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 Transforming Wholesale Data into Actionable Insights with Data Analysis, Web Scraping, and Tableau
Client Overview

A leading wholesale distributor managing multiple product categories across regions approached Insightogram to streamline how they collect, analyze, and visualize their business data.
The client relied heavily on manual data collection from multiple supplier portals and e-commerce sources, which made it difficult to track pricing trends, inventory levels, and competitor insights in real time.

The Challenge
The client’s existing process involved:

  • Manually downloading and compiling pricing and stock data from multiple wholesale websites

  • Spending hours each week cleaning, validating, and organizing dat

  • Limited visibility into fast-moving vs. slow-moving products, regional demand patterns, and pricing fluctuation​

They needed a scalable, automated, and visual solution to help their decision-makers access fresh, reliable insights — without the repetitive manual effort.
Our Approach

Insightogram designed a comprehensive data intelligence solution that combined web scraping, data processing, and Tableau visualization into one seamless system.

1

Data Collection (Web Scraping)

  • Built automated Python-based scraping scripts to extract real-time data from multiple wholesale and competitor websites
     

  • Captured essential fields such as product name, SKU, price, availability, and discount trends
     

  • Scheduled daily and weekly data refreshes for consistent accuracy

2

Data Cleaning & Analysis

  • Cleaned and standardized raw datasets using SQL and Python (Pandas)
     

  • Applied statistical analysis to identify pricing anomalies, demand gaps, and supplier trends
     

  • Combined scraped data with internal sales data for comprehensive performance comparison

3

Visualization (Tableau Dashboards)

  • ​​Developed interactive Tableau dashboards to provide clear insights at a glance
     

  • Included views for:
     

    • Price comparison across suppliers

    • Product performance by category and region

    • Stock movement and replenishment cycles

    • Margin analysis and profitability insights

Business Consultation

The Outcome

  • 80% reduction in manual effort for data collection and reporting

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  • Real-time visibility into pricing and inventory trends

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  • Improved decision-making speed across procurement and sales teams

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  • Enhanced profitability through optimized pricing and product stocking strategies

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Tools & Technologies Used

  • Python – For automated web scraping and data processing
     

  • SQL – For structured data storage and analysis
     

  • Tableau – For dynamic dashboards and visualization
     

  • Power BI (For future scaling) – integrated for potential comparative use

Conclusion

​​Through a blend of automation, analytics, and visualization, Insightogram helped the client transform unorganized wholesale data into a strategic decision-making engine.
The project not only improved operational efficiency but also demonstrated how data-driven intelligence can directly impact business growth.

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