Data Mining Approach for Target Marketing SMEs in Nigeria

Presently, in addition to the lack of funds experienced by SMEs in Nigeria, the main challenges experienced by SMEs (Small and Medium Enterprises) in Nigeria has to do with them not being able to understand and the apply marketing concept. Also there are a lot of resources being wasted inmarketing campaign which does not target anybody in particular. This study is therefore focused on finding the target market of SMEs using the K-means clustering technique in combination with sentiment analysis, also known as opinion mining. The study also aims at recommending the best medium to market these SMEs as discovered from the output of the analysis. The result of this research will give positive direction to improving the profit of small and medium business through target marketing. Also, this study is not trivial because it will help to reduce marketing cost through target marketing. The study also helps to discover the opinion of the populace on the small andmedium business and the medium through which they can be targeted. This discovery will definitely form solid foundation for further marketing action and improve their profit.Keywords: Data Mining, K-means Clustering, Target Marketing, Sentiment Analysis, SME, Opinion Mining

A Systematic Review of Consumer Behaviour Prediction Studies

Due to the importance of Customer behaviour prediction, it is necessary to have a systematic review of previous studies on this subject. To this effect, this paper therefore provides a systematic review of Customer behaviours prediction studies with a focus on components of customer relationship management, methods and datasets. In order to provide a comprehensive literature review and a classification scheme for articles on this subject 74 customer behaviour prediction papers in over 25 journals and several conference proceedings were considered between the periods of 1999-2014. Two hundred and thirty articles were identified and reviewed for their direct relevance to predicting customer behaviour out of which 74 were subsequently selected, reviewed and classified appropriately. The findings show that the literature on predicting customer behaviour is ongoing and is of most importance to organisation. It was observed that most studies investigated customer retention prediction and organizational dataset were mostly used for the prediction as compared to other form of dataset. Also, comparing the statistical method to data mining in predicting customer behaviour, it was discovered through this review that data mining is mostly used for prediction. On the other hand, Artificial Neural Network is the most commonly used data mining method for predicting customer behaviour. The review was able to identify the limitations of the current research on the subject matter and identify future research opportunities in customer behaviour prediction.Keywords: Consumer Behaviour, Prediction, Statistics, Data Mining, Dataset, Customer Relationship Management, Literature Revie

Measuring the Impact of the Coronavirus Disease 2019 Pandemic on Mobility Aspirations and Behaviours

The coronavirus disease 2019 (COVID-19) pandemic prompted tens of thousands of people worldwide to migrate from cities in its early stages, leading to an increased spread of the virus. Understanding the factors driving relocation during a pandemic is crucial for effective outbreak control. We investigated how the pandemic influenced people’s aspirations and preparations to move, both domestically and internationally, surveying individuals in Greece, India, Italy, Kenya, Nigeria, Portugal, Serbia, Spain, and the United States of America. Out of 4448 eligible responses, 765 participants (17.2%) had a strong aspiration to move due to COVID-19, and 155 (3.5%) had already prepared. Those considering relocation were statistically significantly more likely to perceive moving to an area with fewer COVID-19 cases as protective against the virus (OR = 1.3, p p p < 0.01). Social alienation, social imitation, and the perceived efficacy of mobility increased aspirations to move due to COVID-19. This study emphasizes the rapid population movements at pandemic onset and their potential contribution to disease transmission, urging future pandemic planning to take account of such mobility dynamics