Demand · Looker · Head of E-Com

Demand Forecasting + Looker: Built for Head of E-Com

Most retailers find Demand problems too late. Ward delivers automated insight cards. What changed, why, and what to do. While there's still time to act. Your E-Commerce team has the data. What they don't have is bandwidth to find what's buried in it.

Demand Forecasting powered by Looker / Looker Studio

Demand Forecasting is the process of ward combines historical patterns, weather data, local events, and economic signals to forecast demand at the store-sku-day level.

When connected to Looker / Looker Studio, Ward reads looker api for query results, underlying database (direct), lookml model metadata and enriches them with contextual signals to generate demand insight cards. Ward can query Looker via API or connect directly to the underlying database. Either way, Ward monitors while your team browses.

How Ward delivers Demand insight cards: Ward builds store-level demand models incorporating seasonality, weather forecasts, promotional calendars, local events, and macroeconomic indicators.

Key capabilities

  • Store-SKU-day level precision
  • Weather-driven adjustment
  • Event and holiday modeling
  • Automatic reorder point recalculation
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.

How Ward connects to Looker / Looker Studio

Ward does not replace Looker. Ward watches the same data Looker visualizes and proactively alerts when something changes. Your dashboards stay. Ward adds intelligence.

Setup: Ward can query Looker via API or connect directly to the underlying database. Either way, Ward monitors while your team browses.

Data Ward reads from Looker

Looker API for query results
Underlying database (direct)
LookML model metadata

Impact metrics with Looker

Time to Insight
Proactive, no login
Explains why metrics moved before anyone checks a dashboard.
Anomaly Detection
Inter-refresh coverage
Catches deviations between Looker dashboard refresh cycles.
Decision Velocity
Root cause attached
Every anomaly card includes cause analysis; no drill-down needed.
Data Utilization
Unused models activated
LookML dimensions and measures queried beyond built dashboards.

Data lake enrichment

Ward enriches Looker data with: Looker query results, Underlying database, Weather & events, Competitor data, Customer segments

Your online and offline data live in different worlds.

Pain points
  • ×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
How Ward helps
  • 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

Frequently asked questions

Ward can query Looker via API or connect directly to the underlying database. Either way, Ward monitors while your team browses. Data points include: Looker API for query results, Underlying database (direct), LookML model metadata.

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.

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 demand 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