Construction of New Energy Vehicle User Segmentation Model Based on Data Mining Algorithm

With the rapid growth of NEV(New energy vehicle), users' daily travel demand for public charging services is increasing, and higher requirements are put forward for the service level of charging facilities operation and management units. In this paper, NEV is studied based on DM(data mining) algorithm, and the user segmentation model is constructed. DM algorithm is a brand-new business information processing technology. According to the clustering results, this paper puts forward the NEV user value evaluation method, gives the evaluation index rules and analysis results. Through simulation experiments, it is found that "non-value and non-lost users" account for the largest proportion, accounting for about 81% of all users, and belong to the user group whose value needs to be improved. In the long-term users account for 12.34%. The "non-value" long-term users account for 12.42% of the total charging power and the balance of electric cards, but the charging efficiency is slightly lower. In order to better develop NEV in China, this paper carefully analyzes the actual marketing situation of NEV in China's current automobile industry based on DM algorithm, and accordingly implements some targeted marketing strategies.