Ontario Expansion Strategy for Kang’s Boutique

Kang’s Boutique is seeking to expand its presence in Ontario by developing a comprehensive wholesale and retail strategy. The project aims to identify potential partner stores, regional markets, and distribution opportunities that align with the brand’s vision. Learners will conduct market research to evaluate the feasibility of partnerships and explore pricing models that suit both wholesale and retail environments. Additionally, the project will focus on retail positioning to enhance brand visibility and support the next phase of growth. The goal is to create a strategic plan that leverages classroom knowledge in business development and marketing to provide actionable insights for Kang’s Boutique’s expansion. Key objectives include: Conduct market research to identify potential partner stores and regional markets in Ontario. Evaluate the feasibility of partnerships and develop suitable pricing models. Explore distribution opportunities to enhance retail positioning. Apply classroom knowledge in business development and marketing to create a strategic expansion plan.

Digital Market Expansion Strategy for Kang’s Boutique

This experience focuses on equipping learners with the skills to evaluate market opportunities and design strategic growth plans for a Canadian fashion retailer. Participants will apply analytical frameworks and strategic thinking to real-world business challenges, specifically in the context of helping Kang’s Boutique expand its digital presence and reach new customer segments across North America . Learners will gain hands-on experience in e-commerce growth strategies, competitive positioning, social media marketing, and consumer behavior analysis , while also honing their communication and problem-solving skills through practical deliverables.

Build a Fashion Website for Kang’s Boutique

The objective of this project is to: Design and launch a new website for Kang’s Boutique , a fashion retail business in Brampton, Ontario. The website should highlight our brand identity, showcase our clothing collections, and provide an intake/contact form so customers can easily reach out. The goal is to create a professional, stylish, and mobile-friendly online presence that reflects Kang’s Boutique’s modern fashion brand. Desired outcomes by the end of the project: Build a responsive, multi-page fashion retail website (Home, About, Shop/Collections, Contact) Apply modern front-end design practices that align with Kang’s Boutique’s brand (colors, typography, visuals) Create an intake form for customer inquiries or wholesale requests Demonstrate best practices in web design and development Explain the role of front-end and back-end development in website creation Deploy the website live using GitHub Pages, Netlify, or another hosting service Ensure the website is optimized for mobile and easy navigation Recommended IBM SkillsBuild course(s): Web Development Basics Developing Sites for the Web Introduction to HTML and CCS Your Future in Web Development: The Job Landscape

IBM SkillsBuild: AI Use Case Exploration for Industry

Describe the project’s main objective and goals The objective of this project is to: Conduct an opportunity analysis to identify and evaluate three promising AI use cases within the fashion retail industry for Kang’s Boutique. The aim is to uncover high-ROI opportunities such as personalized shopping, trend forecasting, and virtual try-on experiences, and recommend how these applications could be piloted within our business. This will serve as a strategic guide for Kang’s Boutique in assessing AI initiatives with real potential for customer engagement, sales growth, and operational efficiency. Desired outcomes by the end of the project: Define artificial intelligence in the context of fashion and retail Describe three levels of artificial intelligence and their relevance to fashion businesses Explore the history and future potential of AI in retail and e-commerce Define and describe machine learning applications for fashion (e.g., product recommendations, demand forecasting) Differentiate between structured (sales, inventory) and unstructured (customer reviews, social media) data in retail Describe how machine learning structures data for insights in customer shopping behavior Explore how machine learning can use probabilistic models to improve recommendations and inventory planning Discuss methods by which machine learning analyzes purchasing trends and predicts demand cycles Describe how AI and human creativity/service can complement each other in a boutique retail environment Recommended IBM SkillsBuild course: Introduction to Artificial Intelligence