Stockouts distort performance metrics. When a SKU is unavailable for part of a measurement period, raw sales numbers don’t reflect true demand—they reflect what sold when inventory existed. This creates a real problem: deciding whether to drop a SKU when its sales look weak, but you don’t know if weakness came from low demand or zero availability.
The Core Problem
- Incomplete data masquerading as performance: A SKU with low monthly sales might actually have solid demand, but stockouts killed half the sales window.
- Risk of false negatives: You might retire a viable product based on a metric poisoned by your own supply chain gap.
- No automatic proxy for lost demand: Enquiries, wait-list requests, or purchases of alternatives are signals, but none is a direct measure of what the unavailable SKU would have sold.
Approaches Sellers Use
- Compare in-stock periods only: Calculate sell-through or velocity using only days when inventory was available, then annualize or project. This isolates demand signal from availability.
- Run a fresh selling window: Restock and monitor a full measurement period with consistent availability to see true performance.
- Layer in indirect signals: Track customer enquiries, cart abandonment, or competitor review sentiment during the stockout to estimate suppressed demand.
- Set a minimum observation threshold: Don’t make a retirement decision on a month where availability was below 80% or 90%—wait for a full cycle.
How Squatio helps
Squatio Decode (ASIN lookup, listing visibility & Sentiment IQ review analysis) lets you monitor customer questions, review sentiment, and listing visibility over time. If a SKU had stockouts, you can audit whether customer enquiries spiked during the unavailable period—a signal that demand was there but unmet. This helps you separate “low demand” from “low sales due to supply constraint.”
When deciding whether to retire or restock, pairing cleaned sales data (in-stock days only) with Squatio’s review and question history gives you a clearer picture of true market interest.
Discussion
When you’ve faced a stockout on a borderline SKU, how did you decide whether to bring it back or retire it? Did any indirect signal (customer questions, abandoned carts, social feedback) influence your call?
Source: Reddit