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Elasticsearch for E-Commerce

elasticsearch for e-commerceElasticsearch has the core features required for building powerful search applications, ranging from intranet to e-commerce site search. Using Elasticsearch for e-commerce sites can enable a high level of relevancy, flexibility, and specific search features that support retention and conversion.

For instance, Elasticsearch can be configured to provide key e-commerce site search features, such as auto-suggestions (or type-ahead, autocomplete, query suggestions), spell correctionsynonymsfaceted searchresults paginationprice ranges, and more. But similar to many open source solutions, it requires tuning and appropriate setup in order to fulfill your business goals and user expectations. 


Search Technologies provides consulting, implementation, support, and complementary technologies to address specific e-commerce challenges, so you can maximize revenue from site search activities.

  • Replatforming – if you are thinking of migrating your current site search platform to Elasticsearch, we can assess your needs and system performance in order to recommend and implement the most appropriate migration approach (e.g. Endeca to Elasticsearch, Solr to Elasticsearch, SAP Hybris to Elasticsearch, SLI Sytems to Elasticsearch, etc.).
  • Search quality analysis - a Search Quality Analyst specializes in evaluating users' search queries and providing suggestions for a user-centric search experience. This bridges your product catalog's vocabulary and the buyer's intent.
  • Content processing - product catalogs often have little metadata or are not properly indexed by the search engine. We apply an automated content processing pipeline to extract, normalize, and enrich your metadata before indexing to the search engine. 
  • Search engine scoring – a proven methodology for measuring and improving your search engine based on statistical scores.
  • Scaling Elasticsearch - we are experienced in helping customers scale their search applications up to billions of documents.
  • Search results personalization - Elasticsearch can be combined with big data technologies like Hadoop to build a truly personalized search experience for your users. A common use case is log analytics, in which the Elastic Stack (Elasticsearch, Logstash, Kibana, and Beats) is used to analyze queries and personalize results. Read our case study on how a large retailer improved conversion rate with the Elastic Stack.


Our 200+ consultants are well-versed in search engines, content processing best practices, and big data techniques. Over the years, we've helped many large and small e-commerce companies improve their revenues by delivering the best-of-class search experience. View our case studies here.

In addition to leveraging Elasticsearch for e-commerce search applications, we work with a wide range of open source and commercial e-commerce search solutions, including SolrEndeca, the Google Search ApplianceCloudSearch, and others.

Contact us to see how we can help improve your Elasticsearch site search for higher e-commerce conversion rate.