Convenience · NCR · Head of LP

NCR + Convenience Retail: Built for Head of LP

Convenience retailers have 3,000+ SKUs and blind spots hiding in every store. Ward watches them all and delivers the findings your team doesn't have bandwidth to find. Your NCR Voyix data holds answers nobody has time to extract. Ward reads it via read-only APIs.

Ward + NCR for Convenience & C-Store

Convenience & C-Store retailers running NCR Voyix get AI-powered insight cards without custom development. High-frequency, low-SKU environments where every facing counts. Ward monitors impulse categories and daypart demand patterns around the clock.

How it works: Ward reads NCR transaction data via API or data export. Real-time or batch, depending on your NCR configuration.

Ward monitors 3,000+ SKUs across your locations and delivers automated insight cards covering Transactions/hour, Attach rate, Basket size, and more.

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Live product demo — Ward analyzing retail data in real time.

What Ward delivers

  • Store-level shrinkage tracking with cause attribution
  • Anomaly detection flags stores deviating from estate average
  • Receiving dock discrepancy patterns identified automatically
  • Correlation analysis links operational changes to loss shifts
  • Trend analysis catches slow-bleed patterns audits miss

Metrics Ward monitors

Transactions/hour
Attach rate
Basket size
Planogram compliance
Daypart mix

Convenience challenges Ward solves

  • Daypart demand variation
  • Planogram compliance
  • Impulse category optimization
  • Fuel attach rate
  • Labor scheduling

How Ward connects to NCR Voyix

Ward integrates with NCR Voyix POS and Aloha for convenience and restaurant retail. Transaction-level data powers daypart analysis and impulse optimization.

Setup: Ward reads NCR transaction data via API or data export. Real-time or batch, depending on your NCR configuration.

Data Ward reads from NCR

POS transactions
Item-level sales
Tender data
Daypart summaries
Loyalty data

Impact metrics with NCR

Attach Rate
Adjacencies mapped per daypart
Impulse cross-sell patterns identified by time of day.
Daypart Revenue
Underperforming hours exposed
Traffic and weather data pinpoint revenue-light dayparts.
Shrinkage
Slow-bleed loss detected
POS anomaly patterns caught that periodic audits miss.
Basket Size
Bundle opportunities surfaced
Item-level sales mined for actionable upsell patterns.

Data lake enrichment

Ward enriches NCR data with: POS transactions, Weather & events, Loyalty data, Competitor proximity, Demographic data

Shrinkage costs you more than you think. Ward finds out where.

Pain points
  • ×Shrinkage is a year-end surprise, not a weekly metric
  • ×Cannot distinguish theft from spoilage from admin error
  • ×High-shrinkage stores only identified during audits
  • ×No correlation between operational changes and loss patterns
  • ×Exception-based reporting misses slow-bleed patterns
How Ward helps
  • Store-level shrinkage tracking with cause attribution
  • Anomaly detection flags stores deviating from estate average
  • Receiving dock discrepancy patterns identified automatically
  • Correlation analysis links operational changes to loss shifts
  • Trend analysis catches slow-bleed patterns audits miss

US retail shrinkage hit $112.1 billion in 2022 — up 19.4% year over year. — National Retail Federation

What a Ward insight card looks like

Ward · Convenience06:47 AM

Store #37 showing 4.2% shrinkage vs 1.8% estate average. Pattern suggests receiving dock discrepancy, not shoplifting.

✓ Action recommendedConvenience context appliedNCR data

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.
Shrinkage
Slow-bleed detection
Transaction-level anomalies that periodic audits miss.

Frequently asked questions

Ward reads NCR transaction data via API or data export. Real-time or batch, depending on your NCR configuration. Data points include: POS transactions, Item-level sales, Tender data, Daypart summaries, Loyalty data.

Yes. Ward reads NCR data and combines it with contextual signals (weather, events, demographics) to generate Convenience-specific insight cards. No custom development required.

Shrinkage costs you more than you think. Ward finds out where. Ward solves this with automated insight cards: Store-level shrinkage tracking with cause attribution. Anomaly detection flags stores deviating from estate average. Receiving dock discrepancy patterns identified automatically.

Ward delivers daily insight cards covering Transactions/hour, Attach rate, Basket size — tailored for Loss Prevention decision-making. Each card includes what changed, why it matters, and what to do next.

First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish robust baselines for your specific operation.

No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards — so your team acts on findings instead of hunting for them.

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
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Customer acquisition lift for data‑driven orgs
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Foundation models shipped since 2022
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Guarantees any single model stays on top

See what Convenience 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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