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Coffee Shop Sales Dashboard

Problem Statement:
The coffee shop aims to gain deeper insights into its sales performance to identify trends, optimize operations, and make data-driven decisions. By analyzing sales data, the goal is to understand sales patterns, product performance, and customer behavior to improve overall business performance.Data Cleaning and Transformation:
• Data Acquisition: Sourced sales data from Excel files.
• Data Import: Imported the data into Power BI for analysis.
• Data Cleaning: Addressed data inconsistencies, errors, and missing values.
Created calculated columns for metrics like total sales, total orders, and total quantity sold. Established relationships between different data tables for comprehensive analysis.Insights and Actions:
• Identified peak sales periods and days for optimized staffing and inventory management.
• Analyzed product performance to inform product assortment and promotions.
• Identified high-performing store locations for potential expansion or replication strategies.
• Developed strategies to improve sales during slower periods.Conclusion:
The coffee shop sales analysis provided valuable insights into sales trends, customer behavior, and product performance. By leveraging the dashboard, the business can make data-driven decisions to optimize operations, increase sales, and enhance overall profitability.

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EV ANalysis Dashboard

Problem Statement:
The company struggles to effectively analyze and track electric vehicle adoption trends across various states and vehicle models. The absence of a streamlined, centralized data platform makes it difficult to evaluate the performance of different electric vehicle models and manufacturers, hindering data-driven decision-making for future market strategies.Data Cleaning and Transformation Steps:
• Imported raw electric vehicle data into Tableau for efficient visualization and analysis.
• Filtered the dataset to focus on key variables such as EV type, model year, state, and vehicle make to ensure accurate insights.
• Created calculated fields and relationships to structure KPIs, including total vehicles, average electric range, and model popularity.Insights and Actions:
• Tesla dominates the market with over 50% of total vehicle registrations.
• The highest electric vehicle concentration is in California, with 15,002 vehicles.
• Recent years (2021-2023) show a significant rise in electric vehicle adoption, with the highest sales in 2023.
• Focus marketing and resources on states with lower adoption rates to increase market penetration.Conclusion:
This Tableau dashboard enables real-time tracking of electric vehicle adoption trends across various segments, allowing the company to monitor model popularity, geographical trends, and electric vehicle growth. The visualization simplifies decision-making, identifying key areas for growth and product focus.

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Leads Analysis Dashboard

Problem Statement:
The company faces challenges in tracking both successful sales and lost leads across multiple channels, making it difficult to optimize marketing and sales strategies. Inconsistent lead conversion tracking hinders the ability to evaluate the performance of different acquisition sources effectively.Data Cleaning and Transformation Steps:
• Connected Google Sheets data to Looker Studio for real-time updates.
• Filtered and cleaned data, focusing on key metrics like deal size, lead source, and win/loss outcomes to enhance decision-making.Insights and Actions:
Sales Performance: February saw the highest average deal size, but many leads were lost, especially from event channels.
Lead Conversion: Product-based leads have the highest conversion rate (100%), while direct/unknown sources and organic search performed poorly.
Lost Leads: January and February had the most closed lost leads, with events contributing to the highest lost deal size. This highlights the need for improvements in lead nurturing and follow-up for these channels.
Win-Loss Trends: The win-loss ratio peaked at 50% in June, indicating potential strategy improvements. However, earlier months like January and February showed significant lead losses, pointing to a need for enhanced sales tactics during those months.Conclusion:
By using Looker Studio to visualize the data, the company gains valuable insights into sales performance and lead loss trends. Optimizing underperforming lead sources and adjusting sales strategies during high-loss periods can significantly improve overall performance and reduce lead attrition.

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