ENHANCE ENTERPRISE MARKETING STRATEGY BY TARGET CUSTOMER SEGMENTATION BASED ON CUSTOMER’S VARIANCES
Keywords:
Customer Segmentation, E-Commerce, Clustering Techniques, Personalization, Marketing StrategiesAbstract
Offering every Customer, an identical product model, email, text message, or campaign is not a practical strategy. Customer needs might differ. Additionally, promoting the same item and running the same advertisement results in decreased engagement, resulting in lower income. Customer segmentation can assist in resolving this problem. By figuring out the optimal amount of unique consumer groups and basing it on customer behaviour, one better grasps the distinctions between their clients and caters to their demands. Customer segmentation improves the customer experience and boosts revenue for the company. Because of this, performing customer segmentation is essential to beat the e-commerce market's escalating rivalry. The choice of clustering technique depends on the unique properties of the data and the segmentation goals. There are several clustering algorithms that may be utilized for e-commerce customer segmentation. A hybrid model can be created by combining K-means with hierarchical agglomerative clustering, and it can work for all sorts of data sets. Because of the dispersed nature of the data, it is used to segment and cluster users for the same goal, as well as to identify hidden patterns in all sorts of data sets.
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