Customer Behavior + Oracle: Built for Head of LP
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 Loss Prevention team has the data. What they don't have is bandwidth to find what's buried in it.
Customer Behavior powered by Oracle Retail
Customer Behavior is the process of ward tracks basket composition shifts, daypart patterns, and customer segment migration.
When connected to Oracle Retail, Ward reads sales audit, inventory positions, allocation and enriches them with contextual signals to generate customer insight cards. Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.
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
How Ward connects to Oracle Retail
Ward integrates with Oracle Retail Merchandising (RMFCS), Oracle Retail Demand Forecasting, and Oracle Retail Analytics. Full stack visibility.
Setup: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.
Data Ward reads from Oracle
Impact metrics with Oracle
Data lake enrichment
Ward enriches Oracle data with: Sales audit data, Weather & events, Competitor pricing, Demographic data, Supplier scorecards
Shrinkage costs you more than you think. Ward finds out where.
- ×Shrinkage is a year-end surprise, not a weekly metric
- ×Cannot distinguish theft from spoilage from admin error
- ×High-shrinkage stores only identified during audits
- ×No correlation between operational changes and loss patterns
- ×Exception-based reporting misses slow-bleed patterns
- ✓Store-level shrinkage tracking with cause attribution
- ✓Anomaly detection flags stores deviating from estate average
- ✓Receiving dock discrepancy patterns identified automatically
- ✓Correlation analysis links operational changes to loss shifts
- ✓Trend analysis catches slow-bleed patterns audits miss
US retail shrinkage hit $112.1 billion in 2022 — up 19.4% year over year. — National Retail Federation
What a Ward insight card looks like
Evening shoppers (6-9 PM) adding 22% more ready-to-eat items vs last quarter. Deli adjacency planogram opportunity identified.
Frequently asked questions
Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments. Data points include: Sales audit, Inventory positions, Allocation, Replenishment, Demand forecasts, Price management.
Shrinkage costs you more than you think. Ward finds out where. Ward solves this with automated insight cards: Store-level shrinkage tracking with cause attribution. Anomaly detection flags stores deviating from estate average. Receiving dock discrepancy patterns identified automatically.
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.
Related solutions
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.
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.
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.
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.
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.
See what customer problems Ward catches.
Root causes, not just alerts. See it on your data.
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.