The client is a dynamic digital innovator with an impressive portfolio of top-quality furniture brands. They provide an extensive range of furniture solutions that balance style, function, and form, for both homes and businesses.
Challenge:
The retailer, selling products on multiple platforms such as Amazon, Target, and Home Depot, faced challenges in understanding the profitability of various pricing strategies.
With each platform having the autonomy to set retail prices independently, the retailer needed precise insights into how pricing on these platforms affected their profit margins and sales volumes.
To address this challenge, we developed a data analytics framework that integrated internal sales data from the retailer’s Salesforce system with external sales metrics from Amazon. This integration enabled a holistic view of profitability and sales performance specifically in comparison to Amazon.
The solution involved several steps:
Consolidating data from multiple sources, including internal sales records (profit margin, revenue, quantity shipped) and third-party data about Amazon’s sales (similar KPIs).
We used advanced analytical models to compare the retailer’s profitability from selling to Amazon with Amazon’s profitability from selling directly to consumers. This analysis took into account our wholesale prices to Amazon and how Amazon sets their retail prices, giving us a clear picture of where we stand and how we can improve.
Creating a dynamic Tableau Business Intelligence dashboard that provides real-time insights into sales performance and profitability metrics, enabling strategic decision-making.
The revenue and cost analysis over the reported period shows significant peaks and troughs, particularly a notable surge on May 6, where revenue reached $647,815. Based on this view, the retailer is now focusing on understanding the underlying factors contributing to these trends. Since this analysis allows us to drill down to product brands and categories, we can focus on finding patterns when we want to discover what drives revenue growths. Identifying what drives revenue growth during these periods will enable the retailer to replicate successful tactics and manage costs more effectively.
The number of units sold on Amazon has shown a steady performance, with slight variations that have not significantly impacted the average revenue per unit. This stability suggests that the retailer’s pricing strategy is well-calibrated to maintain consistent sales performance.
Our analysis indicates that Amazon’s profit margins are generally higher and more robust, fluctuating between 54.41% and 56.10% over the observed period. This demonstrates that Amazon’s strategies for selling directly to consumers are highly effective. As of May 13, their profit margin stands at 54.77%.
In contrast, the retailer’s profit margins when selling to Amazon are considerably lower, ranging from 8.87% to 11.89%. This disparity highlights the need for the retailer to reassess their pricing and cost structures. Despite the stability, these lower margins suggest that the retailer’s profitability is more constrained.
The significant difference between the retailer’s lower profit margins and Amazon’s higher margins underscores the efficiency of Amazon’s direct-to-consumer sales strategies. This insight is crucial as it suggests potential areas for improvement in the retailer’s pricing and sales strategies to enhance profitability.
The implementation of this data analytics solution provided the furniture retailer with several impactful benefits:
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