Influence of marketing mix strategies on performance of microfinance institutions in Nairobi County

Abstract

Microfinance institutions (MFIs) play a key role in Kenyan economy by providing financial support to the middle working class and the low-class individuals. Some of the notable MFI`s include Platinum Credit, Mwananchi Credit, Momentum Credit, My Credit, among others. With the many hidden costs such as loan penalties, tracking, insurance costs, repossessions by auctioneers of the charged securities, Covid-19 pandemic, MFIs still manage to offer stiff competition to the mainstream banks and other financial service providers. With the many hidden costs such as loan penalties, tracking, insurance costs, repossessions by auctioneers of the charged securities, Covid-19 pandemic, MFIs still manage to offer stiff competition to the mainstream banks and other financial service provides. The necessity to investigate the marketing mix factors employed by MFIs to obtain and maintain a competitive advantage edge in the highly competitive market was prompted by these evident inconsistencies. This study examined the influence of marketing mix Strategies (4Ps) on the performance of MFIs operating within Nairobi County. The objectives of the study included examining the influence of product, promotional, price and place on performance of MFIs in Nairobi. The study analyzed several theories and how they are connected to the study variables. These theories were the marketing mix theory, Hierarchy of effects Theory, AIDA Model and Resource-Based Theory (RBT). The study utilized a descriptive research design with the study population consisting of the 49 MFIs located in Nairobi and 98 respondents selected from all the selected Microfinance institutions. The primary data collection instrument was questionnaires, which was tested for validity and reliability using a sample pilot study. During the pilot, five Microfinance institutions were involved. The Data collected was analyzed using SPSS and subsequently presented in the form of graphs and tables. The study established that all the variables had positive relationships with the performance of MFI institutions. Predictors: (Constant), Promotion, location, product, and price, and r values of.741, .735, 608, and.595 respectively. Regression analysis revealed that the regression model was reliable because it was statistically significant based on the outcomes of the ANOVA (table 4.10). The unbiased study revealed that the study variables accounted for 63.3% of the factors affecting the performance of MFIs. The linear regression model revealed that unit changes in product, promotion, price, and place impacted MFI performance. According to the findings, MFI should increase budgetary allocation for promotion, product differentiation, alternative pricing strategies, eliminating hidden costs, and maintaining their current location while using customer requirements to guide changes in their distribution channels, ensuring customer retention and growth through acquisition of new customers.