How MarginWhiz Makes Pricing Decisions
The short video below explains how MarginWhiz supports pricing decisions using data, logic, and repeatable optimization cycles.
How to Use MarginWhiz
Use our web interface for quick setup and visual control
Step 1: Set Up Your Project
Create a new project with your core settings — like market, currency, and product types. MarginWhiz uses this setup to tailor your optimization cycles and target pricing intelligently.
Step 2: Upload Your Master Product Data
Drop in your product list as a CSV — including current margins, sales, and product attributes. MarginWhiz maps the fields and prepares your data for intelligent recommendations.
Step 3: Get MarginWhiz Recommendations
MarginWhiz analyzes your data and recommends optimal adjustments — based on your base margin and key product attributes like Size or Color. Suggestions are derived from our AI-powered pricing engine trained on real-world patterns. You can override any recommendation — but most users just click Confirm and go.
Step 4: Run the Optimization Cycle
Once you're happy with the setup, MarginWhiz exports your new prices. You apply them in your store or system — then watch the sales roll in.
Step 5: Upload Sales Data & See What Worked
After the test period, upload actual sales. MarginWhiz compares before vs. after — and shows you what changed. It breaks down the impact by attribute, value, and overall effect.
Step 6: Get Smart Next-Step Recommendations
Based on the results, MarginWhiz recommends what to do next — continue with the same attribute, try a new one, or pause. You stay in control — but the system does the thinking.
Watch the Demo
See MarginWhiz in action — how projects are set up, data uploaded, and margins optimized step by step.
The AI Engine
🤖 How MarginWhiz Uses AI
Our AI engine combines pricing logic, observed margin behavior, and machine learning models trained on real-world e-commerce data. The system analyzes:
- Historical performance — What margin changes worked in the past
- Attribute correlations — How size, color, brand affect price sensitivity
- Market dynamics — Demand patterns and competitive positioning
- Sales velocity — Moving fast vs. moving slow products
The result: transparent, explainable recommendations that can be reviewed, adjusted, and applied with confidence. AI suggests, you decide.
🎯 Attribute Ranking
AI identifies which product attributes (category, brand, size) have the highest optimization potential based on your data.
💰 Margin Recommendations
For each attribute value, AI suggests optimal margin adjustments with reasoning — balancing profitability and sales velocity.
🔄 Next-Action Logic
After each cycle, AI analyzes results and recommends whether to continue, switch attributes, or end optimization.
💡 AI Service Architecture
Our AI runs on a separate service at ai.marginwhiz.com — ensuring fast, scalable recommendations whether you use the web interface or integrate via API.
Available to both UI and API users. Same intelligence, your choice of interface.