Advanced Data Capture and Networking Technologies for Customer Prioritization in Digital Marketing

Abstract

In the changing world of marketing’s landscape, it is essential to prioritize customers effectively to boost engagement and get the most out of your investments. This research delves into how cutting-edge data capture and networking technologies can elevate customer prioritization tactics. Through a dataset analysis the study combines the Hierarchy Process with the Term Frequency Inverse Document Frequency approach to assess and order customers according to various factors. The Analytic Hierarchy Process helps break down decision making tasks into to handle hierarchical structures whereas the Term Frequency Inverse Document Frequency technique examines text data to pinpoint important customer characteristics effectively. Using both of these methods together allows for an evaluation of customer value and behavior trends. The results demonstrate that utilizing these approaches substantially boosts the precision and effectiveness of prioritizing customers when compared to practices. In the research findings point out elements that influence customer interaction and showcase how detailed data examination can reveal unidentified customer groups. It stresses the significance of utilizing data gathering and networking tools to guide marketing choices. Through embracing these methods firms can improve their marketing strategies to reach audiences and in turn boost customer happiness leading to long term growth. This study enhances marketing by offering a structure, for prioritizing customers and showcasing how blending analytical methods can revolutionize marketing tactics in a data focused setting.