Social Media Analytics and Market Performance of Commercial Banks in Nairobi City County, Kenya
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Date
2025-11
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Kenyatta University
Abstract
The ability of a firm to generate business insight from social media data and to exploit it to improve business processes and decision-making is vital for market performance. However, it is a challenge for many commercial businesses in Kenya to analyze and use this data appropriately for instance, big data. The social media has become more innovative and interactive compared to the conventional print or audio/video media. However, due to unstructured and dispersed nature of this data, it is difficult to extract information that is meaningful and applicable. The firms’ inability to utilize the social media analytics in generation of business insights has limited their efforts to take advantage of this new marketing channel to make sound business decisions. The aim of this study was to establish the influence of social media analytics on the market performance of commercial banks in Nairobi City County. The specific objective of this research is to assess the influence of news analytics, opinion mining, sentiment analysis, and social media scraping on the market performance of commercial banks in Nairobi City County; while ascertaining the moderating effect of organizational capabilities on the relationship between social media analytics and the market performance of commercial banks in Nairobi County. The study is founded upon four major theories: resource-based view, dynamic capability theory, holistic theory and systems theory. The study adopted a stratified random sampling technique used to choose respondents, with structured questionnaires being used to collect data. The data collection tool was pre-tested for validity and reliability analysis was conducted. The target population for the study was 39 licensed commercial banks in Nairobi City County from which a sample of 156 respondents from these banks was sought. Descriptive and inferential statistics utilized to analyse the research data. The analysis techniques comprised means, standard deviation, regression statistics, and beta-coefficients. Multiple regression analysis was employed in this study to determine the influence of the four independent variables on the dependent variable. The study found that social media analytic, opinion mining, sentiment analytic and social media scrapping have positive statistically significant impact on the market performance of commercial banks in Nairobi City County, Kenya. Further, the study revealed a moderating effect of organization capability on the relationship between social media analytics and the market performance of commercial banks. The study concludes that news analytic enable invaluable insights into market performance. Opinion mining helps in keeping trends and events that act as warning signs for supply-chain risks. Sentiment analysis helps in gathering data and feedback on problems with products and services. Social media scraping allows banks to gather valuable insights into current market trends and organizational capabilities pinpoints a bank’s strengths and weaknesses. Further, the study further concludes that applying social media analytics in an environment of organization capability improves the positive impact on the market performance of commercial bank. The study recommends that banks should establish high social media performance standards, and their employees should strive to meet or exceed them. Further, stakeholders in the banking sector should improve their participation by offering feedback in social media to be able to inform decision making.
Description
A Thesis Submitted to the School of Business, Economics and Tourism in Partial Fulfilment of the Requirement for the Award of the Degree of Master of Science in Marketing of Kenyatta University, November, 2025
Supervisor;
1.Reuben Njuguna
2.John Mutinda