E-Commerce Search Using Open Source

If you use Elasticsearch, OpenSearch or Solr to power your E-commerce, we can help.

Search applications are an essential component of E-commerce websites. They allow customers to find the products they are looking for quickly and easily, improving the overall buyer experience. The goal is not just to complete a buying transaction, but to drive customer satisfaction and return business.

Solr and Elasticsearch are popular open-source search engines for search applications. OpenSearch is also an option. Pureinsights has deep expertise in helping companies leverage open source to deliver e-commerce search experiences that delight customers and drive revenues.

Ecommerce search with open source
"The mission of e-commerce search is to help customers find what they want, so they engage, leave satisfied, and most importantly, return."
Phil Lewis
Phil Lewis
CTO, Pureinsights
“Our business depends on our search capability and Pureinsights provides unique search expertise and technology that allows us to focus on our business.“
Ben Hirsch
CTO and Co-Founder, Locally.com

Address technical challenges of Open-Source E-Commerce search

Solr and Elasticsearch are popular open-source search engines that have gained a lot of popularity in the e-commerce industry due to their powerful search capabilities. OpenSearch, a derivative of Elasticsearch, is also available. However, implementing and maintaining these search engines for e-commerce search can pose several challenges.

One major challenge is the management of product data. E-commerce websites have a vast amount of product data that needs to be indexed and queried in real-time. This can be a daunting task for Solr or Elasticsearch, especially when dealing with large and complex product catalogs. Managing product metadata to optimize search can also be a time-consuming and error-prone process.

Another challenge is maintaining relevance in search results. E-commerce search engines must deliver relevant search results that meet the user’s intent, even when dealing with complex queries that involve multiple product attributes. This requires the use of advanced search techniques like faceted search, fuzzy matching, and relevance scoring. However, fine-tuning relevance can be a complex process that requires a lot of experimentation and optimization.

Scalability is also a significant challenge in e-commerce search. As the number of products and users grow, the search engine must be able to handle increasing traffic without compromising performance. This requires the use of distributed search architecture and load balancing techniques, which can be complicated to set up and manage.

Finally, e-commerce search engines must be integrated with other e-commerce systems like product information management, order management, and customer relationship management systems. This can be a challenging task, especially when dealing with multiple systems that use different data formats and protocols.

So while Solr, Elasticsearch and OpenSearch are powerful search engines for e-commerce search, their implementation and maintenance can pose significant challenges. Addressing these challenges requires a deep understanding of e-commerce data, search algorithms, and system architecture.

Drive business with better E-commerce Search

Solr and Elasticsearch are both based on the Lucene search engine library, but they have their differences. Solr is a search platform built on top of Lucene, while Elasticsearch is a distributed search and analytics engine. OpenSearch is a derivative of Elasticsearch based on the Apache license. All three are fast, scalable, and highly customizable, making them ideal for powering search applications.

One of the primary goals of search applications is to improve the buyer experience. By providing relevant search results and intuitive filters, customers can quickly find the products they are looking for. This not only improves their experience on the website but also increases the likelihood of them making a purchase. Solr, Elasticsearch, and OpenSearch provide advanced search capabilities such as autocomplete, faceting, and geospatial search, all of which can be used to enhance the buyer experience.

Another goal of e-commerce search applications is to encourage customer loyalty. By providing a personalized and efficient search experience, customers are more likely to return to the website for future purchases. Search engines can be customized to provide personalized search results based on user behavior and preferences. This can increase customer loyalty by providing a unique and tailored experience for each customer.

Optimizing revenues is another important goal of search applications. By improving the search experience, customers are more likely to find the products they are looking for, increasing the likelihood of them making a purchase. Solr, Elasticsearch, and OpenSearch can be used to provide relevant search results based on user behavior and preferences, making it easier for customers to find the products they want to buy.

Increasing conversion rates and repeat business are also key goals of search applications. By providing a fast and intuitive search experience, customers are more likely to complete their purchases and return for future purchases. Solr and Elasticsearch can be used to provide real-time search results and fast autocomplete functionality, making it easier for customers to find what they are looking for and complete their purchases.

By leveraging the advanced search capabilities provided by these open-source search engines, e-commerce websites can provide a personalized and efficient search experience that drives business growth. Addressing the technical challenges and achieving the desired business results requires an experienced, methodical approach.

Pureinsights E-Commerce Search Solutions

Pureinsights E-Commerce Search solutions combine expertise and technology to help you achieve your business goals.

E-commerce search open source solution approach

Search engine independent

We enter each engagement without any bias towards any search engine, commercial or open source.  We keep the customer’s best interest in mind and let technical and business requirements drive the decision on which search engine to use.

Search application assessment

We usually recommend getting started with a Search Application Assessment, which is brief paid engagement where we perform a deep analysis of your current situation and develop a roadmap to get you from your current to your desired state with your e-commerce website search.

Search maturity matrix

In the assessment, we usually use our Search Maturity Matrix to map out what features you have currently implemented, and which search features might enhance your results, balanced against the difficulty of implementation.

Search Feature Maturity Matrix for E-Commerce Search

Relevance tuning and Search Relevance Dashboard

In addition to features implementation, e-commerce search on your website may benefit from Search Relevance Tuning and Search Engine Scoring, where we analyze log data to optimize the search relevance results for your customers.  The results can also be objectively measured and monitored with our Search Relevance Dashboard.

Search Relevance Dashboard

Continuous search improvement process

We can help you implement a process by which you can continuously monitor results and improve search relevance results to ensure that your website revenues are being maximized through the busy retail season and year-round.

Search personalization / recommendations

Pureinsights can review and help you improve the implementation of any personalization or recommendation engines for your e-commerce website search.  This is critical to ensure a high-degree user satisfaction, a higher conversion rate, and return business.  It can also be a tremendous competitive advantage – the more your users buy, the mor information you have on their buying preferences. 

AI-Powered platform

The best e-commerce websites today are now all leveraging AI and machine learning throughout their search applications. The Pureinsights Discovery Platform™ (PDP)  complements your existing e-commerce platform and preferred open-source search engine with the latest cloud-based AI services. PDP’s content processing capabilities can improve your product catalog metadata and greatly improve search relevance. The platform can also be used to implement question-and-answer capabilities to provide a better customer experience, whether they are shopping for products, or looking for support on your website.

Start Now and be ready for the next Retail Season

Contact Us for a free 1:1 initial consultation, or to learn more about how Pureinsights can help you with your E-commerce search applications so you can be ready before the start of the next major retail season.