Home Improvement · 50,000+ SKUs

Ward for
Home retail.

Project basket identification. Seasonal pre-positioning. Project-based purchasing, long-tail SKUs, and seasonal volatility. Ward manages the complexity of 50,000+ SKU environments with ease.

Home improvement retailers lose an estimated 4–8% of revenue to seasonal overstock and stockout imbalances each year.Source: Harvard Business Review / IHL Group
Ward · Home Live
Which SKUs are dead weight right now?
Schema Scout → Merchandising Agent

Ranked on GMROI and velocity together, not units alone, so profitable slow movers survive the cut.

gmroi.sku412 SKUs below $0.90 GMROI holding $1.8M in working capital
assortment.gap31 SKUs selling in the urban cluster are unstocked in a demographically matched cluster
11 parallel queries POS + cost + on-hand confidence 0.94

Problems Home operators
find too late.

The failure modes that usually surface in a post-mortem, weeks after anyone could act on them.

Project basket identification
Seasonal pre-positioning
Long-tail inventory
Pro vs DIY segmentation
Weather-driven demand
Home improvement retailers lose an estimated 4–8% of revenue to seasonal overstock and stockout imbalances each year.

Source: Harvard Business Review / IHL Group

app.getward.ai Live demo
Acme Home @Merchandising: Seasonal Analyst claude-sonnet default
A

Dashboards

Pinned views built from saved data-lake queries.

Revenue vs. plan +2.9% WoW
Gross margin, seasonal −2.4pp
Mulch on-hand vs plan 61%
Special order cycle time +3.1 days

Sources

Connect external systems to the data lake.

NameTypeLast sync
epicor_pos_transactionsimport2m ago
epicor_special_ordersimport2m ago
netsuite_inventory_snapshotimport14m ago
retail_seasonal_prebuildimport1h ago
retail_sku_velocityimport1h ago
retail_pro_account_salesimport1h ago
retail_weather_dailyimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
merch-read-defaultpermitModel::*
pro-team-read-accountspermitModel::"pro_account_sales"
vendor-blockedforbidModel::"labor_*"
supply-read-orderspermitModel::"special_orders"
Ward analyzing Home retail data. Live product, real data lake.

Where Home operators
leave money on the table.

The KPIs Ward monitors, and what changes when someone is watching.

Seasonal Accuracy
Weather + event driven
Pre-positioning adjusted for peak season signals.
Long-Tail Turn
Dead weight separated
Which tail SKUs serve project needs vs sit idle.
Project Basket Value
Cross-sell surfaced
Project purchasing patterns drive attachment.
Inventory Carrying Cost
Capital freed
Demand forecasting reduces slow-moving overstock.
Important caveats

Ward requires 6\u201312 months to baseline seasonal categories. Pro vs DIY segment separation is critical for accurate modeling.

Questions about Ward for home retail.

First insight cards within 48 hours of connecting to your data. Stable baselines across 50,000+ SKUs and your store estate within roughly two weeks.

Ward connects to the systems home 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 home data, or a broader advisory engagement.

See what Home 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.

Step 1 of 3
What are your goals?
Step 2 of 3
About your operation
Step 3 of 3
Your contact info