Anomalies

Stockful scans your sales data every day and flags SKUs whose velocity has changed in a way that doesn’t fit their usual pattern. Each anomaly comes with a short AI-written explanation of what happened and a likely cause.

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What gets flagged

The daily scan compares each SKU’s recent sales against its own baseline (the rolling average + variability) per location. When today’s velocity falls far enough outside the normal band, Stockful records an anomaly. Anomalies have a direction:

• Drop - sales fell sharply versus the baseline
• Spike - sales jumped sharply versus the baseline

And a severity, based on how far outside the normal band the change sits: Anything smaller than the medium threshold is treated as noise and isn’t recorded.

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Where you see them

• /anomalies page - the dedicated list, filterable by location, severity, and direction. Each row shows the SKU, the observed vs. baseline numbers, the AI narrative, and a link to the inventory detail page.
• Inventory detail page - if the variant you’re looking at has an open anomaly, a banner appears at the top of the page with the narrative and a Dismiss button.
• Home dashboard - a compact card on the home page surfaces the most recent unresolved anomalies so they don’t get lost.
• Slack (optional) - high-severity anomalies can be posted to a Slack channel of your choice.

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Slack alerts

To get anomalies pushed to Slack:

1. Go to Settings → AI
2. Under Anomaly alerts, pick the Slack channel for alerts
3. Set the Severity threshold - High severity only (default) or Medium and above
4. Set the Direction - Drops and spikes (default) or Drops only if you only want to know about declining sales
5. Set the Time of day the alert can fire

Each Slack message includes the SKU, the size of the change, and the AI narrative.

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Dismissing an anomaly

Anomalies stay open until you dismiss them. Click Dismiss on the inventory-detail banner or use the dismiss action on a row in the anomalies list. Dismissed anomalies are excluded from cards and Slack alerts but stay in your history (filter the list by Dismissed to see them).

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What the AI narrative does

Anomaly detection itself is statistical - it doesn’t need AI to fire. The AI step writes a short explanation: looks at the SKU’s product type, vendor, recent events (price changes, restocks), and suggests a likely cause (“matches a Black Friday lift across the catalog”, “stockout in the prior week may explain the drop”, etc.). When the model isn’t confident, the narrative says so rather than guessing.

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Plan availability

Available on all paid plans.

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Troubleshooting

• No anomalies for a SKU - the baseline needs enough recent sales history to compute. Brand-new SKUs won’t generate anomalies until they have enough data.
• Too many alerts in Slack - raise the severity threshold to High severity only and/or switch the direction to Drops only.
• Anomalies stopped appearing - check Settings → AI that Enable Stockful AI is on. If it’s off, no scan runs and no anomalies are recorded.