Mahamed Hassan
Learner -
(1)
4
Location
Toronto, Ontario, Canada
Portals
Categories
Data analysis Competitive analysis Artificial intelligence Data science

Skills

Competitive analysis 1 Customer engagement 1 Data analysis 1 Data cleansing 1 Data manipulation 1 Data science 1 Operational efficiency 1 Project management 1 Proofreading 1 Quality control 1

Achievements

Latest feedback

Recent projects

Ami Tea & Sub
Ami Tea & Sub
Calgary, Alberta, Canada

AMT-BDR3 RFP Customer Reviews Analysis

The AMT-BDR3 Customer Review Analysis project, as part of the Ami Tea & Sub 2024-2025 Business Development Roadmap (BDR) Initiative, seeks to leverage advanced data analytics to enhance customer experience and business performance. This project focuses on developing a PowerBI-driven customer sentiment dashboard to accurately measure customer preferences and track feedback across various platforms. Advantages of a Customer Review dashboard include: Enhanced Customer Experience Insight, where PowerBI utilization would aggregate and analyze reviews from multiple sources, including social media and online platforms to develop an intuitive dashboard that can capture sentiments, preferences, and dissatisfaction points. Data-Driven Operational Improvements, which will highlight key areas that need improvement, such as menu items, service speed, or ambiance. This can create momentum for management to pursue alternative strategies in customer engagement or refine current training standards. Strategic Business Decision-making, which aims to provide actionable insights to drive strategic decision-making. This includes menu optimization, marketing strategies, and potential aeras for expansion or renovation.   What is its strategic implications?   The strategic implications of the AMT-BDR3 Customer Review Analysis project for Ami Tea & Sub are multifaceted, especially when considering the disparity in customer preferences and performance across different locations, such as the contrast between Inglewood/Chinatown and mom n' pop-owned stores like Heritage or St. John. This project's focus on developing a PowerBI-driven dashboard to analyze customer sentiment and feedback is not just about harnessing data; it's about understanding the underlying factors contributing to these inconsistencies.   Firstly, the analysis may reveal gaps in staff training or management practices at underperforming locations. The difference in staff numbers and the consequent variation in customer experience underscore the need for a standardized training protocol and quality control measures across all franchisees. For a franchisor like Ami Tea & Sub, ensuring consistency in customer experience is paramount. It's not just about maintaining the brand's reputation; it's also about delivering the promise of quality and service that customers expect from a franchised establishment, regardless of its location.   Furthermore, the insights gained from this project will enable Ami Tea & Sub to align its operational strategies with the dynamic and location-specific customer preferences. This is crucial in tailoring menu offerings, marketing efforts, and overall customer engagement strategies to meet the unique demands of each locale. By understanding the nuances of different market segments, Ami Tea & Sub can optimize its operations to cater effectively to diverse customer bases.   Additionally, the project aligns with best practices identified in the DTTP Competitive Analysis, which highlights that major F&B chains are increasingly investing in data analytics. This not only validates the approach but also sets a foundation for Ami Tea & Sub to explore and integrate advanced data analytics into its business model. By doing so, Ami Tea & Sub is not merely catching up with industry standards but is also positioning itself to proactively leverage data for strategic decision-making, future-proofing the business in a highly competitive market.   Goals that this project supports: Primary Goals Standardization of Training and Quality Control: Implement a comprehensive training program across all Ami Tea & Sub locations, focusing on service quality and operational efficiency, to address inconsistencies and elevate customer experience, especially in underperforming areas. Location-specific Operational Optimization: Tailor operations and menus at each customer sentiment to boost satisfaction and performance, particularly in locations currently lagging behind in customer preferences.   Immediate Data Integration and Analysis Capability Enhancement: Rapidly deploy a user-friendly PowerBI dashboard for real-time customer feedback analysis, enabling quick operational decisions. Secondary Goals Brand Consistency and Reputation: Enhance Ami Tea & Sub’s brand reputation for quality and consistency through long-term customer feedback monitoring ad continuous service improvement. Strategic Business Expansion and Innovation: Utilize customer data insights for market expansion, new products innovation, and service enhancement. Industry Leadership in Data-Driven Decision-Making: Position Ami Tea & Sub as an emerging industry leader in data analytics within the Vietnamese F&B sector, continually investing in advanced tools and fostering a culture of evidence-based decision-making.   What areas will be covered? The AMT-BDR3 Customer Analysis Project covers the following four areas: Data Acquisition and Cleanup: involving the systematic collection of customer feedback data from various sources such as social media, online review platforms, and in-store feedback forms. Potential tasks include: establishing data collection protocols, setting up automated data scraping tools if necessary, and performing data cleaning and preprocessing to ensure accuracy of data before the analysis. Development of PowerBI Dashboard: this is the core of the project, which is intended to provide intuitive and insightful visualization of customer feedback data based on the appropriate user level. Potential tasks include: designing the dashboard layout, configuring data import and visualization tools, and ensuring that the dashboard is user-friendly and can display real-time data effectively. Data Manipulation and R-Programming Integration: deals with the integration of advanced data analysis techniques, particularly R for sentiment analysis, to glean deeper insights from customer feedback data. Potential tasks may include writing R scripts for sentiment analysis, manipulating and transforming data to suit the analysis needs, and integrating R scripts with PowerBI for seamless flow of processed data. End-user Training and Feedback (Deck Development): Final stage is crucial for ensuring that the insights derived from the dashboard are actionable and accessible to decision-makers within Ami Tea & Sub. This process may entail developing simplified training materials for end-users. 

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Category Data analysis + 3
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