Poor personalization is painfully obvious. Shoppers expect quality individualized experiences from type ahead to search and browse pages, to recommendations and content. Collect signals from site, store, and any other channel and apply those insights to the product discovery journey online. Predict the next click to accelerate the path to purchase and increase AOV.
Lucidworks applies advanced algorithms like semantic dense vector search to retrieve highly relevant products your shoppers are more likely to add to cart. Designed specifically for ecommerce catalogs, these advanced search methodologies understand intent and surface the right items even if shoppers search for the wrong product name.
Looking to plug in your data science team to deliver additional sophistication to the search platform? The Data Science Toolkit will empower your data science team to experiment, explore and build models that deliver the specific results and metrics you’re looking to improve.
Search and merchandising strategies are forever iterating. Before committing changes along this journey, use experiments to easily run multivariate tests and be confident in the changes made before they are rolled out to production.
Leverage our pre-tuned machine learning jobs and easily approve suggestions for low-performing queries. Empower your search and merchandising teams to get back to tackling larger initiatives that optimize your product discovery experiences.
Type-ahead suggestions are traditionally based on matching partial or complete query terms to popular searches, categories, and products. Use Semantic Vector Search to locate high performing queries and products that are nearby in the shared vector space. This powers a higher-converting experience that goes beyond understanding intent.
Drowning in thousands of rules to manage facets and facet values across the site? Operationalize your facet strategy with machine learning. Get the right facets in front of your shoppers to encourage engagement and accelerate their path to purchase.
With ML, facets will rerank based on parameters and contexts important to your business. Apply this strategy across the site and focus on the few pages that benefit from your teams’ expertise.
Las Vegas travel search engine Vegas.com increased page views and engagement by 63% . Bounce rates for the mobile site dropped 8%. Conversion rates from search to a reservation or ticket increased by 33%. The team has since built the desktop search experience with Fusion as well. Full case study…
The American sportswear and footwear retailer put Lucidworks to work and saw a 10% lift in add-to-cart, improved personalization, and better analytics to drive merchandising decisions for promotional events.