Connect Shopify with Klevu to power AI-led site search and merchandising with natural language queries, synonym rules, and product recommendations that improve product discovery and sales.
• Shopify product data (titles, descriptions, SKUs, barcodes, images, collections, tags, price, and availability) is mapped to Klevu’s catalog schema for indexing.
• Catalog updates are processed as incremental syncs so only changed products, variants, prices, or stock states are re-sent and re-indexed.
• Customer search queries, clicks, add-to-carts, and purchases are captured as events and routed to Klevu to train relevance and power conversion-focused ranking signals.
• Search terms and natural language phrases are resolved through Klevu dictionaries where synonyms, redirects, and zero-result handling rules are applied before results are returned.
• Merchandising rules (boost, bury, pin, and campaign-driven promotions) are evaluated at query time, with filters and facets derived from Shopify attributes and tags.
• Product recommendations use indexed catalog data plus behavioral signals, returning ranked product IDs that Shopify renders in search results, PDP, cart, or category modules.
• Sync and query operations are logged, with validation for required fields and fallbacks for missing attributes to prevent empty or broken result sets.
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We sync your Shopify catalog to Klevu, configure search relevance, synonyms, and merchandising rules, then validate results with real queries before go-live.
At minimum, send titles, SKUs, variants, prices, inventory, collections, and attributes, plus search, click, add-to-cart, and purchase events for learning and recommendations.
Yes, Klevu can be set up per Shopify store or market, with language-specific synonyms and rules to keep results relevant across locales.
Synonyms catch the way people actually type, while rules let you pin, boost, or demote products and categories to match campaigns, margins, and stock.
Most launches take weeks, depending on catalog complexity, theme customization, and event tracking readiness; the biggest delays are data quality and unclear attribute mapping.









