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The company needed to gain deeper insights into its sales and customer data to understand what factors influenced bike purchases. they had extensive data on customers’ age, gender, income, and commute distance, so they more clarity for strategic decision-making. Management wanted a simple yet interactive tool that could visualize patterns, reveal target demographics, and support sales and marketing decisions based on real data.
My task was to develop a comprehensive Excel-based Bike Sales Dashboard that could bring together various datasets, visualize customer purchase behavior, and uncover actionable insights. The goal was to identify which demographic and regional factors most strongly correlated with bike ownership and to help management tailor marketing and inventory strategies accordingly.
Data Preparation:
Cleaned, formatted, and merged raw data from multiple Excel sources, ensuring accuracy and consistency across customer demographics and regional sales figures.
Created calculated columns to categorize customers into age brackets (Adolescence, Middle Age, Old) and commute distance ranges (0–1 miles, 1–2 miles, etc.).
Dashboard Design:
Built interactive visualizations using PivotTables, charts, and slicers to analyze sales by gender, region, age, and income.
Developed KPIs such as average income, total purchases, and purchase likelihood by demographic group.
Designed a clean and intuitive layout for real-time exploration, allowing users to filter data dynamically and instantly see relationships.
Analytical Layer:
Integrated comparative visuals such as bar charts for gender vs. purchase count, doughnut charts for age brackets, and line charts for commute distance trends.
Used conditional formatting and calculated metrics to highlight patterns, such as which regions had the highest purchase percentages or income differences between buyers and non-buyers.
The final dashboard delivered a clear view of customer behavior and provided actionable insights that directly informed marketing and operational planning:
Middle-aged males were the most likely to purchase bikes, while older customers showed lower engagement.
Customers with shorter commute distances (1–2 miles) had the highest bike purchase rates.
Higher-income groups consistently displayed greater interest in bike ownership.
North America led in total purchases, suggesting regional market strength and opportunity for expansion.
With these insights, management was able to refocus marketing campaigns toward middle-aged professionals and optimize inventory distribution in key regions. The dashboard became a vital decision-making tool, leading to more efficient sales targeting and better resource allocation.
Middle-aged customers are the primary buyers, followed by adolescents.
Action: Focus marketing messages on middle-aged professionals who value health, eco-friendly commuting, and leisure fitness.
Older customers have low purchase engagement, suggesting possible barriers such as cost or physical activity concerns.
Action: Introduce lighter or electric-assist bike options to appeal to older age groups.
Male customers are more likely to purchase bikes than females, though female participation is gradually increasing.
Action: Expand female-oriented bike campaigns — including community cycling events or “fitness lifestyle” promotions — to encourage broader market reach.
Customers commuting short distances (1–2 miles) are significantly more likely to purchase bikes.
Action: Target urban and suburban neighborhoods with short commuting zones using local advertising or ride-to-work incentives.
Those commuting more than 10 miles show minimal purchases, indicating travel distance as a limiting factor.
Action: Promote electric or hybrid models designed for long-distance riders to expand market potential.
North America leads in total bike purchases, followed by Europe and the Pacific.
Action: Maintain North American marketing dominance but explore potential partnerships or distributor expansions in underperforming regions.
Regional differences in income and commute distance indicate varying motivations — lifestyle in North America versus practicality in Europe.
Action: Tailor messaging regionally (e.g., “healthy commute” in Europe vs. “adventure lifestyle” in North America).
Buyers generally have higher average income levels than non-buyers.
Action: Position premium models toward higher-income professionals, while introducing affordable alternatives or financing plans for other segments.
Insights show clear behavioral segments:
Fitness Enthusiasts (young, short-distance commuters)
Eco-Conscious Professionals (middle-aged, higher income)
Urban Commuters (short-distance, convenience-driven)
Action: Design personalized marketing campaigns and loyalty programs around these customer personas.
The strong correlation between commute distance and purchases suggests urban design and mobility trends directly impact bike sales.
Action: Collaborate with local governments or companies promoting green mobility to position the brand as a sustainability leader.
The dashboard provides management with a single source of truth for understanding customer demographics and purchase patterns.
Action: Use this dashboard to support quarterly sales reviews, targeted ad budget allocation, and inventory management by region and age segment.
| Area | Opportunity | Recommended Action |
|---|---|---|
| Demographics | Middle-aged, high-income customers | Tailored promotional campaigns |
| Gender | Growing female interest | Launch female-specific models and ads |
| Commute Distance | Strong short-distance demand | Focus marketing on urban commuting |
| Region | North America dominance | Expand in Europe & Pacific |
| Product Strategy | Income-linked preferences | Develop premium + affordable varia |
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