Stockout windows, inventory velocity, GMV trends, ghost products, price intelligence — the analytics layer your brand actually needs to grow.
Every question your catalog team asks daily — answered in real time, without building custom reports.
Exact timestamps when each SKU went OOS. Revenue lost per stockout window. Chronically stocking-out products flagged automatically.
Units/day per SKU. Days-of-stock-remaining at current sell rate. Risk-of-stockout alerts before it happens.
Net delivered GMV by month. Orders vs delivered vs returned vs RTO. COD vs prepaid split. 12-month trend view.
SKUs live on your store with zero orders in 90 days. Total inventory value locked in dead stock. Actionable cleanup list.
Price change history per SKU. Conversion impact after each price change. AI-driven price recommendations.
How long each unit has been in stock. Value locked in 30d / 60d / 90d+ buckets. Clearance candidates identified.
Cohort retention by first-purchase category. Which products create repeat buyers vs one-time purchases.
Revenue per ₹ of discount. New vs returning customer split for each coupon. Additionality vs cannibalisation.
Delivery rate by courier. RTO rate by courier and pincode. Which courier is costing you customers.
Order density by state and city. Pincode-level demand heatmap. Untapped geographies identified.
New SKUs added vs SKUs that actually sold. Category expansion quality score. Catalog efficiency trend.
AI-powered product title audit. SEO completeness score. Bulk title improvements pushed directly to Shopify.
Shopify shows you what happened. DPanda Catalog Analytics shows you why, what you missed, and what to do next.
We'll set up a live demo using your actual Shopify catalog data. See your ghost products, stockout revenue loss, and velocity leaders — in 30 minutes.
Our team will set up a personalised demo using your actual brand data.
Priced by Shopify store size — not by seat or module. All 14 analytics modules included.
Join Indian D2C and electronics brands using DPanda Catalog Analytics to find revenue they didn't know they were losing.
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