Evaluating A Customer Reviews Of Products Sold Online

Amazon.com operates in the Online Retail Industry. The sector is one of the fastest growing globally and is outperforming the ordinary retail marketplace. It was created after 1995 and it was only the Internet that made it possible for such an industry not only to be established but to become one of the most flourishing sectors in the business environment. What is interesting is that Amazon.com, together with eBay is the pioneer in the field. Both companies were launched in 1995 and are still extremely successful. The creation of e-mail in 1996 had a huge impact on the development of online retail by introducing a fast and easy way to communicate with customers. For this two-year period Internet usage

As evidence for the basis of judgments and decisions, evaluated in my own reports and records, I need to show that I accurately and clearly record the judgements and decisions and evidence on which the judgements have been based and where judgement is based on informed opinion. I do record other evidence and reports which support my judgements and decisions and conflict with my judgements and decisions. It is as well very important to clarify events and decisions.

This section discuss about the common traits or ideas observed in the three research topics. Although, each of the three articles discuss a unique idea, all of them are aimed at utilizing the web data to produce better results. Web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilization of the valuable user generated data from the social media or the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by an individual. All the three articles propose an idea to solution the problem stated, compared their results to the existing models and showed significant improvement.

In the paper Nguyen et al \cite{Micro:Ng}, the model makes use of the Micro-reviews\cite{Micro:Ng} generated by the users through various social media sites about any particular entity. Micro-Reviews \cite{Micro:Ng} are the reviews that are not too long , easy to comprehend and also considered as the most appropriate feedback of the customer. But it is starting to get complicated as the number of Micro-Reviews \cite{Micro:Ng} are increasing and is hard to go through several thousands of the user reviews to find the best review suitable to the user preferences. In order to overcome this, these reviews are categorised in to either positive or negative feedbacks. Then this Micro-Reviews \cite{Micro:Ng} are associated and

Using the customer feedback in advertising is a great marketing strategy and with today’s technology it is inexpensive and easy to gather this information. Consumers trust the opinions of their neighbor much more than the opinion of a large sometimes faceless company. By using this strategy they have developed a neighborhood type environment bring pet lovers together.

"In a study based on theory, the framework is usually referred to as theoretical framework" (Fain, 2017, p. 103). The theoretical framework was presented clearly in the objective statement of the article, “To identify factors that influence adherence to guidelines for prevention

"A satisfied customer will tell five people about their experience, a dissatisified customer will tell twenty-five!"

When personally evaluating the credibility from digital media advertising, the context of what the advertisement is trying to portray and the message that it is trying to achieve are important. Meaning, every advertisement has an objective that is presented in a certain matter; therefore, understanding both is how I evaluate the credibility. For instance, when it comes to dietary supplements, advertisements that showcase celebrities for promotion of the product loses creditability. Individuals identify paid promotion with dietary supplements constant; therefore, the products endorse by celebrities have less creditability. On the other hand, when Jared Fogle, the spokesman of Subway, shared how eating healthier Subway sandwich is the reason for his weight lost- individuals were more prone to purchase Subway’s sandwiches. Inference, credibility is measured depending on the contexts of the digital advertisement, and the objective for the product.

It became an issue for consumer, and they felt uncomfortable due to companies invaded consumers privacy without their consent. Another issue regarding data mining is there no clear policies around how the company uses data once they have collected the information. After Target received negative publicity regarding its original data mining approach, they change their strategy by mixing all their ads, so it not that obvious that they were spying on them. It makes customers’ to assume that everyone else gets same coupons and ads. Data mining has given Target awareness into the relationship between product sales and online reviews. Target retailers identify guests how write reviews, examining their history of purchasing and invited to write review on their products. This program was highly successful, leading Target to obtain incremental reviews and increase sales of those key products. More importantly, data mining has empowered companies to find new opportunities for growth, make better decisions to succeed business goals and safe money. The retailer industry utilizes data mining and customer analytics to support customer decisions. Exploring how collected data can be manipulated to identify customers buying patterns and increase profitability is a growing business

Online purchasing is becoming more and more practical thing for contemporary customer. It is explained by high internet penetration in every country, lower cost than in retail network, door to door delivery. Internet plays an important role nowadays; therefore it creates a new market, which sometimes is quite difficult to measure. Online shopping is different from the B&M shopping due to the fact that there is no physical presence of goods, from other standpoint internet is able to sell way more services and motivation and decision making process directly connected to the feedbacks.

First of all, with the help of SAP ERP system and associated business intelligence applications, the employees could serve the customers instant personalized as they use the firm’s database to profile customers. For instance, as the article said, the site’s software can analyze order patterns, reminding and suggesting customers of their favorite products. They add a YMAL cross-selling tool and develop a customer relationship management system that tracks each customers’ past purchases which recommends products that other customers purchased. Moreover, the database recognizes whether a visiting customer is a new, infrequent, or loyal customer which could serve them appropriate information.

Opinion mining (or Sentiment Analysis) is the practice of extracting simple human sentiments like positive or negative, objectivity or subjectivity from the text written in natural language [3]. The way we perceive things or express feelings are different from other and that’s why opinion mining is most intriguing research area in today’s times. Opinion mining has developed into the most active research area in data mining. Due to its wide range of influence, it has spread across the areas of marketing and social science and not just been confined to computer science.

It is very important the company focuses on the product features such as fuel efficiency, improve mechanical, and tires. Improving product features will help the company grow and produce quality products.

At first “X” company has to conduct a SWOT analysis, which provides data for an organization to create strategic plans, appropriating resources and developing tools or actions to bring about continued success to analyze the organization. Once the SWOT analysis has been completed, the organization is able to create the mission and vision statements. In addition to what was said before, customer satisfaction should be one of if not the main objectives. To understand the level of customers’ satisfaction, and desires “X” should implement surveys called “customer satisfaction survey.” These surveys will be sent to new and old customers during certain times a year. E-mail surveys also have to be provided for all customers. The surveys will

In this paper we different techniques which is used for domain analysis, feature recommendation. This approach mines descriptions of product from publicly available online product Descriptions, used a text mining and a novel incremental diffusive clustering algorithm to discover features in specific domain , use association rule mining to know latent relationships between features within products of same domain and used KNN algorithm for generates a probabilistic feature model that represents commonalities, variant.