Brand Equity Prediction and Analysis with Artificial Intelligence
Date : 12-Apr-2024

Principal Investigator

Javeria Hassan Khan        

Lecturer, Department of Management Science


This research attention at identifying the role of perceived coolness in generating brand equity in smart watch users through customer experience. The data is collected from smart watch users from the twin cities. We will explore how some products can increase brand equity i.e., brand awareness, brand associations, perceived quality and brand loyalty. The AI analytics will help discover consumers insights, find new patterns and discover relationships in the data.

Completed Activites

1- Data Collection and Preprocessing:

Description: Successful acquisition and preprocessing of diverse datasets containing information related to brand performance, consumer                         sentiment, and market trends.

Ongoing Activities

2- Feature Selection and Model Training:

Description: Identification of relevant features for brand equity prediction and training of machine learning models for accurate analysis.

Future Activities

3Prediction Model Development:

Description: Development of a robust prediction model to assess brand equity, considering factors such as consumer perception, market   

                      trends, and competitive landscape.

4- Analysis and Insights Generation:

Description: Conducting in-depth analysis using the developed model to generate insights into the determinants of brand equity and its

                      impact on market performance.

Completion Status