intensity. A favorable sentiment, for instance, might receive an increased positive score, while an adverse feeling may have a higher negative rating. Such analyzers can be employed for a variety of purposes, including social media monitoring, market research, client feedback evaluation, and general opinion analytics. The intensity scores can be displayed in any number of methods, contingent upon the method of execution or methodology. E-commerce experience with a product relates to the complete customer experience or satisfaction when engaging with goods or services on a digital retail marketplace. It encompasses numerous aspects of the consumer background, spanning the moment a customer first comes across an item to their final choice of purchase and post-purchase acquaintances. A positive customer experience is a vital part of any profitable online shopping operation. It encompasses each phase of the consumer's experience; at the moment they find a product to the last post-purchase interactions. In addition, customized recommendations and incentive schemes adapt to a person's preferences, promoting relationships that endure. By continually enhancing and honing the product experience, e-commerce companies may make an eternal mark on the consumers they serve, building confidence and receiving an edge over their competitors in the constantly changing online marketplace. A favorable e-commerce product experience can lead to increased consumer satisfaction, sales, and brand loyalty. E-commerce enterprises should regularly monitor and evaluate customer comments, user behavior, and sales data to find areas for improvement and improve the overall product experience. Businesses may stand out in the competitive online market by providing a flawless and pleasurable e-commerce product experience. We have developed a Sentiment analysis we application using flask using VADER (Valence Aware Dictionary and sEntiment Reasoner) sentiment Intensity analyzer to, where both customer and buyer can get the benefits of the business needs. This program also displays the mood of each prior customer's remarks or feedback when they purchase a new product. The program has been tested on several E-Commerce platforms' real-time platforms. The score table provides the sentiment such as Positive, Negative, Neutral and Compound.
"Future prospects on E-Commerce Product Experience based on Natural Language Processing and Machine Learning algorithms", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 8, page no.229 - 235, August-2023, Available :https://ijsdr.org/papers/IJSDR2308033.pdf
Volume 8
Issue 8,
August-2023
Pages : 229 - 235
Paper Reg. ID: IJSDR_208108
Published Paper Id: IJSDR2308033
Downloads: 000347148
Research Area: Computer Science & Technology
Country: Mysore, karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
