https://github.com/sksubhadeep/bike-sales-dashboard-using-excel
https://github.com/sksubhadeep/bike-sales-dashboard-using-excel
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/sksubhadeep/bike-sales-dashboard-using-excel
- Owner: sksubhadeep
- Created: 2023-09-17T13:03:57.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-09-26T17:41:19.000Z (over 1 year ago)
- Last Synced: 2024-12-30T06:14:37.829Z (5 months ago)
- Size: 172 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Bike-Sales-Dashboard-using-Excel
Each of these visualizations and filters can provide valuable information to understand your customer base and their preferences. Here's a breakdown of how each element contributes to the overall insights:
1. **Line Chart - Age Groups Interest in Bike Purchases:** This chart helps identify which age groups show the most interest in buying bikes. It can inform marketing and product development strategies. For example, if younger age groups are more interested, you might focus on promoting sportier or trendier bike models.
2. **Bar Chart - Gender-Based Purchasing Power:** This chart provides insights into gender-based differences in bike ownership. Understanding these differences can be crucial for tailoring marketing campaigns and product offerings to different genders.
3. **Filter Tab - Marital Status:** Allowing users to filter data based on marital status can help you understand if there are variations in bike purchase preferences between married and single individuals. It can also inform decisions related to family-oriented bike models or accessories.
4. **Filter Tab - Education:** Education level can be an important factor in bike purchases. Higher education levels might correlate with higher disposable income, which can influence the choice of bike models or accessories. By providing this filter, you can analyze how education impacts purchasing patterns.
5. **Filter Tab - Region:** Regional variations in bike sales can be significant. Certain regions might have a higher demand for bikes due to climate, terrain, or cultural factors. The regional filter allows you to identify these trends and tailor your marketing strategies accordingly.
6. **Line Chart - Customer Commute Distance:** Understanding the average customer commute distance can help you determine the suitability of different bike models. For example, if customers primarily use bikes for short commutes, you might focus on promoting city bikes or e-bikes, whereas longer commutes might require more versatile models.
Overall, these insights and features in dashboard provide a holistic view of your bike sales data, allowing you to make data-driven decisions, target specific customer segments, and adapt your product offerings and marketing strategies to maximize sales and customer satisfaction.