Stockout · Looker · Head of E-Com

Stockout Prediction + Looker: Built for Head of E-Com

Most retailers discover Stockout 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.

Stockout Prediction powered by Looker / Looker Studio

Stockout Prediction is the process of ward detects skus trending toward zero-on-hand and alerts your team with replenishment recommendations before customers notice.

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 stockout 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 Stockout insight cards: Ward analyzes sell-through velocity, current inventory levels, lead times, and supplier reliability to predict stockouts 24-72 hours before they occur.

Key capabilities

  • Reduce lost sales by catching gaps early
  • Automated replenishment recommendations
  • Supplier-aware lead time modeling
  • Priority ranking by revenue impact
app.getward.ai
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
  • ×Omnichannel inventory visibility is a dream, not reality
  • ×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, not the basket
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. — Harvard Business Review

What a Ward insight card looks like

Ward · Stockout06:47 AM

23 SKUs trending toward zero-on-hand within 48 hours. Replenishment recommendation attached. Priority: dairy and produce categories.

✓ Action recommendedLooker data

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 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
$1.8T
Projected global AI market by 2030
0
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Customer acquisition lift for data‑driven orgs
0
+
Foundation models shipped since 2022
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Guarantees any single model stays on top

See what stockout problems Ward catches.

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

Get a demo

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.

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