Convenience · Promos · NCR · Head of LP

Head of LP: convenience promos, read from NCR Voyix

Ward reads straight from POS transactions, item-level sales, tender data from NCR Voyix, scans continuously promos across 3,000+ convenience SKUs, and sends the loss prevention read each day.

Promo Effectiveness for Convenience on NCR, scoped to loss prevention

Convenience & C-Store changes the scale of the problem: 3,000+ SKUs, every one of your locations. High-frequency, low-SKU environments where every facing counts. Ward monitors impulse categories and daypart demand patterns around the clock.

Shrinkage costs you more than you think. Ward finds out where. Ward writes the finding at the altitude a Head of LP works at.

Promo Effectiveness, in one sentence. Ward measures true promotional lift net of cannibalization, pull-forward, and pantry loading.

The mechanism. Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.

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

Key capabilities

  • Net lift measurement (not gross)
  • Cannibalization quantification
  • Pull-forward detection
  • Promo ROI scorecards
app.getward.ai Live demo
Acme Convenience @Store Ops: Regional Analyst claude-sonnet default
A

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why is the morning daypart down at the Route 9 sites?
You · 9:42 AM
Schema Scout · routed to Store Ops Agent

I pulled the 6–9a daypart for the 14 Route 9 sites against the chain baseline. Two causes, one of them scheduling.

SignalFinding
daypart_sales6–9a revenue −11% vs. chain, coffee units −18%
labor_schedulingSecond associate clocks in at 7:30a, peak starts 6:40a at 9 of 14 sites
foodservice.wasteBreakfast sandwich waste 14%, hold times past 4 hours at 6 sites

Recommend: move the second open to 6:15a at those nine sites, cut the breakfast batch by one tray, and re-check attach in two weeks.

7 parallel queries 3 sources cited confidence 0.91
Show me the schedule change by site.
You · 9:43 AM
Labor Agent · drafting shift diff
Querying daypart_sales
Ask anything, Ward routes to the right agent. Cmd+K

Reporting

Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.

7d13w52w
Inside-store sales
$12.9M
+2.4% WoW
Foodservice margin
47.3%
−2.1pp
Attach, fuel-to-store
31.2%
−1.6pp
Shrink, cigarettes
1.94%
+0.6pp
Inside-store sales 13 weeks actual, 6 weeks forecast, 80% interval
Actual Forecast 80% interval
% of plan 106 94 100 forecast → W−13 W−5 today +6wk
Holt-Winters + weather regressor MAPE 4.1% at 4wk Backtested 24 months Crosses plan in 3 weeks
Forecast error by horizon MAPE, 24-month backtest
1wk 2.1%
2wk 3.0%
4wk 4.1%
8wk 6.3%
13wk 8.9%
Accuracy bar for promo decisions: ≤5% at 4wk
Models in production Every forecast ships a model card
ModelHorizonMAPE
holt_winters4wk4.1%
arima_sarimax13wk8.9%
gbm_demand1wk2.1%
bayes_hiernew store11.4%

Sources

Connect external systems to the data lake.

NameTypeLast sync
ncr_pos_transactionsimport2m ago
pdi_fuel_transactionsimport2m ago
verifone_forecourt_eventsimport14m ago
ncr_planogram_auditimport1h ago
retail_daypart_salesimport1h ago
retail_foodservice_wasteimport1h ago
retail_labor_schedulingimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
ops-read-defaultpermitModel::*
lp-read-shrinkagepermitModel::"inventory_shrinkage"
vendor-blockedforbidModel::"labor_*"
fuel-team-forecourtpermitModel::"fuel_transactions"
Promos for Convenience on NCR data, live product demo.

Why Promos matters for Convenience retail

Most c-store operators accept vendor-funded promotions without measuring whether they actually improve store economics. Multi-unit deals can cannibalize single-unit margin, and rebates often don't offset the erosion. Ward measures the true P&L impact of each program, giving operators evidence for vendor negotiations.

What Ward has eyes on.

Know which promos actually work. Ward runs the model continuously rather than on a reporting cycle, which is why a finding lands the morning the pattern starts instead of at the end of the period.

Coverage is store by store, category by category. Ward scans continuously transactions/hour, attach rate, basket size over 3,000+ SKUs and compares each store against its own baseline, not against the chain. That is the difference between knowing the store base is fine and knowing which seven locations are not.

Ward reads NCR rather than replacing it. POS transactions, item-level sales, tender data come across on a read-only connection, get enriched with contextual data, and come back as findings. Your POS is untouched.

At the metric level. Ward tracks unit lift vs margin impact, single-to-multi-unit cannibalization, vendor funding offset accuracy, and post-promo demand suppression, including inventory holding, labor for reset, and displaced revenue from non-promoted items.

Signals · POS at SKU-store-day with promo flags, full vendor funding terms, event calendars, labor schedules, and basket compositions including adjacent SKU effects.

Why this combination
is its own problem.

Promo Effectiveness needs POS transactions and item-level sales at minimum. NCR Voyix carries both, at the grain the model needs. That is the whole integration story: no middleware, no staging warehouse, no custom extract.

  • 01 Display labor and reset cost is left out of promo P&L; on tight-staffing nights, store-level cost can exceed vendor funding.
  • 02 Vendor funding gets credited against the discount in margin reports, hiding the cannibalization of single-unit margin and adjacent-SKU sales.

Benchmarks. C-store vendor promo programs typically show 15-50% gross unit lift and 3-15% net margin lift after cannibalization, funding, and labor. Most chains run 100-300 vendor events per year; the bottom quartile is usually negative-net.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward plugs into NCR Voyix with read-only credentials and begins ingesting POS transactions and item-level sales. No config changes on your side. First cards arrive inside the first 48 hours.

  2. 02

    Weeks 2 to 3: baselines

    Ward needs roughly two weeks of history per store to separate a real deviation from normal variance. During this window the cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: steady state

    Ward hands back findings daily, each with the cause and the next step. Volume settles at a level a single person can read over coffee. The measure of success is not how many daily cards arrive, it is how many get acted on.

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 lands as a year-end surprise
  • ×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. Source: National Retail Federation

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 once they start costing revenue.
Shrinkage
Slow-bleed detection
Transaction-level anomalies that periodic audits miss.

Frequently asked questions

Ward measures true promotional lift net of cannibalization, pull-forward, and pantry loading. For Convenience retail specifically, Ward monitors 3,000+ SKUs across your locations and delivers automated insight cards with root cause analysis and recommended actions.

Ward tracks Transactions/hour, Attach rate, Basket size, Planogram compliance, Daypart mix at the store-category level. Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.

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.

Ward tracks unit lift vs margin impact, single-to-multi-unit cannibalization, vendor funding offset accuracy, and post-promo demand suppression, including inventory holding, labor for reset, and displaced revenue from non-promoted items.

A top beverage vendor runs 26 promotional events per year across the chain. Ward reveals that fewer than half generate positive net margin after accounting for cannibalization and margin erosion. Ward provides per-event ROI scorecards the category manager uses to renegotiate: fewer but deeper promotions on high-ROI events, elimination of negative-margin ones, and better vendor funding terms.

First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish stable 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.

See what Convenience promos problems Ward catches.

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

Read-only to start · your LLM keys · SOC 2 Type II underway · or book a call directly

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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Step 2 of 3
About your operation
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