<![CDATA[The electric vehicle (EV) market has experienced unprecedented growth in recent years, largely fueled by technological advancements, increasing environmental concerns, and supportive government policies. However, this growth presents a challenge: effectively reaching and engaging diverse consumer segments within the EV market. To address this, our study employs advanced clustering analysis to segment the EV market using a comprehensive dataset from Washington state, which includes vehicle characteristics such as model year, electric range, and geographic distribution. Through this analysis, we identified four distinct clusters within the EV market. Clusters 2 and 3 are characterized by high-end, newer EV models with extended electric ranges, predominantly located in affluent urban and suburban areas. These clusters are likely composed of environmentally conscious consumers who are early adopters of advanced technologies. In contrast, Clusters 0 and 1 consist of older EV models with shorter electric ranges, appealing to a more budget-conscious demographic spread across various geographic regions, including rural areas. The insights gained from these clusters have significant implications for digital marketing strategies in the EV sector. For Clusters 2 and 3, digital marketing campaigns should focus on highlighting the luxury, cutting-edge technology, and sustainability features of premium EV models, using targeted online advertising and social media engagement. For Clusters 0 and 1, marketing efforts should emphasize the practicality, cost-effectiveness, and everyday usability of EVs, addressing potential concerns such as charging infrastructure and range anxiety. The study demonstrates the critical importance of market segmentation in crafting effective digital marketing strategies that resonate with specific consumer groups. By leveraging data-driven insights, marketers can enhance engagement, drive higher conversion rates, and ultimately accelerate the adoption of electric vehicles. Future research should explore broader datasets and additional variables to further refine these segmentation strategies and support the evolving needs of the global EV market.]]>
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