Optimizing Multi-Channel Sales Strategies through Data Analytics

Industry: Retail (Furniture)

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.


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:

Data Integration

Consolidating data from multiple sources, including internal sales records (profit margin, revenue, quantity shipped) and third-party data about Amazon’s sales (similar KPIs).

Profitability Analysis

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.

Dashboard Development

Creating a dynamic Tableau Business Intelligence dashboard that provides real-time insights into sales performance and profitability metrics, enabling strategic decision-making.

Screenshot of a Tableau dashboard for retail price trends, showing revenue, cost analysis, and profit margins between Amazon and a furniture retailer across various timeframes.


  1. Revenue and Cost Dynamics:

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.

  1. Consistency in Units Sold and Revenue Per Unit:

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.

  1. Amazon’s vs Retailer Profit Margins:

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.

Next Steps for Enhanced Profitability and Growth

  • Deep Dive into Revenue Spikes: Investigate the factors that led to revenue peaks, especially around May 6, to understand what worked well. This will help the retailer replicate these successes and avoid potential pitfalls in future strategies.
  • Refine Pricing Strategies: Continue refining the retailer’s pricing strategies on Amazon to ensure they are optimized for maximum profitability. This includes staying competitive while also maintaining healthy margins.
  • Expand Analytical Framework to Other Platforms: While this report focuses on Amazon, applying this analytical approach to other platforms like Target and Home Depot can provide a holistic view of the overall sales performance. This will enable the retailer to make informed decisions across all sales channels, enhancing their strategic planning and execution.
  • Enhance Promotional Strategies: Based on the insights from Amazon, tailor the retailer’s promotional strategies to drive better results during peak sales periods across all platforms. This will help them maximize the impact of their promotional efforts and improve overall profitability.


The implementation of this data analytics solution provided the furniture retailer with several impactful benefits:

  1. Enhanced Profitability Insights: Clear visibility into revenue per product per category, aiding in strategic pricing and distribution decisions.
  2. Data-Driven Decision Making: Helped the retailer to make informed decisions on how to better negotiate the product’s prices when selling to Amazon  based on profitability analysis.
  3. Scalable Analytics Framework: Established a robust and scalable framework that the retailer plans to extend to additional sales platforms, enhancing their overall sales strategy.

Technologies and Tools

  • Salesforce: for internal sales data management
  • Marshall Insights System: for platform’s sales data management
  • Snowflake: for data integration and management
  • Tableau: for dynamic dashboard creation and reporting.