AI-Powered Demand Forecasting Retail Dashboard
Project category
AmbreCouture
Ecommerce
France
4.5 Months
Boost your margins with AI-driven dynamic pricing and optimize your strategy.
Project Overview
A leading French e-commerce perfume retailer sought to boost peak-season margins but struggled to adjust prices in real time as demand, competitor pricing, and inventory shifted.Â
We built a dynamic pricing solution powered by an AI engine and a power bi ecommerce dashboard, automating price updates and surfacing actionable insights.Â
The initiative delivered a 12% margin lift during peak periods by sensing demand fluctuations, tracking competitor moves, and aligning decisions to seasonal trends—keeping the brand competitive while maximizing profitability.
Main KPIs Tracked
The Dynamic Pricing Dashboard focused on the following key metrics:
- Price Elasticity of Demand
- Revenue per Unit
- Competitor Price Comparison
- Inventory Levels
- Sales Velocity
- Gross Profit Margin
- Customer Conversion Rate
- Promotional Pricing Impact
- Discount Levels
Solution Offered — AI-Driven Dynamic Pricing Dashboard Development
Our team implemented a 5-step process to deliver a comprehensive dynamic pricing solution:
Data Integration & Preparation
- Integrated historical pricing data, sales data, competitor pricing information, and inventory levels from ERP, POS, and external competitor monitoring tools.
- Ensured high-quality data for AI model development by cleaning and normalizing the data.
Machine Learning Model Development
- Built and deployed machine learning models using Azure Machine Learning to determine optimal price adjustments.
- The models considered factors like demand elasticity, competitor pricing, historical sales, and stock levels.
Dashboard Design & Visualization
- Developed an automated dynamic pricing engine that adjusted prices in real-time based on pre-configured rules and predictive analytics.
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- Incorporated competitor price tracking and market demand forecasts to dynamically adjust prices.
Automation & Real-Time Updates
- Created a Power BI dashboard that provided real-time insights into pricing performance, inventory levels, and competitor pricing.
- Offered detailed views of pricing changes, margin optimization, and sales performance by product category.
Insight Sharing & Collaboration
- Automated price updates based on the latest inventory and sales data.
- Set up real-time alerts to notify the pricing team of significant changes in competitor pricing or stockout conditions that might require immediate action.
Main Features of the Dashboard
The dynamic pricing dashboard delivers an intuitive and data-rich experience, combining real-time pricing adjustments with AI-driven insights. It empowers teams to monitor pricing performance, competitor trends, and inventory levels while optimizing margins effectively.
Business Benefits of Dynamic Pricing
Dynamic pricing leverages real-time ecommerce data analytics to optimize margins, grow sales, and elevate the customer experience.
By ingesting demand forecasts, inventory positions, competitor prices, and on-site behavior, it adjusts prices in step with market shifts and stock levels—helping retailers maximize profitability, reduce stockouts, stay competitive, and foster long-term loyalty.
01
Optimized Margins
Increased profitability by adjusting prices dynamically based on real-time data, achieving a 12% margin improvement during peak seasons.
02
Competitive Edge
Gained a competitive advantage by responding quickly to market changes and competitor pricing strategies.
Improved Sales Volume
Maximized sales during high-demand periods by aligning pricing with consumer demand elasticity.
04
Reduced Stockouts & Overstocking
By adjusting prices based on inventory levels and demand forecasts, the retailer reduced stockouts and avoided overstocking.
05
Enhanced Customer Experience
Customers received personalized, competitive prices, which improved conversion rates and customer loyalty.
Who Gains Actionable Insights from This Dashboard?
Tech Stack Used
A robust and scalable technology architecture enabled seamless dynamic pricing adjustments and real-time insights:
Power BI
Azure Machine Learning
SQL Database
Results Achieved
The implementation of the dynamic pricing model resulted in significant improvements across key business metrics, driving both profitability and competitive positioning during peak sales periods.
Key Results:
By utilizing AI-powered dynamic pricing, the retailer was able to react in real-time to market fluctuations, ensuring maximum profitability while maintaining competitive pricing.