Ecommerce Merchandising Dashboard
Paste your product data and get instant merchandising insights, scores, and actionable recommendations.
Paste rows with columns: Product, Category, Revenue, Units Sold, Views, Conversion Rate (%), Return Rate (%). Use commas or tabs as separators. First row can be a header.
| Category | Products | Revenue | Units | Avg Conv. Rate | Avg Return Rate |
|---|
| Product | Revenue |
|---|
| Product | Revenue |
|---|
Composite score (0-100) based on revenue share, conversion rate, views, and return rate relative to averages.
| Product | Category | Score | Revenue | Conv. Rate | Return Rate |
|---|
Understanding Merchandising Analytics
What Is Merchandising Analytics?
Merchandising analytics combines product performance data with customer behavior to decide what to promote, reposition, or phase out. Instead of guessing which products deserve homepage real estate, you let the numbers decide. It covers everything from category-level trends to individual SKU profitability.
Revenue Per View (RPV)
Revenue per view tells you how much money each product page visit generates on average. A product with 50,000 views but only $2,000 in revenue (RPV = $0.04) is underperforming compared to one with 5,000 views and $5,000 revenue (RPV = $1.00). Use RPV to identify products that deserve more visibility.
Category Management
Category management means treating each product category as its own business unit. You analyze revenue, margin, and conversion rate at the category level to spot which categories are carrying the store and which are dragging it down. Smart allocation of marketing spend and shelf space follows from this analysis.
The Pareto Principle in E-commerce
In most stores, roughly 20% of products generate 80% of revenue. Identifying your top performers lets you double down on what works. Equally important: understanding which products in the long tail might be costing you money in warehousing and maintenance without contributing meaningfully to the bottom line.
Merchandising Best Practices
✓ DO
- Review merchandising data weekly, not just monthly
- Compare conversion rates within the same category (not across all products)
- Factor in return rates when calculating true product profitability
- Use revenue per view to allocate homepage and category page placement
- Test promotional placement changes with A/B tests before going all-in
- Segment by traffic source — paid traffic converts differently than organic
✗ DON’T
- Judge products solely by revenue — high revenue with high returns is a trap
- Ignore low-traffic products — they might convert well if given more visibility
- Compare seasonal products against evergreen ones without adjusting for timing
- Remove underperformers without checking if they drive cross-sells
- Optimize for conversion rate alone — a 10% rate on $5 products matters less than 1% on $500 items
- Set and forget your merchandising — product performance changes over time