Machine Learning-enhanced Reranking
Search results rankings that drive purchases
Krestor Search uses machine learning (ML), behavioral data and your business goals to drive conversions and revenue. In controlled production A/B tests, Krestor’s automated and data-driven approach to results ranking repeatedly drove more search-related revenue and more customer checkouts. In other words, both site owners and customers succeed with Krestor Search’s ML-enhanced reranking.
Users expect magic from search. Are you giving it to them?
… not if your site search relies on ordinary search technology and out-of-the-box keyword ranking algorithms. Creating measurable improvements in revenue and customer satisfaction requires more than adding a few new features to an outdated foundation. It requires the integrated and data-driven approach found in Krestor Search.
ML-ENHANCED RERANKING AT WORK
ML Is Revolutionizing Results Ranking
When behavioral data and machine learning algorithms inform search results ranking, both users and site owners see improved outcomes.
That’s exactly what tech giants Google, Microsoft, Netflix and others are doing to improve search experiences on their sites. What’s more their machine learning investments are driving business outcomes including increases in conversions, revenue and customer loyalty.
Machine learning is at the core of Krestor Search. It continuously learns from an expanded set of data, including customer behavior, product catalogs, product-related metadata, price changes and purchases. And it immediately applies those learnings to improve results ranking.
ML-enhanced reranking algorithms
Krestor utilizes automated, and computationally sophisticated algorithms to improve results rankings in real time.
Behavioral Data
Krestor Search tracks behavioral data to improve and personalize search results. Query terms—and the related counts of click-throughs, conversions and purchases—are all used to improve future search outcomes.
Merchant-centric optimizations
Site owners can tune search optimization parameters to their business goals. For example, search results may be tuned to maximize revenue, conversions, loyalty, average order value or a combination of factors.
Automated boost
Algorithms improve results ranking for products based on historical conversion frequency data.
Automated bury
Algorithms diminish results ranking for products based on historical conversion frequency data.
Relevance-weighted search facets
Refine search results based on attributes such as manufacturer, color and price. Search facets are displayed in conversion-optimized order.
In-session ranking improvements
Algorithms use behavioral data to improve current sessions in real time. Behavioral data is processed in real time without any offline or batch processing.
The automation advantage
The benefits begin with improved search experiences and measurable revenue growth. But there is more. Krestor Search lets you focus on improving your core business: creating customers, driving online sales, and improving customer experiences.
ML-enhanced reranking works along with natural language processing, collaborative personalization and merchant controls to provide an automated solution that improves conversions, revenue and customer loyalty.
Don’t just trust us. Make us prove it.
Let us quantify the value of Krestor’s ML-backed search and discovery on your site using your data. No contract required.
