Assortment Planning: Home retail, Epicor data, E-Commerce decisions
Ward reads straight from sales orders, inventory, purchase orders from Epicor, tracks assortment across 50,000+ home SKUs, and returns the e-commerce read each day.
The full picture: home assortment, Epicor data, E-Commerce decisions
Applied to Home Improvement, the surface area is 50,000+ SKUs throughout stores. Project-based purchasing, long-tail SKUs, and seasonal volatility. Ward manages the complexity of 50,000+ SKU environments with ease.
Your online and offline data live in different worlds. Ward writes the finding at the altitude a Head of E-Com works at.
Assortment Planning is a card type Ward runs continuously. Ward analyzes sell-through by store cluster to recommend which SKUs to add, drop, or reallocate.
Under the hood. Ward clusters stores by demographic, traffic, and sales patterns, then measures SKU performance against cluster benchmarks.
Getting the data in. Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.
Capabilities
- SKU rationalization recommendations
- Whitespace opportunity detection
- Planogram optimization inputs
- Store cluster segmentation
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…
Reporting
Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.
| Model | Horizon | MAPE |
|---|---|---|
holt_winters | 4wk | 4.1% |
arima_sarimax | 13wk | 8.9% |
gbm_demand | 1wk | 2.1% |
bayes_hier | new store | 11.4% |
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" |
Why Assortment matters for Home retail
The top 2,000 SKUs generate the bulk of revenue, but the remaining 48,000 are what makes you a project destination. Drop a niche fitting and you lose the entire project basket. Ward identifies which tail SKUs are project-basket anchors worth keeping and which are truly dead weight that should be rationalized.
What Ward has eyes on.
Ward tracks 50,000+ SKUs throughout your stores, at the store-category level rather than the chain roll-up. The metrics under watch include project basket value, seasonal accuracy, long-tail turn. A roll-up hides a single-store problem inside a healthy average, which is how project basket identification stays invisible for a quarter.
Ward pulls from Epicor rather than replacing it. Sales orders, inventory, purchase orders come across on a read-only connection, get enriched with contextual data, and come back as insight cards. Your ERP is untouched.
Stock what sells. Cut what doesn't. 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.
At the metric level. Ward tracks long-tail project basket affinity, Pro vs DIY assortment dependency, seasonal SKU activation cycles, and revenue-per-linear-foot by department and planogram section.
Why this combination
is its own problem.
A Head of E-Com does not need the assortment model explained. They need to know which stores moved, why, and what to do by end of day. Ward writes the finding at that altitude.
- 01 SKU rationalization based on standalone velocity destroys project-basket anchors and drives customers to competitors for the entire job, net assortment economics turn negative.
- 02 Seasonal activation cycles mean a SKU "dead" for 9 months can be critical for 3; chain-wide 90-day velocity cuts kill seasonal anchors prematurely.
Benchmarks. Home improvement long-tail SKUs (the bottom 60-70% of catalog by velocity) typically generate 8-15% of standalone revenue but anchor 25-35% of project basket value. Pro customers depend disproportionately on the tail, losing tail items typically costs 2-4x the standalone revenue impact in Pro retention.
What the first 90 days
actually look like.
-
01
Week 1: connect
Read-only credentials to Epicor. Ward reads sales orders, inventory, purchase orders and starts building baselines. First findings land inside 48 hours, before baselines are stable, so you can see the shape of the output early.
-
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 insight cards are directionally right and the thresholds are still moving.
-
03
Weeks 4 to 12: operating rhythm
Cards arrive daily and get triaged like any other queue. Most teams find the volume settles into something one person clears in ten minutes. What matters is the action rate, not the alert count.
How Ward connects to Epicor
Ward integrates with Epicor for home improvement, furniture, and building supply retailers. Inventory, purchasing, production, and sales data power insight cards.
Setup: Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.
Data Ward reads from Epicor
Impact metrics with Epicor
Data lake enrichment
Ward enriches Epicor data with: Sales orders, Weather & events, Contractor/Pro data, Competitor pricing, Vendor scorecards
Your online and offline data live in different worlds.
- ×Nobody can see one inventory position across every channel
- ×Online promo performance is measured separately from in-store
- ×Customer behavior data is siloed by channel
- ×BOPIS/BORIS operational complexity is growing unchecked
- ×Digital marketing attribution stops at the click
- ✓Unified insight cards across online and in-store channels
- ✓Cross-channel promo effectiveness with true attribution
- ✓Customer journey tracking across digital and physical touchpoints
- ✓BOPIS fulfillment performance monitoring with exception cards
- ✓Full-funnel marketing attribution to in-store conversion
Retailers with unified omnichannel data see 30% higher lifetime value per customer. Source: Harvard Business Review
Home KPI impact
Frequently asked questions
Ward analyzes sell-through by store cluster to recommend which SKUs to add, drop, or reallocate. For Home retail specifically, Ward monitors 50,000+ SKUs across your stores and delivers automated insight cards with root cause analysis and recommended actions.
Ward tracks Project basket value, Seasonal accuracy, Long-tail turn, Pro customer share, Attachment rate at the store-category level. Ward clusters stores by demographic, traffic, and sales patterns, then measures SKU performance against cluster benchmarks.
Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse. Data points include: Sales orders, Inventory, Purchase orders, Customer accounts, Pricing tiers, Vendor performance.
Yes. Ward reads Epicor data and combines it with contextual signals (weather, events, demographics) to generate Home-specific insight cards. No custom development required.
Your online and offline data live in different worlds. Ward solves this with automated insight cards: Unified insight cards across online and in-store channels. Cross-channel promo effectiveness with true attribution. Customer journey tracking across digital and physical touchpoints.
Ward delivers daily insight cards covering Project basket value, Seasonal accuracy, Long-tail turn, tailored for E-Commerce decision-making. Each card includes what changed, why it matters, and what to do next.
Ward tracks long-tail project basket affinity, Pro vs DIY assortment dependency, seasonal SKU activation cycles, and revenue-per-linear-foot by department and planogram section.
Plumbing carries thousands of SKUs, hundreds with zero sales in 90 days. Ward's project basket analysis reveals that many of those "dead" SKUs appear alongside high-velocity project items, a specialty elbow fitting with minimal standalone sales is still critical to a complete project basket. Deleting it sends the customer to a competitor for the entire job. Ward separates true orphaned SKUs from project-basket anchors and recommends cutting only the former.
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.
Related solutions
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Root causes, not just alerts. See it on your data.
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