Furniture · Customer · Epicor · VP Merchandising

Customer Behavior + Epicor + Furniture Retail: Built for VP Merchandising

Furniture operators find Customer problems in post-mortems and quarterly reviews. Ward catches them daily — with root causes and recommended actions. Your Merchandising team has the data. What they don't have is bandwidth to find what's buried in it.

What is Customer Behavior for Furniture Manufacturing & Retail?

Customer Behavior is the process of ward tracks basket composition shifts, daypart patterns, and customer segment migration.

For Furniture Manufacturing & Retail retailers specifically, this means monitoring 10,000+ SKUs across locations. ERP-locked production data, long lead times, and margin erosion you don't see until quarter-end. Ward connects your internal systems and surfaces what matters.

How Ward delivers Customer insight cards: Ward analyzes transaction-level data to detect shifts in basket composition, shopping frequency, daypart preferences, and segment movement.

Key capabilities

  • Basket composition trends
  • Daypart behavior modeling
  • Customer segment migration
  • Cross-sell opportunity detection
app.getward.ai
Live product demo — Ward analyzing retail data in real time.

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

Sales orders
Inventory
Purchase orders
Customer accounts
Pricing tiers
Vendor performance

Impact metrics with Epicor

Seasonal Accuracy
Pre-buy timing sharpened
Weather and event signals calibrate seasonal positioning.
Project Basket Value
Cross-sell patterns found
Project purchasing sequences reveal attachment opportunities.
Vendor Fill Rate
Degradation caught early
Fill rate drops flagged before shelf impact materializes.
Inventory Carrying Cost
Slow-movers identified
Demand-aligned ordering frees capital tied in dead stock.

Data lake enrichment

Ward enriches Epicor data with: Sales orders, Weather & events, Contractor/Pro data, Competitor pricing, Vendor scorecards

Your category managers are drowning in spreadsheets.

Pain points
  • ×Promo planning relies on last year's playbook, not this week's data
  • ×Assortment reviews happen quarterly when they should happen daily
  • ×Price changes are reactive, not predictive
  • ×No visibility into true cannibalization across categories
  • ×Vendor negotiations lack real-time sell-through evidence
How Ward helps
  • Insight cards flag promo cannibalization the day it happens
  • Assortment gaps and whitespace opportunities surface automatically
  • Price elasticity shifts detected before margin erosion compounds
  • Category-level performance cards replace manual spreadsheet reviews
  • Vendor scorecards generated from actual fill rate and quality data

Retailers lose an estimated $300B+ annually to suboptimal assortment and promotional decisions. — McKinsey & Company

What a Ward insight card looks like

Ward · Furniture · Customer06:47 AM

Evening shoppers (6-9 PM) adding 22% more ready-to-eat items vs last quarter. Deli adjacency planogram opportunity identified.

✓ Action recommendedFurniture context appliedEpicor data

Furniture KPI impact

Inventory Carrying Cost
Aged stock flagged
Slow-moving SKUs identified before carrying costs compound.
Order-to-Delivery Cycle
Bottleneck visibility
Cycle time tracked by production stage against baselines.
Gross Margin
Real-time by channel
Material cost drift detected as it happens, not at P&L close.
Stockout Frequency
Advance warning
POS and e-commerce signals feed back into production.

Frequently asked questions

Ward tracks basket composition shifts, daypart patterns, and customer segment migration. For Furniture retail specifically, Ward monitors 10,000+ SKUs across your locations and delivers automated insight cards with root cause analysis and recommended actions.

Ward tracks Inventory carrying cost, Order-to-delivery cycle, Gross margin by channel, Raw material cost variance, Custom order cycle time at the store-category level. Ward analyzes transaction-level data to detect shifts in basket composition, shopping frequency, daypart preferences, and segment movement.

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 Furniture-specific insight cards. No custom development required.

Your category managers are drowning in spreadsheets. Ward solves this with automated insight cards: Insight cards flag promo cannibalization the day it happens. Assortment gaps and whitespace opportunities surface automatically. Price elasticity shifts detected before margin erosion compounds.

Ward delivers daily insight cards covering Inventory carrying cost, Order-to-delivery cycle, Gross margin by channel — tailored for Merchandising decision-making. Each card includes what changed, why it matters, and what to do next.

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

Ward
Insight
Dispatch
Feedback
Evaluate
Learn
01

Insights surface

Ward’s agents detect what changed, why it matters, and what to do about it. Every insight includes a recommended action—not just a chart to interpret.

Real-time detection Root cause + recommendation
02

Insights become actions

Any insight card can be turned into a tracked ticket or task. Dispatched to the right person, on the right channel—mobile push, text, or email. Not every insight needs a ticket. But when one does, it has an owner.

Tickets created automatically Dispatched to the right person
03

Your team responds

Insights get voted up or down with reasoning. Tickets get completed or rejected. Every response is a signal—Ward learns what worked, what missed, and why.

Vote up / down Ticket completed Reasoning attached
04

Outcomes measured

Ward evaluates real results: revenue, margin, fill rate, labor cost. Did the action actually improve the number it targeted? Measured outcomes, not assumptions.

KPI impact tracked Results vs. prediction scored
05

Agents get sharper

Every vote, every completed ticket, every measured outcome feeds back in. Ward learns from your team’s judgment and real-world results. Each cycle sharpens the next. Then it starts again.

Cycle repeats, sharper each time
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See what Furniture customer problems Ward catches.

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

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Find out what your data has been hiding.

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