Make smarter, data-driven decisions about what to stock and how much. Our AI-powered Store Mix Enhancement solution analyzes sales trends and inventory data to recommend the right product mix at the right quantities—empowering store managers to drive revenue, reduce waste, and improve customer satisfaction.
Getting the Right Products on the Right Shelves Is Harder Than It Looks
In today’s competitive retail landscape, businesses struggle to align product availability with customer demand across locations. Traditional methods of managing store assortments often rely on outdated data or manual guesswork—leading to lost sales, overstock, and inefficiencies.
Mismatch Between Inventory and Local Demand
Stores often carry products that don’t resonate with regional buying patterns, leading to excess stock or stockouts.
Time-Consuming, Manual Decisions
Store managers and merchandisers spend hours analyzing sales and inventory data without clear, actionable insights.
Limited Visibility Across Stores
Fragmented data makes it difficult to identify what’s working—and what’s not—across locations.
Inconsistent Customer Experience
Poor product mix decisions can result in disappointed customers and missed revenue opportunities.
Inventory Carrying Costs & Waste
Overstocked or underperforming products increase storage costs and markdowns, eating into margins.
How RapidCanvas AI Enhances Store Product Mix
Our solution uses AI to continuously analyze sales and inventory patterns across regions and stores, turning data into clear, store-level product mix recommendations.
Data Integration Across Sources
Data Integration Across Sources
Ingests third-party regional sales data, historical store performance, and real-time inventory levels.
Ensure the right products are available in the right locations—boosting revenue and meeting customer demand.
Reduced Overstock & Waste
Eliminate excess inventory and minimize markdowns with smarter, demand-aligned stocking strategies.
Faster, Simplified Merchandising
Save hours of manual analysis with automated, actionable recommendations in a user-friendly interface.
Continuous Improvement Across Stores
Leverage a learning system that evolves with every sale and manager input, driving long-term efficiency.
Key Industry Metrics
Hear from Our Customers
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Getting the Right Products on the Right Shelves Is Harder Than It Looks
Mismatch Between Inventory and Local Demand
Time-Consuming, Manual Decisions
Limited Visibility Across Stores
Inconsistent Customer Experience
Inventory Carrying Costs & Waste
Mismatch Between Inventory and Local Demand
Time-Consuming, Manual Decisions
Limited Visibility Across Stores
Inconsistent Customer Experience
Inventory Carrying Costs & Waste
Mismatch Between Inventory and Local Demand
Time-Consuming, Manual Decisions
Limited Visibility Across Stores
Inconsistent Customer Experience
Inventory Carrying Costs & Waste
Mismatch Between Inventory and Local Demand
Time-Consuming, Manual Decisions
Limited Visibility Across Stores
Inconsistent Customer Experience
Inventory Carrying Costs & Waste
Mismatch Between Inventory and Local Demand
Time-Consuming, Manual Decisions
Limited Visibility Across Stores
Inconsistent Customer Experience
Inventory Carrying Costs & Waste
Mismatch Between Inventory and Local Demand
Time-Consuming, Manual Decisions
Limited Visibility Across Stores
Inconsistent Customer Experience
Inventory Carrying Costs & Waste
See Rapid Time-To-Value
Address unique business needs without starting from scratch; state your business problem and the AutoAI discovery process will generate a matching AI solution within hours.
Build Expert-Led AI
Leverage the industry knowledge of data science experts, as required, to validate against industry benchmarks and ensure optimal AI solution performance
Access Actionable Business Insights
Create visual, interactive data apps, dashboards and reports to showcase business KPIs and outcomes, and monitor business performance
Use An End-To-End AI Solution
Achieve an end-to-end AI solution with an out-of-the-box setup for all steps from data orchestration, data preparation, transformations, model building and testing, through to model deployment and data apps
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