Most WooCommerce "related products" are little more than products from the same category. They ignore attributes, brands, pricing, and how shoppers actually compare products.
Get Recommendor uses a custom-trained machine learning model for every product, helping customers discover alternatives that genuinely match what they're looking for.
Every recommendation is ranked using multiple product signals instead of relying on a single rule.
Products sharing categories, subcategories, and tags receive higher relevance scores, ensuring recommendations remain contextually accurate.
Attributes such as color, size, material, style, compatibility, or specifications are analyzed to surface products with meaningful similarities.
Customers often trust brands they already know. Products from the same brand receive an additional relevance boost while still competing with better overall matches.
Price heavily influences buying decisions. Products with similar price points are prioritized while large pricing gaps receive lower scores, avoiding unrealistic recommendations.
Unlike generic recommendation engines, Get Recommendor trains a machine learning model using your store's own catalog and shopping behavior.
Categories, attributes, brands, pricing, clicks, carts, and purchase patterns help the model understand which products customers are most likely to explore next.
As your store grows, the model is periodically retrained to keep recommendations accurate and relevant.
Every signal contributes to a final relevance score. Instead of requiring an exact match, Get Recommendor's model evaluates the complete product profile to determine which products deserve the highest ranking.
Whether your store has hundreds of products or hundreds of thousands, recommendations remain fast. Visitors always receive fast recommendations without slowing down your storefront.
Showing genuinely relevant alternatives helps customers make purchasing decisions faster. Instead of leaving your store to compare products elsewhere, customers continue exploring your catalog.
A customer is viewing Men's Trail Running Shoes – Storm Grey. Get Recommendor may rank products like these:
Recommendations appear naturally without exposing technical relevance scores to shoppers.
Simply activate the feature and Get Recommendor automatically displays Similar Products on every product page.
Prefer complete control? Display recommendations anywhere using a shortcode.
[reco type="similar" limit="8"] [reco type="similar" product_id="123" limit="6"]
Control everything directly from the WooCommerce dashboard. No coding required.
Get Recommendor combines machine learning with intelligent caching to deliver fast recommendations without expensive computation on your WooCommerce server.
Your store securely sends aggregated shopping signals to our AI platform, where a recommendation model is trained specifically for your catalog. When recommendations are needed, the plugin retrieves them through our optimized API and caches the results for future visitors.
Recommendation requests are lightweight and cached locally by the plugin. Most visitors receive cached recommendations, keeping page loads fast.
Yes. Set a global default or override it using the shortcode.
Get Recommendor automatically expands its search criteria to find the closest available matches while maintaining relevance.
Yes. Parent products, variations, attributes, brands, categories, and pricing are all considered when calculating relevance.
Every product page becomes another opportunity to keep shoppers engaged. Smarter recommendations. Better shopping experiences. Higher conversions.