Search relevancy guides for WordPress & WooCommerce

PostgreSQL can explain complex queries like vector reranked with BM25 RRF

Vector search with BM25 reranking (RRF – Reciprocal Rank Fusion), filters, and facets can become complex very quickly: * You’re combining multiple rankings (e.g., BM25 + vector similarity). * You’re applying post-filtering or pre-filtering (categories, availability, dates, etc.). * You’re computing facets/aggregations on top of already-ranked results. * And sometimes you’re adding re-sorting (e.g., by date or popularity after relevance). That’s where PostgreSQL really shines. With `EXPLAIN (ANALYZE, BUFFERS)` you can: * See whether your vector index (IVFFlat / HNSW) is actually used. * Check if filters are applied before or after similarity search. * Detect expensive bitmap heap scans or unnecessary sequential scans. * Measure the real cost of CTEs vs. subqueries. * Understand how RRF is materialized (temporary sort, window function, hash aggregation).

Provide better search and generative AI experiences with Vertex AI Search

Vertex AI search is (finally) catching up with advanced RAG features like VLM document parsing, chunking, citations, re-ranking, grounding generation/verification. As usual, you will have to choose between an all-in-one closed-source monolytic solution like this or aggregating the best open-source solutions. But this now looks, at least on paper, like a solid RAG/search solution with the key advantage of being serverless and scalable end-to-end. Similar to the new features of Amazon Bedrock knowledge bases https://aws.amazon.com/bedrock/knowledge-bases/. It is not easy to clone this with disparate components without investing time and money. Contact us if you want to build a RAG in your WordPress.

WordPress search : Ultimate Guide

WordPress is the most widely used CMS and single handedly powers 40% of the web. If you haven’t tried it already, it is intuitive, powerful and if you use one of many hosting providers out there, you can easily set up a working website in minutes. But once you made all of your content, how do you ensure that your users can find it. For that, you need a good site search. Many types of search exist : keyword search, AI search, even personalized search. WordPress provides one by default, but it is incredibly slow and ineffective. This guide will go over the benefits of a fast and relevant search and how you could implement third party search engines easily into any WordPress or Woocommerce

Must, Must_Not, Should : Boolean operators in search engines don’t work how you think they do

Concepts The traditional boolean operators are AND or NOT are very effective when programming or doing SQL requests but are not as good for search relevancy. The Apache Lucene library has it’s own boolean operators : Must, Must_Not, Should. The must boolean operator in a query means that only the documents that contain the specified keyword(s) will be returned, the must_not boolean operator in the query means that all the documents containing the specified keyword(s) will not be returned while the should operator means that the documents that contain at least one of the specified keyword(s) will be returned. Must is represented by the character +, Must_Not by the character – and Should by no character. So , the query “+dog -cat lazy” means

How do search engines use inverted indexes?

How are inverted indexes used ? Have you ever wondered how search engines and libraries like Lucene, Solr and Elasticsearch work? They use inverted indexes which are faster and more efficient than forward indexes since the document database doesn’t need to perform a full table scan. They are a fundamental component of keyword search. Almost every software that does Information Retrieval uses some kind of inverted index since you don’t go through a list of documents hoping to find the match, you go through a list of documents that you already know contains the match. How do inverted indexes work ? Indexation works in a few steps : The data received is tokenized : it simplifies each word of

The default WordPress search is losing you money, Algolia explains you how

How does the default WordPress search works ? Learn how the default WordPress search works. Why it’s making lose money It works by sending a basic SQL query to the WordPress database that is wildly inefficient and imprecise which, according to Algolia, could be losing you money. ???? By reading this article, you’ll learn that 43% of visitors immediately go to the search bars when opening a website and shoppers that use search bars spend 2.6 times more than others. Conclusion ???? So it is important that you use a highly performant and relevant search engine for your website since the more data you have, the more the WordPress default search will struggle. If you are interested in equipping your website with an efficient search, check

Quepid : Improve your search relevancy with this simple tool

Have you have installed your search engine like Elasticsearch, Opensearch or Apache Solr but found the results unsatisfying. It seems just setting up your search is not enough, you could optimize it using OpenSource Connections’s Quepid search relevancy toolkit (https://quepid.com/). Well in the following video, Eric Pugh explains how you can use Quepid to improve your search: https://www.youtube.com/watch?v=sazrBME353M. How it works : – Let the client or whoever understands in detail the contents of the website define key queries and rate each one of the returned results. – Use the different algorithms in Quepid to give a score to each one of the queries so that the search relevancy expert can understand which ones needs work. The simple metric allows anyone (even those that don’t understand the subject)

