Market Penetration through Digital Marketing: A Case Study of a Tractor Dealership During Covid-19 Pandemic

Vishesh Rai; Vikas Chauhan

doi:10.57159/gadl.jcmm.2.2.23042

Authors

Vishesh Rai Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India 576104
Vikas Chauhan Sonalika International Tractors Limited, Seoni, Madhya Pradesh, India 480661

DOI:

https://doi.org/10.57159/gadl.jcmm.2.2.23042

Keywords:

Digital marketing, Tractor dealership, Customer engagement, Sales enhancement, Automation tools

Abstract

The present study investigates the efficacy of digital marketing strategies in enhancing customer reach and sales for a tractor dealership, “Shyam Tractors of Sonalika International Tractors Limited,” located in Seoni, Madhya Pradesh, during the COVID-19 pandemic. The dealership adopted digital marketing to stimulate additional inquiries, leading to increased customer reach and sales. Of the total inquiries received over four months, 32% were sourced from digital marketing initiatives. These strategies encompassed the use of automation tools for continuous customer interaction, resulting in amplified brand visibility and customer trust, and fostering positive word-of-mouth. The findings suggest that the success of digital marketing strategies is contingent upon location, demographics, and target audience, emphasizing the necessity of customizing strategies to local market conditions. While digital marketing showed promising results, the continued relevance of traditional marketing underscores the need for a balanced marketing approach for optimal customer engagement. In summary, this study concludes that digital marketing strategies can effectively augment customer reach, sales, and engagement in the tractor industry, particularly during periods of economic uncertainty and market disruption. This implies that tractor dealerships could benefit significantly from integrating digital marketing strategies into their business models.

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