Convenience · Stockout

Ward detects. You decide. Stockout Prediction for Convenience.

Ward delivers Stockout findings as insight cards with recommended actions.

Stockout Prediction for Convenience: the Ward approach

Ward detects SKUs trending toward zero-on-hand and alerts your team with replenishment recommendations before customers notice.

Ward analyzes sell-through velocity, current inventory levels, lead times, and supplier reliability to predict stockouts 24-72 hours before they occur.

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Stockout for Convenience — live product demo.

What changes for your team

  • Reduce lost sales by catching gaps early
  • Automated replenishment recommendations
  • Supplier-aware lead time modeling
  • Priority ranking by revenue impact

Why stockout matters
in convenience retail.

The c-store value proposition is instant availability — a customer who can't find their energy drink drives to the next location, not to the next aisle. Ward models hourly sell-through by daypart, traffic flow, weather, and local events to predict which SKUs will empty before the next delivery window.

Friday night energy drink rush, 340-store chain

Ward detects energy drink velocity running well above normal at university-adjacent stores during homecoming weekend — an event its model picked up from local data. Standard delivery won't replenish until Monday. Ward issues stockout prediction cards for the affected stores and recommends emergency redistribution from lower-velocity suburban locations to protect weekend revenue.

What a Ward card looks like.

Ward · Stockout for Convenience06:47 AM

23 SKUs trending toward zero-on-hand within 48 hours. Replenishment recommendation attached. Priority: dairy and produce categories.

✓ Action recommendedConvenience context applied

Convenience stockout:
the shift.

Without Ward
Found in the quarterly review — weeks after the damage is done.
  • ×Daypart demand variation
  • ×Planogram compliance
  • ×Impulse category optimization
With Ward
Caught this morning. Root cause attached. Action recommended.
  • Reduce lost sales by catching gaps early
  • Automated replenishment recommendations
  • Supplier-aware lead time modeling

Convenience KPI impact.

Attach Rate
Impulse adjacencies
Daypart-specific cross-sell opportunities surfaced.
Daypart Revenue
Weak hours identified
Which hours and categories underperform, and why.
Planogram Compliance
Sales-correlated flags
Deviations flagged when they affect revenue, not just visuals.

Value compounds across multi-site operators. Chains with 100+ locations see the strongest returns. Fuel-dominant locations should expect impact concentrated on forecourt-to-store attach rate.

Questions about stockout.

SAP, Oracle Retail, Shopify, BigQuery, Snowflake, flat files, and any system with a REST API.

TLS 1.3, AES-256 at rest. SOC 2 Type II in progress. On-prem available.

Yes. Ward scales from 5 stores to 5,000.

Convenience stockout
by data source.

Ward
Insight
Dispatch
Feedback
Evaluate
Learn
01

Insights surface

Ward’s agents detect what changed, why it matters, and what to do about it. Every insight includes a recommended action—not just a chart to interpret.

Real-time detection Root cause + recommendation
02

Insights become actions

Any insight card can be turned into a tracked ticket or task. Dispatched to the right person, on the right channel—mobile push, text, or email. Not every insight needs a ticket. But when one does, it has an owner.

Tickets created automatically Dispatched to the right person
03

Your team responds

Insights get voted up or down with reasoning. Tickets get completed or rejected. Every response is a signal—Ward learns what worked, what missed, and why.

Vote up / down Ticket completed Reasoning attached
04

Outcomes measured

Ward evaluates real results: revenue, margin, fill rate, labor cost. Did the action actually improve the number it targeted? Measured outcomes, not assumptions.

KPI impact tracked Results vs. prediction scored
05

Agents get sharper

Every vote, every completed ticket, every measured outcome feeds back in. Ward learns from your team’s judgment and real-world results. Each cycle sharpens the next. Then it starts again.

Cycle repeats, sharper each time
$1.8T
Projected global AI market by 2030
0
×
Customer acquisition lift for data‑driven orgs
0
+
Foundation models shipped since 2022
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Guarantees any single model stays on top

Convenience retailers: see what Stockout problems Ward catches.

Root causes, not just alerts. See it on your data.

Get a demo

Find out what your data has been hiding.

Tell us about your operation. We’ll show you the problems Ward catches — and the ones your current tools miss.

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