Customer · BigQuery · Head of E-Com

Customer Behavior + BigQuery: Built for Head of E-Com

Most retailers discover Customer 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.

Customer Behavior powered by Google BigQuery

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

When connected to Google BigQuery, Ward reads any bigquery dataset, ga4 event exports, ads data transfers and enriches them with contextual signals to generate customer insight cards. Service account with BigQuery Data Viewer role. Ward runs read-only SQL queries on your schedule.

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 Google BigQuery

Ward queries BigQuery using your existing datasets. GA4 exports, POS data, CRM exports. Ward reads it where it lives.

Setup: Service account with BigQuery Data Viewer role. Ward runs read-only SQL queries on your schedule.

Data Ward reads from BigQuery

Any BigQuery dataset
GA4 event exports
Ads data transfers
Custom ETL outputs

Impact metrics with BigQuery

Time to Insight
No staging required
GA4, POS, and CRM datasets queried in place.
Marketing Attribution
Online-offline linked
GA4 events joined with in-store POS to close attribution gaps.
Data Activation
Historical data unlocked
Years of unqueried BigQuery data brought into analysis.
Anomaly Detection Speed
Always-on monitoring
Deviations caught between scheduled dashboard reviews.

Data lake enrichment

Ward enriches BigQuery data with: Any BigQuery dataset, GA4 event exports, Weather & events, Demographics, Custom feeds

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 · Customer06:47 AM

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

✓ Action recommendedBigQuery data

Frequently asked questions

Service account with BigQuery Data Viewer role. Ward runs read-only SQL queries on your schedule. Data points include: Any BigQuery dataset, GA4 event exports, Ads data transfers, Custom ETL outputs.

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
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Customer acquisition lift for data‑driven orgs
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Foundation models shipped since 2022
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Guarantees any single model stays on top

See what customer 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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