Project One

Sales Performance of Market Space, Mooncake Love, and Toy Story Land

Showcases the sales performance of three brands, including Market Space, Mooncake Love, and Toy Story Land, over time, comparisons between stores, and reveals the impact of geographical location on sales.
Through a refined dashboard, this report provides interactive data insights for decision-making.

  1. Store ID: Each store has a unique ID, such as TOY001, TOY002, etc., which helps in identifying and tracking the performance of each store.
  2. Brand: This indicates the brand or chain to which the store belongs, for example, “Toy Story Land” represents a toy-related retail brand, while “Market Space” might represent a market or retail space offering a wider range of products.
  3. Shop Location: Specifies the specific shopping center or location of the store, such as MOKO, Olympian City, etc., which aids in analyzing the commercial appeal of specific locations or shopping centers.
  4. Street, Area, City: These fields provide the precise geographical location of the store, allowing for in-depth analysis of commercial activities in different regions of Hong Kong.
  5. Full Address: Provides the complete address of the store, which not only aids in geographical positioning but may also be used for marketing and logistics planning.
  6. District: The administrative district in which the store is located, such as Yau Tsim Mong District, Central and Western District, etc., helping to analyze the sales performance and market potential of specific administrative areas.
  • Market Distribution: Understand the distribution of different brands across various regions of Hong Kong, identify high and low-income areas, thereby optimizing future store opening strategies.
  • Brand Performance: By comparing the income of different brand stores, assess how well brands perform in the market and identify which brands are more popular among consumers.
  • Impact of Geographical Factors on Sales: Analyze the income situation of stores in different locations to understand how geographical location affects sales performance, such as whether stores in shopping centers or specific areas enjoy higher sales.
  • Market Trends: By studying the sales data of different areas and brands, gain insights into market trends and changes in consumer preferences, providing a basis for formulating marketing strategies.
    1. Revenue Trends and Seasonal Analysis:
  • Monthly Revenue Changes: Time-series charts showing total income each month, identifying sales peaks and troughs, analyzing possible reasons such as holidays, promotional activities, etc.
  • Seasonal Trends: Analyze income data to identify sales patterns in specific seasons or months, helping to forecast future sales trends and guide inventory management.
    2. Store Performance Comparison:
  • Store Performance by Area: Use bar charts or map views to show the sales performance of stores in different areas, analyzing how geographical location affects sales.
  • Brand Efficacy Analysis: Classify stores by brand, compare the sales performance of each brand, identifying the best and worst-performing brands.
    3. Revenue and Geographical Location Correlation:
  • Map View Analysis: Use Power BI’s map feature to combine income data with store geographical locations, visually displaying the sales situation in different areas, exploring how geographical location affects sales.
  • Regional Hotspot Analysis: Identify high-income area hotspots, analyze the common features of these hotspot areas, such as foot traffic, consumer spending power, etc.
    4. Dynamic Reports and Dashboards:
  • Interactive Filters and Slicers: Create dynamic reports containing filters for time, area, brand, etc., enabling stakeholders to view and analyze data according to different needs.
  • Comprehensive Dashboard: Create a dashboard containing key performance indicators (KPIs), charts, and maps, providing a comprehensive business perspective, quickly capturing important information and trends.