Context-aware recommendations
Context-aware recommendations adapt to the live conversation and a shopper’s stated intent, instead of relying only on static rules or past purchase history.
What it means
Rule-based personalization fires the same suggestions from fixed conditions — ‘customers who bought X.’ Context-aware recommendations read what the shopper is telling you right now — the occasion, the constraint, the person they’re buying for, and adjust in the moment.
Why it converts
Relevance is highest when a recommendation reflects the shopper’s actual situation. Grounded in your catalog and the current dialogue, context-aware suggestions feel like advice rather than a merchandising slot.
A shopper says “it’s a gift, she likes minimal jewelry” and the recommendations shift immediately to understated pieces in budget.
MerchantIQ adapts recommendations to live conversations and shopper intent, not just static business rules, while staying grounded in your products.
Context-aware recommendations, in brief.
How is this different from rule-based personalization?
Rule-based personalization uses fixed conditions and history. Context-aware recommendations respond to the shopper’s current, stated intent and adjust as the conversation evolves.
Does it ignore business rules?
No. It works within your rules and catalog — context makes the suggestions sharper, it doesn’t override your controls.
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