Client Success Story

Discover How we Optimized eCommerce Order Analysis through Executive Dashboards

The client

A Leading Footwear Company with a Nationwide Reach

Our client is one of the oldest and largest shoe manufacturers in the UK, renowned for their high-quality footwear. They distribute their products through branded stores, third-party retail showrooms, online platforms, and wholesale channels, such as large department stores.


Tracking eCommerce and Offline Orders

This client faced significant challenges in balancing their offline and online supply chain processes. Since they only recently began selling on online marketplaces like Amazon and eBay, they were also facing the complexities of tracking orders and updating inventory and prices across multiple stores.

Additionally, sustaining offline operations while overseeing and expanding online presence became increasingly difficult. The resulting price discrepancies and inventory levels led to situations where many products were sold with minimal or zero margins. The involvement of multiple platforms also made it challenging to consolidate and analyze the actual ROI statistics.


A Unified Solution for Offline and Online Operational Visibility

After analyzing their existing workflow, we realized there was a need to:

  • Unify data integration by consolidating data (orders, stock levels, sales, prices) from all eCommerce platforms (Amazon, eBay, Etsy) and offline channels into a centralized system.
  • Automate tracking and reporting by integrating advanced analytics tools.
  • Create dashboards to visually represent sales trends, inventory turnover, product performance, and comparison of orders received from different channels.
  • Help with inventory analysis to monitor stock levels, predict demand, and optimize inventory turnover.

Optimizing eCommerce Operations with Holistic eCommerce Data Management and Visualization

The proposed solution for eCommerce order analysis required us to explore the data points used by the client and identify inconsistencies, quality issues, and gaps in their current eCommerce inventory management system. Once we had this information, we streamlined the process by finalizing relevant KPIs and dashboard designs for effective analysis.


Consolidated Data from All eCommerce Platforms (Amazon, eBay, Etsy) and Offline Channels

Upon receiving access to the client’s data from both online and offline channels, we analyzed it to identify key data categories such as orders, stock levels, sales figures, and pricing information. Our eCommerce data experts employed additional Python scripts to clean this data, ensuring accuracy before consolidation.

Next, we used AWS Glue to extract and transform this data, standardizing it across all categories. The cleaned and transformed data was loaded into a centralized repository (Redshift warehouse) for scalable and secure storage.


Automated Tracking of Orders, Inventory Levels, Sales, and Price Fluctuations

We integrated advanced analytics tools such as Apache Spark for large-scale data processing to handle the substantial volume of eCommerce data. Our storage solution, Amazon Redshift, enabled quick and efficient data retrieval and querying. To establish a real-time monitoring process, we deployed AWS Lambda to leverage its serverless architecture, creating automated functions that continuously tracked data changes in orders, inventory levels, sales, and prices.


Integrated Power BI and Developed Custom Dashboard Templates

We integrated the centralized repository with Power BI to create data visualizations for a comprehensive view of sales trends, product performance, and order comparisons across different channels.

We identified and tracked key performance indicators (KPIs) such as sales trends, inventory turnover rates, and channel-wise order performance. Then, we developed custom dashboard templates integrating these KPIs, tailored to the unique needs of the client’s departments and stakeholders. Features like filters, slicers, and dynamic charts were added to enhance user engagement and facilitate detailed analysis.


Provided Inventory Analysis Support

We provided end-to-end inventory analysis support to help the client monitor stock levels, predict demand, and optimize inventory turnover in near real time. Using AWS Glue (for ETL), Redshift (to integrate inventory data), and ML services like SageMaker, we identified slow- and fast-moving products and the corresponding price fluctuations. Using this information, we created dedicated dashboards offering visibility into current stock levels, holding costs, and future demand.

Technology Stack

Data Processing

  • AWS Glue
  • Apache Spark

Data Storage

  • Amazon Redshift
    Amazon Redshift


  • Icon-Architecture/64/Arch_AWS-Lambda_64 Created with Sketch.
    AWS Lambda

Machine Learning

  • Amazon SageMaker
    Amazon SageMaker

Data Visualization and Reporting

  • Power BI

Project Outcomes

With our eCommerce data management and visualization support, the client experienced enhanced visibility in both online and offline performance. The project outcomes not only streamlined their processes but also positioned them for sustained online growth and offline success in the market.

50% reduction in manual tracking and updation of inventory and orders.

Executive dashboards on sales trends and channel performance resulted in a 30% increase in actionable insights.

Identifying slow- and fast-moving products enabled them to reduce low-margin, obsolete products by up to 25%.

Integrating ML-based services resulted in a 35% improvement in demand prediction accuracy.


Grow your Business with eCommerce Product Data Management and Data Visualization

By consolidating product data from disparate resources, integrating it with advanced analytics, and customizing executive dashboards, we delivered a holistic eCommerce solution that significantly improved the client’s visibility into their operations. You can achieve similar results with our eCommerce inventory management and data visualization services.