Additionally, YesPlz AI includes automated keyword management, acting as a co-pilot for eCommerce managers. This feature dynamically updates and optimizes product tags and filters, eliminating manual work and ensuring that search results stay current with the latest trends and shopper preferences.

We typically recommend sorting results by popularity, which reflects your shoppers’ intent. However, you can customize various parameters—such as brand, price, new arrivals, and even size—at each category level. Our user-friendly search console makes it easy to calibrate these settings, and we support you to fine-tune relevance perfectly for your shoppers. Contact sales to see the live demo at hello@yesplz.ai

Hybrid search in fashion eCommerce refers to search engines that combine multiple technologies—advanced text search, semantic search, vector search, and image-based tagging—to deliver highly relevant shopping results. These systems understand both keywords and context, making product discovery faster and more accurate for modern style queries.

The best eCommerce search platform for fashion is one trained on fashion data — not a generic engine with fashion keywords bolted on. Generic platforms like Algolia and Shopify's native search treat a query like "cottagecore dress" as text to match; a fashion-native engine reads it as a style, an occasion, and a silhouette. YesPlz combines keyword, visual, and fashion-tagging search in a single hybrid engine built specifically for apparel catalogs. When Looxloo replaced its previous engine with YesPlz, search accuracy rose from 82% to 95% — and W Concept's search-to-cart rate hit 5x the industry benchmark.

Algolia alternatives fall into three groups: general-purpose engines (Constructor, Searchspring, Klevu), Shopify-native apps (Boost AI Search, Fast Simon), and vertical platforms built for a single industry. For fashion retailers, vertical is the group that matters — queries like "beach wedding guest dress" depend on occasion, style, and silhouette data that general-purpose engines don't model. YesPlz is the fashion-native alternative: instead of keyword matching with add-ons, it runs hybrid search combining text, fashion image embeddings, and automated fashion tagging. When fashion retailer Zilo switched from Algolia and A/B tested the two, search revenue rose 16% and zero-result searches dropped from 13% to 3%. A general engine fits a general catalog; a fashion catalog needs an engine trained on fashion.

It’s simple. Retailers can integrate either our search widget or API. Our AI then automatically analyzes the entire product catalog to enable hybrid search. Additionally, our team customizes your category structure into intuitive search filters, allowing shoppers to easily find precisely what they want. Typical integration time takes 1-2 weeks.

Our customers see a +15% boost in search accuracy, 3-4x higher add-to-cart rates compared to the industry average, and a 1.5-2x increase in search-driven sales attribution.

We offer flexible pricing based on your SKU count and traffic volume. Contact our sales team for a personalized quote at hello@yesplz.ai.

Glad you asked! We provide detailed analytics on site search performance, including basic click-through and conversion rates. Plus, our unique keyword funnel tracks popular search terms and optimizes results by matching actual shopper intent. All done automatically, but you can always track the progress.