
ADOPTION OF PREDICTIVE ANALYTICS FOR MARKETING DECISION MAKING: IMPLICATIONS FOR SMALL BUSINESS GROWTH
Author:
Okwudiri Nnanna-Ohuonu, Duru Chidinma Martha, Emeka Innocent Chibuzor, Akunyi Adachukwu Angel
This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
This study examined the adoption of predictive analytics for marketing decision making and its implications for business growth. Specifically, the study examined the nexus between adoption of sales trend forecasting and customer retention in SMEs. Survey descriptive research design was used in the study. The population of the study consist of 1,902 registered SMEs in Awka South Local Government Area, Anambra State, with sample size of 330 respondents obtained using Taro Yamane (1967) formula. Data (Primary) were collected using structured questionnaire. Mean and frequency distribution were used to conduct descriptive analysis on the data. Hypothesis was tested using multiple regression analysis, at a 5% level of significance. The result indicted that a very high positive correlation exists between the variables analyzed, with an R coefficient of 0.8849, while the R² value of 0.7831 means that about 78.31% of the variation in the dependent variable is explained by the model. The study, therefore, concluded that Sales Trend Forecasting significantly and positively influence overall Business Growth of SMEs through customer retention. Sequel to this, among others, it was recommended that small business should learn to leverage data analytics, and by extension, sales trend forecasting, so as to be able to predict customer behavior and track it, in order to follow-up and ensure repeat purchase, and build loyalty among customers.
| Pages | 66-70 |
| Year | 2025 |
| Issue | 1 |
| Volume | 4 |
