Home stockout, delivered as insight cards instead of dashboards.
Ward delivers stockout findings as insight cards, each with a root cause and a recommended action.
Why stockout matters
in home retail.
A missing grout SKU doesn't just lose a grout sale, it kills the entire tile project basket. Ward models project basket dependencies and scores stockout predictions by basket-impact, prioritizing replenishment on the items with the highest project-abandonment risk.
Benchmarks. Home improvement project basket abandonment: a missing $5 component routinely costs $150-400 in lost project basket revenue. Pro customer baskets average 3-8x DIY size and have markedly different replenishment urgency.
Project basket dependency alert, spring season
Ward detects a popular deck stain trending toward stockout as spring project season peaks. The insight goes beyond the stain itself: project basket analysis shows customers buying this product also purchase brushes, drop cloths, and sandpaper. Ward issues a prediction card with full basket-impact context, and the DC team expedites replenishment to protect total project basket revenue across affected stores.
Three pitfalls Ward catches
in home stockout.
- 01 Stockout severity gets ranked by SKU revenue when the real cost is the project basket abandonment that follows the missing low-margin component.
- 02 Pro customer bulk orders aren't modeled separately from DIY single-unit demand; a Pro pulling 50 units of fastener creates a stockout that DIY-grade replenishment can't cover.
- 03 Seasonal spring/summer surges are modeled by chain-wide curves that miss the regional weather variance, Northeast deck season starts 4-6 weeks after Southeast.
How Ward runs stockout
for home retailers.
-
01
Map project basket dependencies
Ward analyzes basket-completion patterns to identify which components anchor multi-SKU project baskets (deck stain, tile grout, paint primer).
-
02
Project depletion at the project-anchor level
Stockout predictions are weighted by basket-impact, not just standalone revenue, so low-margin components that anchor projects rise in priority.
-
03
Separate Pro and DIY demand
Ward models Pro bulk orders separately and triggers different replenishment thresholds for stores with significant Pro account volume.
What a Ward card looks like.
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled the spring pre-build against the last three seasons and the weather signal for the 22 Southeast stores.
| Signal | Finding |
|---|---|
seasonal_prebuild | Mulch on-hand hit 61% of plan the week temps broke 70°F |
dc_push | DC push started 9 days after the first-warm-week trigger, LY it was 2 |
attach.project | Soil and edging attach fell 18% at stores that gapped on mulch |
Recommend: tie the push trigger to the 10-day forecast instead of the calendar week, pre-position two truckloads at the 8 stores that gapped, and re-set the attach endcap.
seasonal_prebuild…
Dashboards
Pinned views built from saved data-lake queries.
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
epicor_pos_transactions | import | 2m ago |
epicor_special_orders | import | 2m ago |
netsuite_inventory_snapshot | import | 14m ago |
retail_seasonal_prebuild | import | 1h ago |
retail_sku_velocity | import | 1h ago |
retail_pro_account_sales | import | 1h ago |
retail_weather_daily | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
pro-team-read-accounts | permit | Model::"pro_account_sales" |
vendor-blocked | forbid | Model::"labor_*" |
supply-read-orders | permit | Model::"special_orders" |
Home stockout:
the shift.
- ×Project basket identification
- ×Seasonal pre-positioning
- ×Long-tail inventory
- ✓Reduce lost sales by catching gaps early
- ✓Automated replenishment recommendations
- ✓Supplier-aware lead time modeling
Home KPI impact.
Ward requires 6\u201312 months to baseline seasonal categories. Pro vs DIY segment separation is critical for accurate modeling.
Questions about home stockout.
A missing grout SKU doesn't just lose a grout sale, it kills the entire tile project basket. Ward models project basket dependencies and scores stockout predictions by basket-impact, prioritizing replenishment on the items with the highest project-abandonment risk.
Ward detects a popular deck stain trending toward stockout as spring project season peaks. The insight goes beyond the stain itself: project basket analysis shows customers buying this product also purchase brushes, drop cloths, and sandpaper.
Ward accounts for project basket dependencies, seasonal demand curves, Pro customer bulk patterns, and the outsized revenue impact of missing a low-cost component that completes a high-value project.
First stockout insight cards arrive within 48 hours. Stable home baselines form within two weeks.
Home stockout
by data source.
More Home insight cards.
Home retailers: see what stockout problems Ward catches.
Root causes, not just alerts. See it on your data.
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