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AI Recommendation
Product recommendation engine
Recommend the right products without losing commercial control
Use customer behavior, product data, and business rules to show relevant product recommendations across your digital touchpoints.
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Suggestions shaped by catalog and affinity rules.
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Controlled recommendations for the next journey step.
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Workflow
Turn product data into recommendation rules your team can trust
AI Recommendation is designed for companies that want personalization without handing every decision to a black box.
Catalog
Connect product data
Use product, stock, category, price, and campaign information as the recommendation base.
Behavior
Read customer signals
Evaluate views, clicks, carts, purchases, and browsing patterns to understand intent.
Rules
Apply business logic
Keep exclusions, priorities, stock rules, and campaign limits in the decision layer.
Publish
Show recommendations
Serve relevant products on website areas, campaigns, and other customer-facing surfaces.
Capabilities
Recommendation logic built for daily commercial work
The value is not only that products are recommended. It is that your team can guide what should, and should not, be recommended.
Personalization
Behavior-based product picks
Use customer actions to recommend products that are more likely to be relevant in the next step.
Commerce
Stock and category awareness
Avoid recommending unavailable items and keep category logic aligned with current priorities.
Campaigns
Promotion-sensitive logic
Bring campaign tags and selected product groups into recommendation decisions.
Controls
Exclusion rules
Block restricted, low-margin, seasonal, or operationally sensitive products when needed.
Testing
Scenario checks
Review recommendation behavior before expanding it into more visible customer journeys.
Reports
Visible performance
Follow recommendation activity with clear reporting, not assumptions about what AI is doing.
Governance
AI that works inside your commercial boundaries
Recommendation systems become useful when the business rules are visible. AI Recommendation helps teams combine data-driven suggestions with the practical constraints every company has.
✓
Approved product pools
Choose which product groups can enter recommendation logic.
✓
Operational guardrails
Keep stock, availability, margin, and campaign limits in view.
✓
Readable decisions
Understand why a product is being recommended before scaling the placement.
About AI Recommendation
WDC AI Recommendation helps companies present more relevant products by combining customer behavior, product information, and controlled business rules.
It can support product discovery, cross-sell areas, campaign placements, category journeys, and personalized website modules. The goal is to make product selection feel more useful for the visitor while keeping the commercial logic understandable for your team.
The platform is intentionally careful about AI language. It does not need to promise automatic growth to be valuable. Its strength is helping teams turn large product catalogs and customer signals into repeatable recommendation decisions.
- For marketing teamsUse recommendations to support campaigns and product discovery.
- For ecommerce teamsBring stock, category, and product priority into customer journeys.
- For decision makersKeep AI-driven personalization measurable, controlled, and easier to explain.