Ward for
Convenience retail.
Daypart demand variation. Planogram compliance. High-frequency, low-SKU environments where every facing counts. Ward monitors impulse categories and daypart demand patterns around the clock.
Pulled Store 37’s last 28 days against the chain baseline. Two compounding causes.
labor_efficiency | Revenue per labor hour −22%, staffing miss at the 11a–1p peak |
|---|---|
promo.lift | BOGO crackers cannibalised Brand Y −28%, net category only +6% |
Nine SKU-store pairs cross the predicted-zero threshold inside 48 hours. Store 22 produce is the most urgent.
forecast.daily | Lettuce at Store 22: 84 units/day against 38 on hand, zero by 11a Thursday |
|---|---|
supplier.lead | Regional DC lead time 18 hours, no sufficient PO already in transit |
Three stores in the ten-store cluster breach the 2% threshold on one SKU. The cause is upstream, not theft.
shrink.rate | Stores 4, 11, 19 at 2.4–3.1% against a 1.2% cluster baseline |
|---|---|
delivery.defect | All three take delivery from the same lane, defect rate 4.8% above goal |
Gross lift looked strong. Net of cannibalisation and pull-forward it destroyed value.
promo.gross_lift | Promoted SKU +41% against its own baseline |
|---|---|
promo.net | After category cannibalisation and pull-forward, net contribution −$14K |
Problems Convenience operators
find too late.
The failure modes that usually surface in a post-mortem, weeks after anyone could act on them.
Source: NACS State of the Industry Report
Dashboards
Pinned views built from saved data-lake queries.
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
ncr_pos_transactions | import | 2m ago |
pdi_fuel_transactions | import | 2m ago |
verifone_forecourt_events | import | 14m ago |
ncr_planogram_audit | import | 1h ago |
retail_daypart_sales | import | 1h ago |
retail_foodservice_waste | import | 1h ago |
retail_labor_scheduling | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
ops-read-default | permit | Model::* |
lp-read-shrinkage | permit | Model::"inventory_shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
fuel-team-forecourt | permit | Model::"fuel_transactions" |
Where Convenience operators
leave money on the table.
The KPIs Ward monitors, and what changes when someone is watching.
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.
Insight cards for Convenience.
What Ward covers
for convenience retail.
Convenience integrationsRead-only by default.
Built for convenience leadership
Metrics Ward moves
Platform pieces convenience teams lean on
Operator stories
and the alternatives.
Questions about Ward for convenience retail.
First insight cards within 48 hours of connecting to your data. Stable baselines across 3,000+ SKUs and your store estate within roughly two weeks.
Ward connects to the systems convenience operators actually run: ERP, POS, e-commerce, data warehouses, and BI tools. Read-only API access. No data movement required.
No. Ward sits on top of the data your dashboards already visualize and surfaces what changed, why, and what to do, between dashboard refresh cycles, while your team is doing other work.
Two ways to start.
A fixed-fee pilot on your convenience data, or a broader advisory engagement.
Playbooks for Convenience.
By department and system.
Tuned to Convenience & C-Store velocity and systems.
Merchandising
Supply Chain
See what Convenience operators are missing.
Ward finds the margin leaks, shrinkage patterns, and promo misfires your reports don’t surface.
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.