The Impact of Social Listening Tools on Brand Perception and Customer Engagement

Abstract

This paper examines the development of an advanced social listening tool designed to elevate brand perception and enhance customer engagement through efficient trend monitoring and analysis. Existing tools often struggle to sift through vast amounts of social media data beyond predefined search queries. Our proposed tool aims to address this challenge by leveraging advanced algorithms in natural language processing and machine learning. It will not only identify relevant information pertaining to specified categories or companies but also uncover emerging trends that may deviate from initial search parameters. Key features include dynamic trend identification, enabling real-time detection of emerging trends from social media conversations, and robust mechanisms for filtering contextual relevance, distinguishing between casual mentions and substantive discussions crucial for brand perception and customer preferences. Furthermore, the tool will provide an easy-to-use interface designed to allow for simple customisation of searches and trend visualization, making it accessible to non-technical users. This research will confirm the tool's efficacy in boosting brand reputation, encouraging customer interaction, and boosting brand loyalty through case studies and data analysis. The tool helps firms modify their marketing tactics in response to timely consumer feedback.