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Abstract
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Online marketing refers to the practices of promoting a company’s brand to its potential customers. It helps the companies to find
new venues and trade worldwide. Numerous online media such as Facebook, YouTube, Twitter, and Instagram are available for
marketing to promote and sell a company’s product. However, in this study, we use Instagram as a marketing medium to see its
impact on sales. To carry out the computational process, the approach of linear regression modeling is adopted. Certain statistical
tests are implemented to check the significance of Instagram as a marketing tool. Furthermore, a new statistical model, namely a
new generalized inverse Weibull distribution, is introduced. ,is model is obtained using the inverse Weibull model with the new
generalized family approach. Certain mathematical properties of the new generalized inverse Weibull model such as moments,
order statistics, and incomplete moments are derived. A complete mathematical treatment of the heavy-tailed characteristics of
the new generalized inverse Weibull distribution is also provided. Different estimation methods are discussed to obtain the
estimators of the new model. Finally, the applicability of the new generalized inverse Weibull model is established via analyzing
Instagram advertising data. ,e comparison of the new distribution is made with two other models. Based on seven analytical
tools, it is observed that the new distribution is a better model to deal with data in the business, finance, and management sectors.
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