Specialty · BigCommerce · VP Merchandising

BigCommerce + Specialty Retail: Built for VP Merchandising

Specialty retailers have 5,000+ SKUs and blind spots hiding in every store. Ward watches them all and delivers the findings your team doesn't have bandwidth to find. Your BigCommerce data holds answers nobody has time to extract. Ward reads it via read-only APIs.

Ward + BigCommerce for Specialty Retail

Specialty Retail retailers running BigCommerce get AI insight cards without custom development. High-consideration purchases, curated assortments, and customer lifetime value. Ward tracks the metrics that matter for margin-rich retail.

How it works: Ward connects via BigCommerce REST API with OAuth. Webhooks for real-time order and inventory events.

Ward monitors 5,000+ SKUs across your boutiques and delivers automated insight cards covering CLV, Conversion rate, Units per transaction, and more.

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

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why did Store 37 miss target last week?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.

SignalFinding
labor_efficiencyRev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak
inventory.freshFresh fill 83%, backroom replenishment lag at 2–4p
promo.liftBOGO crackers cannibalized Brand Y by 28%, net category +6%

Recommend: re-baseline Store 37 schedule against true peak, raise replen window to 1p, and review the BOGO before next cycle.

8 parallel queries 3 sources cited confidence 0.92
Show me how to fix the staffing mismatch.
You · 9:43 AM
Labor Agent · drafting schedule diff
Querying labor_scheduling
Ask anything, Ward routes to the right agent. Cmd+K

Dashboards

Pinned views built from saved data-lake queries.

Revenue vs. forecast +4.2% WoW
Gross margin % −3.2pp
Fill rate, fresh 83%
Shrink, West region +0.8pp

Sources

Connect external systems to the data lake.

NameTypeLast sync
sap_pos_transactionsimport2m ago
sap_inventory_shrinkageimport2m ago
sap_labor_schedulingimport14m ago
retail_inventory_weeklyimport1h ago
retail_google_ads_dailyimport1h ago
retail_meta_ads_dailyimport1h ago
retail_ga4_website_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::*
finance-read-shrinkagepermitModel::"inventory_shrinkage"
vendor-blockedforbidModel::"labor_*"
region-west-onlypermitTenant::"acme"
Live product demo, Ward analyzing retail data in real time.

What Ward delivers

  • 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

Metrics Ward monitors

CLV
Conversion rate
Units per transaction
Repeat purchase rate
Sell-through by tier

Specialty challenges Ward solves

  • Assortment curation
  • Customer lifetime value
  • Staff selling effectiveness
  • Clienteling optimization
  • Inventory depth vs breadth

How Ward connects to BigCommerce

Ward connects to BigCommerce for omnichannel retailers running headless or traditional storefronts. Orders, catalog, and customer data drive insight cards.

Setup: Ward connects via BigCommerce REST API with OAuth. Webhooks for real-time order and inventory events.

Data Ward reads from BigCommerce

Orders
Products & variants
Customers
Inventory
Promotions
Storefront analytics

Impact metrics with BigCommerce

Sell-Through Rate
Velocity tracked live
Slow movers flagged early enough to reallocate inventory.
Customer LTV
Churn risk identified
Cohort analysis surfaces lapsing buyers and re-engagement timing.
Conversion Rate
Buyer vs browser split
Patterns that convert separated from those that just browse.
Inventory Turnover
Reorder cadence optimized
Demand signals calibrate reorder points across the catalog.

Data lake enrichment

Ward enriches BigCommerce data with: Orders & variants, Customer behavior, Marketing data, Returns & exchanges, Competitor pricing

Your category managers are drowning in spreadsheets.

Pain points
  • ×Promo planning still runs off last year's playbook
  • ×Assortment reviews happen quarterly when they should happen daily
  • ×Price changes chase the market a week behind it
  • ×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. Source: McKinsey & Company

Specialty KPI impact

CLV
Churn risk surfaced
At-risk customers identified before they leave.
Conversion Rate
Assortment + staffing
Cards that help convert high-intent browsers.
Revenue per SKU
Whitespace found
Underperformers identified, gaps in curated assortment.
Overstock
Less capital locked
Demand matching reduces slow-moving inventory.

Frequently asked questions

Ward connects via BigCommerce REST API with OAuth. Webhooks for real-time order and inventory events. Data points include: Orders, Products & variants, Customers, Inventory, Promotions, Storefront analytics.

Yes. Ward reads BigCommerce data and combines it with contextual signals (weather, events, demographics) to generate Specialty-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 CLV, Conversion rate, Units per transaction, 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 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.

See what Specialty problems Ward catches.

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

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