How to troubleshoot Elasticsearch

Introduction Elasticsearch is a powerful distributed search and analytics engine that is widely used for storing, searching, and analyzing large volumes of data. However, like any other technology, Elasticsearch can encounter issues and require troubleshooting to ensure optimal performance. In this post, we will explore some common troubleshooting techniques when working with Elasticsearch. Troubleshooting Elasticsearch 1. Check Elasticsearch Cluster Status: The first step in troubleshooting Elasticsearch is to check the cluster status. You can use the Elasticsearch PHP client library to query the cluster health and obtain information about individual nodes, indices, and their status. Here’s an example of how you can use the PHP client to obtain the cluster health: require 'vendor/autoload.php'; $client = Elasticsearch\ClientBuilder::create()->build(); $response = $client->cluster()->health(); // Check the cluster status

How Algolia contributes to the SEO of your WooCommerce store

Introduction In the world of eCommerce, search engine optimization (SEO) plays a vital role in driving traffic and increasing visibility for online stores. WooCommerce, being one of the most popular eCommerce platforms, understands the significance of SEO and offers various tools and plugins to optimize online stores. One such tool is Algolia, a powerful search and discovery platform that can significantly enhance the SEO of your WooCommerce store. In this post, we will explore how Algolia contributes to the SEO of your WooCommerce store and how it can be integrated using PHP client. Introduction to Algolia Algolia provides a search-as-you-type experience for your WooCommerce store, enabling customers to find products quickly and effortlessly. Its sophisticated algorithms and instant search capabilities make it a popular

Boosting search results with Apache Solr

Introduction Boosting search results is a crucial aspect when it comes to improving the overall search experience for users. When users search for specific terms or phrases, it is often desirable to have certain results rank higher than others based on various criteria. Apache Solr is a powerful and versatile search platform that offers advanced search capabilities, including boosting search results. Apache Solr enables developers to create custom ranking rules to influence the order in which search results are displayed. This allows for more relevant and accurate search results, ultimately enhancing the user experience. In this post, we will explore how to boost search results with Apache Solr, and we will also touch on how WPSOLR, a WordPress plugin, can help simplify the process. Boosting

Implementing custom ranking in Elasticsearch for WooCommerce

Introduction Elasticsearch is a powerful open-source search engine that can be used with many different applications. WooCommerce is one such application and is known as one of the most popular eCommerce platforms. By default, WooCommerce uses a relevance ranking system to sort the search results. However, sometimes businesses require different ranking systems, and hence, being able to implement a custom ranking system within Elasticsearch can be highly advantageous. In this post, we will discuss how you can implement custom ranking in Elasticsearch for WooCommerce with PHP client. We will also talk about how WPSOLR, a popular WordPress plugin, can help with that. Implementing Custom Ranking in Elasticsearch for WooCommerce To implement a custom ranking in Elasticsearch for WooCommerce, we need to understand how Elasticsearch handles

The benefits of using Elasticsearch for catalog management in WooCommerce

Introduction In recent times, e-commerce has become one of the most reliable and widespread methods of buying and selling products. WooCommerce is an excellent platform that allows businesses to create online stores easily. However, managing a vast catalog of products can be a daunting task. That’s where Elasticsearch comes in. Elasticsearch is an open-source search engine built on top of the Apache Lucene library. It is fast, scalable, and designed to handle large amounts of data. In this post, we’ll explore the benefits of using Elasticsearch for catalog management in WooCommerce and how you can implement it using the PHP client. Benefits of Using Elasticsearch for Catalog Management in WooCommerce 1. Faster Search Results: Elasticsearch is built to handle large volumes of data, and it

How Relevanssi works compared to the default WordPress search?

Since forever, websites have offered search functionalites to help their users find the content they need. It is no different for WordPress websites. A good WordPress search is invaluable since it increases user engagement and reduces frustration. Well WordPress offers a default search. But is it a good idea to use it? Well apparently not enough since Relevanssi exists. Relevanssi is a WordPress search plugin that replaces the default search with a more refined and efficient one. If you want to learn about more WordPress search plugins, you could check out our list. Which features does Relevanssi add ? Index any WordPress data type The default WordPress search doesn’t offer configuration options, even choosing which data is searchable is not possible. This type of

Exploring the Role of AI in Enhancing Search Engine Efficiency

Introduction Search engines have become an integral part of our daily lives, assisting us in finding relevant information from the vast sea of data available on the internet. Over the years, advancements in artificial intelligence (AI) have played a crucial role in enhancing search engine efficiency. AI-powered techniques, such as LLMs (large language models), vector search, and advanced algorithms, have revolutionized the way search engines retrieve and rank information. In this article, we will explore the role of AI in enhancing search engine efficiency and highlight some cutting-edge technologies like Weaviate, Pinecone, Vespa, Elasticsearch, Solr, and Algolia. Additionally, we will discuss how AI has rendered previous search tricks unnecessary and has opened up new possibilities for multi-language search capabilities. Enhancing Search Efficiency with AI