Research on User Demand Determination Method and Marketing Strategy for Home Broadband Business Based on Data Mining

Abstract

Abstract With the increasing demand for internet access, operators have launched home broadband business marketing activities targeting home users. However, due to the serious homogenization of products in the market and the unreasonable design of marketing plans, the related marketing work has certain difficulties. To address the above issues, this study first utilized MR fingerprint algorithm to construct a positioning model to confirm the location of household users. Then, by designing demand recognition indicators and using decision arithmetic to construct a demand model, the user’s needs and preferences were extracted to form a multi-dimensional user profile. Finally, precise marketing strategies were developed in the form of gifts based on the user’s location and personal needs. It is verified that the MR localization model has a recall rate of 95.2% and an accuracy rate of 96.2%. The on-demand model has a coverage rate of 83.8%, an accuracy rate of 96.3%, and a model accuracy of 89.7%. The proposed precision marketing strategy can achieve a success rate of 13.3% for cross network customers and 31.3% for marketing, and the failure rate of precision marketing strategy is lower than that of traditional marketing strategy among different reasons for marketing failure. Therefore, the MR positioning model proposed in the article has certain application value, and the developed precise marketing strategy has good marketing effects.