DATA ANALYTIC PROJECTS

Problem Statement:

The need to understand the popularity and user adoption of the MDT Mobile App since its launch in December 2022. The goal was to identify the app's usage across different outlets and strategize to increase its usage for purchasing food and beverages.

Solution:

Implemented a comprehensive data analysis using Power BI to track app usage metrics. This involved collating user data, segmenting it by outlet, and analyzing trends over time to gain insights into user behavior and app popularity.

Outcome:

The analysis provided clear insights into which outlets had higher app usage, facilitating targeted marketing strategies to encourage app usage in lower-performing areas. This led to an overall increase in app adoption and improved customer engagement.

Problem Statement:

To refine marketing strategies and enhance company performance by understanding the demographics of MDT Mobile App users.

Solution:

Conducted an in-depth demographic analysis using Power BI, focusing on age, gender, location, and other relevant factors. This involved integrating user data with demographic information to create detailed user profiles.

Outcome:

The demographic insights enabled the marketing team to tailor their strategies more effectively, resulting in more personalized and effective marketing campaigns. This contributed to a better user experience and increased app engagement.

Problem Statement:

A need to analyze customer preferences for dining options (dine-in, take away, Grab Food, Food Panda, Shopee Food, MDT App) across all outlets in 2023.

Solution:

Utilized Power BI to aggregate and analyze data on customer dining preferences. This involved sorting data monthly and categorizing it based on the type of dining option.

Outcome:

The analysis provided a month-by-month breakdown of customer preferences, helping the company adjust its operations and marketing focus accordingly. This led to more efficient resource allocation and improved customer satisfaction.