The Degree of Adoption of Business Intelligence in Romanian Companies—The Case of Sentiment Analysis as a Marketing Analytical Tool

Abstract

The structural changes in the public communication space through the advent of the Internet and the further development of online commerce culminate today with the explosion of blockchain techniques and social networks. This communication space was quickly taken over by marketing tools, as demonstrated by the many marketing campaigns dedicated to these new communication channels. The development of online commerce and the emergence of social networks have allowed consumers to efficiently search for brands/products/services, compare them, express their point of view on them, and even give them grades. Due to the explosion of relevant data online, the changing business environment needs attention to interpret and extract relevant information. The application of sentiment analysis to public reaction in the online environment provides the researcher with how the authors of the analyzed texts (clients/beneficiaries) express themselves regarding the studied reference (product/service/organization/social theme and a feature of them). Along with the other metrics present in marketing, including digital marketing, the reports in the analysis panels of google analytics and social networks, sentiment analysis instantly provides the general and competitive context in which the product/service/theme evolves. In this article, two types of research have been conducted to highlight the benefits felt, but also the degree of knowledge, implementation, and use of sentiment analysis in online marketing analysis. One of the types of research was qualitative, carried out on 10 participants (specialists in the field of marketing), with the help of an interview guide. Qualitative research aims to find out the level of knowledge of sentiment analysis and the general degree of digitalization of Romanian companies, an indicator considered critical in the new post-pandemic business environment. The second research was quantitative and used to develop analysis by structural equations. For this, a questionnaire applied to a sample of 108 respondents was used. Through the analysis by structural equations, a conceptual model was developed that presents the main factors that are related to others and that contribute to the satisfaction of the users of the analysis of feelings for obtaining marketing data.

Utilising Artificial Intelligence to Turn Reviews into Business Enhancements through Sentiment Analysis

“…Sentiment analysis refers to the process of extracting customer sentiments from textual data. Through the analysis of product reviews, comments, and interactions on social media platforms, companies are able to obtain valuable insights into the emotional responses of customers, all while upholding their privacy [48][49][50].…”

“…The use of prompt interventions has the potential to transform unfavourable attitudes into favourable experiences. Also, sentiment analysis can be used to identify areas in need of improvement in customer service, which can then be used to improve the customer experience [48].…”

“…Conversely, bad reviews provide valuable insights that may be used to identify areas for development. Also, sentiment analysis can be used to personalise the shopping experience for customers, which can lead to increased sales and customer satisfaction [48].…”

Sentiment Analysis using Latent Dirichlet Allocation for Aspect Term Extraction

“…Sentiment Analysis, also known as Opinion Mining, is a rapidly growing research area that aims to extract and analyze the opinions, attitudes, and emotions expressed in unstructured text data, such as consumer reviews, social media posts, and online forums [1], [2], [3]. Sentiment Analysis has become an important tool for businesses to better understand consumer perceptions of their products and services and make informed decisions about product design, analysis, and market share [4], [5], [6]. One of the most popular techniques used in Sentiment Analysis is Latent Dirichlet Allocation (LDA) [7], [8], [9].…”

Assessing Digital Transformation Acceptance in Public Organizations’ Marketing

“…Nevertheless, public organization managers in Romania are aware of the need to implement digital marketing. Public digital marketing drives an increase in the level of involvement of citizens in the activities of the public organization by participating in community decisions [11].…”