20+ exceptions Storos catches automatically.
Every check below runs against your existing Shopify data — no extra hardware, no manual input. Connect your store and these run daily.
Sales & Revenue
Bad sales day detection
Your store had a down day compared to what you normally do on that day of the week. A slow Tuesday when Tuesdays are usually your best day — that's a signal.
💰 A location underperforming by 15% on a $2,000/day baseline is $300 gone in one day.
Revenue drift / gradual decline
Sales creeping down week over week. No single day looked bad, but the trend is clear over 3–4 weeks.
💰 A 5% weekly decline on a store doing $8K/week = $1,600/month within 4 weeks.
Year-over-year decline
Sales down compared to the same period last year, adjusted for seasonality.
Cross-store underperformance
One store had significantly fewer orders or lower sales than your other locations on the same day.
Discounts & Pricing
Discount rate spike
More orders than usual are getting discounts. Your team might be over-applying codes or running unauthorized promos.
💰 If discount rate doubles from 15% to 30% on 50 orders/day at $120 AOV, that's $900+ in extra markdowns.
Discount depth shift
Average discount jumped from your normal 20% to 45%. Someone's being too generous — or a code leaked.
💰 Deep discounts on 20 orders at $150 AOV = $750 in a single day.
Refunds & Returns
Refund rate spike
Refund rate higher than baseline for this day of week — by dollar amount or count.
💰 Refunds spiking from 2% to 8% on a $3,000 day = $180 in unexpected returns.
Product-level refund concentration
One product driving an outsized share of returns. Could be quality, sizing, or a specific buyer pattern.
Rapid refund clustering
Multiple refunds within 2 hours of purchase at the same location. Often indicates return fraud or process errors.
💰 Catching one $200 fraudulent return per week saves $10K/year.
Inventory
Critical stockout risk (< 7 days supply)
A product at a specific store will run out within a week at the current sell-through rate.
💰 Running out of a $50 product that sells 5/day = $250/day in lost sales.
Reorder window (7–14 days supply)
Time to place an order without going to zero.
Cross-store imbalance
One store nearly out, another has excess. A transfer solves it without a new PO.
Unexplained inventory drop (shrink proxy)
Units disappeared without a matching sale or restock record. Could be theft, miscounts, or receiving errors.
💰 Average retail shrink is 1.6% of sales. For a $1M/year store, that's $16,000.
Persistent inventory level shift
Inventory dropped and stayed down — a permanent shift, not a fluctuation.
Fulfillment
Unfulfilled order aging
Orders sitting unfulfilled at 24 hours (warning), 48 hours (serious), 72+ hours (critical).
💰 A chargeback costs $20–$100 in fees on top of the order value.
What's Coming Next
Expanding detection as more data sources come online:
Workforce
Labor cost vs. revenue, sales per labor hour, overtime spikes, schedule gaps
Customer health
VIP spend slowdown, lapsed cohorts, repeat rate changes, concentration risk
Marketing ROI
ROAS deterioration, acquisition cost spikes, channel mix shifts
Financial
Gross margin compression, unexplained expense changes, cash flow pressure
Omnichannel
Online/offline inventory mismatch, ship-from-store issues
These require additional integrations (QuickBooks, workforce tools, ad platforms) and are on the roadmap. Beta users get early access as they ship.
Get a real scan of your store. Free during early access.
Connect your Shopify, get your scan, and keep Storos watching from there. No credit card. No commitment.
Not ready yet? Stay in the loop.
Occasional updates on new capabilities and retail ops insights. No spam.
Occasional updates on new capabilities and retail ops insights. No spam.