FORECASTING CONSUMER DEMAND AND ANALYZING THE IMPACT OF SOCIAL MEDIA INFLUENCER MARKETING ON BRAND EQUITY USING ARIMA AND SEM MODELS

Organizations are increasingly using analysis to understand consumer buying habits in order to

understand what type of promotional strategies work best for their products. This is due to the

fact that digital platforms have a greater influence on a consumer's purchasing decisions. A

complete quantitative approach is designed to understand the impact of social media influencer

marketing on brand equity and to forecast the demand for a product. Using historical sales data

to forecast future consumer behaviour, the two statistical models, namely, ARIMA and SEM,

were used to study the effect of promotion through influencers on consumer perceptions,

purchase intent, consumer engagement, and brand equity. For the empirical analysis, the study

relied on data from 1,248 responses to an online survey and total monthly retail and e-commerce

sales data, combined with the ARIMA model, which used historical purchasing patterns,

seasonality, and social media influencer engagement metrics to build forecasts of future

consumer demand patterns. The ARIMA model produced a MAPE of 4.82%, RMSE of 3.41,

forecast accuracy of 95.18%, and a correlation coefficient of 0.93, which shows that the

forecasting model is very reliable in predicting future demand. The results show that the

credibility of the influencer has a significant effect on the engagement of consumers (β = 0.81)

and their trust (β = 0.72), which in turn has a significant effect on consumers' intention to

purchase (β = 0.76) and brand equity. The theoretical model is found to be an acceptable model

with fitness indexes such as CFI = 0.95, RMSEA = 0.041, GFI = 0.93, and Chi-square/df = 2.11.

The results have shown that marketers' use of influencer marketing is crucial for the creation of brand equity and the predictability of demand. The integrated forecasting model can serve as a

practical application for organizations seeking to create effective marketing strategies, leverage

a customer-centric decision-making process, and ultimately, have a precise forecast of future

demand in the current competitive digital landscape.