Abstract
This chapter aims to present the process of selecting and analyzing a number of reviews using a software solution (an online application) created specifically for text analysis and extracting user sentiment. This software measures the level of user satisfaction, analyzing product reviews and taking into account the qualitative part of the content generated by users. Analyzing online customer reviews with the help of specialized software can help both companies and other users. The software can also help us reach a conclusion regarding the analysis of reviews and customer feedback on products or services. This study can also be useful for customers or buyers who want to know the opinion of others about a product, having the opportunity to differentiate between positive and negative reviews.
TopIntroduction
Analyzing online customer reviews with the help of specialized software can help both companies and other users. The software can also help us reach a conclusion regarding the analysis of reviews and customer feedback on products or services.
The biggest benefits of this study are aimed at organizations, which can adapt their products, services or promotion according to the wishes of their customers, as well as the level of customer satisfaction, because they can find out their customers’ opinions of what they offer with the help of online customer reviews analysis. A software solution for the analysis of online customer reviews can provide reports very quickly after extracting information from reviews, forums or interviews. This study can also be useful for customers who want to know the opinion of others on a product, having the opportunity to differentiate between positive and negative reviews. Given that customer behaviors and reactions to product design and marketing are essential for manufacturers (Wang, Lu & Tan, 2018), such a program can help the research about how product qualities can affect consumer satisfaction (Wang et al., 2018).
The main objectives of this chapter are suggested by the online reviews, putting the focus on the importance of the reviews in the user purchase decision, which are the most important elements of a review and what users take into account when writing a review. Also, in the study provided, the interest is to reveal if there are differences between the online shops (e.g. Amazon and Walmart), in terms of reviews and the attitude towards the stores.
This paper will present the process of selecting and analyzing a number of reviews, using a software solution (an online application) created specifically for text analysis and extracting users' sentiments. This software measures the level of user satisfaction, analyzing product reviews and taking into account the qualitative part of the content generated by users. The broader concept of “User Generated Content” has the ability to identify as many customer needs as possible, unlike the use of direct interviews, being a faster research solution, with lower costs (Timoshenko & Hauser, 2018). Therefore, this type of content has spread a lot due to this great advantage, whether we are talking about online reviews, social media or blogs (Timoshenko & Hauser, 2018), and they must be carefully analyzed because they can play an important role in the purchase decision.
Under these specific conditions, companies are taking into account more and more user reviews, and a growing number of them choose customer satisfaction as the main performance indicator (Mihelis, Grigoroudis, Siskos, Politis & Malandrakis, 2001).
Story.ly is the name of the software/ application we will use in this paper and this is a solution from the German company SmartMunk, which aggregates qualitative ideas and reduces the complexity of rich data sets by automatically extracting meaning from text - in almost any language (Boje, 2018). SmartMunk GmbH was created in 2012 by Andera Gadeib and Volker Gadeib, starting from the idea of offering online software to improve customer relations, and the startup business specialized in the development of smart software as a Service solution for co-creation and text analysis (SmartMunk, 2020). The tools they provide want to show companies, first and foremost, what is in the customers’ minds: “We call this 'Voice-of-the-Customer Intelligence'” (SmartMunk, 2020).
SmartMunk's story.ly program supports marketing, sales and new product development in companies (SmartMunk, 2020), promising a very enjoyable experience due to the fact that any amount of text will be semantically condensed and displayed in concise visual analysis and allows the users to easily read the “story” at a glance (smartmunk.com). In addition to the software being easy to use and the intuitive nature of the interface, the program is compatible with any platform and is available in any language around the world.
Therefore, this chapter aims to track the behavior of buyers towards companies in the online environment, given the communication between the two elements, promotion techniques and reviews, trying to reach a conclusion regarding their importance and influence on the purchase decision.
Key Terms in this Chapter
Qualitative: A research method that considering the reviews from the point of view of relevance, clarity and transparency of the user text, numbers are not taken into account, for example the stars achieved by the product or number of reviews.
Story.ly: High performance program which has the capacity to extract the sentiment from text and can show us important elements for the customers.
Corporate: Messages sent by company with a clear purpose to important audiences: employees, mass-media, stakeholders.
Purchasing Decision: The decision taken by a client to buy something, after he read the reviews, studied the product and, in the end, decide to buy it.
Quantitative measure: Measuring the number of reviews, stars, likes and dislikes, positive and negative experiences for positioning a product or a service.
Software: Basic application which set in motion the program through we can analyze reviews, having a powerful database.
Online Store: Online site that sells products or services, customers having the opportunity to receive everything at home, or it can be tested offline before.
Word-of-Mouth: Information transmitted from one person to another, it has the power to spread some details that can reach to thousands of people and even influencing them.
Web 2.0: The Internet after the year 2000, much more developed and available to anyone due to technological and economic advancement.