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NLP-Powered Search Optimization
GraingerChicago, IL, US2016 - 2017Product Manager
Overview
Led product strategy for "Search and Select" functionality on Grainger's B2B/B2C e-commerce platform serving 1.5M products. Drove SEO/SEM optimization and search engine development.
Key Outcomes
$170M
Revenue increase from organic search
7%
Organic traffic growth
14%
Boost in featured SKU sales
23%
Improvement in search satisfaction
The Challenge
Poor product discovery and low search relevance were impacting sales. The existing search couldn't understand user intent, and high-value SKUs weren't being promoted effectively.
My Approach
- Implemented NLP-powered search optimization using Inbenta
- Conceptualized and implemented Java-based product boosting algorithm
- Coordinated with business teams to optimize Solr search engine
- Used Adobe Analytics data for intelligent product ranking
- Initiated Endeca to Solr migration feasibility analysis
Technologies & Tools
SolrEndecaInbenta NLPAdobe AnalyticsJava
Key Learnings
Search optimization has direct revenue impact in e-commerce. NLP can significantly improve user intent understanding. Data-driven product boosting creates compounding returns.
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