AI recommender guides for WordPress & WooCommerce

The most advanced related posts plugin for WordPress

WordPress is the world’s leading solution when it comes to website creation. It is first and foremost a blog CMS so what if you wanted to link posts or any other types of products together to not only improve your SEO but also guide your users, thus greatly increasing user satisfaction? WPSolr can help with that. WPSolr offers a recommendation plugin that uses AI to accurately suggest related posts (and products if you have Woocommerce installed). Why have related posts (recommendations) for your WordPress Most popular websites offer some form of recommendations to the users. They are an automated technology designed to suggest content that is in some way related to what the user is currently viewing. This technology can seem very similar to

Algolia recommendations guide

Algolia is one of the leading providers of search and recommendation solutions, with a significant market share in the industry. So considering using Algolia to power your website’s search & recommendations is a no brainer. Why use AI recommendations ? AI recommendation models are trained on user interactions or clicks to recommend the most relevant products or items for each user. You can usually find them in e-commerce websites, at the bottom of products detailed view or in the homepage. But they can also be found on streaming websites (movie and music) or services, news and many other industries. Algolia AI recommendations in Gymshark Recommendations are useful since they can increase user engagement and drive conversions. Since users are continously

Integrate Woocommerce with Algolia

Algolia is the most popular cloud search & recommendations provider. You could want to integrate it into your Woocommerce or WordPress website. Why use Algolia ? Search Algolia provides search of all kinds : simple keyword search, AI/vector search & personalized search. Keyword search is available in the free tier. Keyword search works by matching the keywords in a search query to the ones present in the indexed items/documents. It can be simple and limited without any configuration but Algolia offers multiple features to fine-tune it. For keyword search, you could define synonyms which is useful for expert websites. For example, if you have a medical website, you could need to set “acute myocardial infarction” as a synonym for heart attack.

Recombee vs Algolia pricing

Algolia and Recombee both offer similar functionalities : search and recommendations. Which solution you should go for would depend on your use case : Overall Overall, Recombee offers a better price to performance ratio compared to Algolia. It’s free tier includes personalized search and recommendations with almost all features available (models optimized for general purposes, e-commerce, streaming, ads, etc…) and very generous usage limits (100 000 recommendation requests per month, etc…) which is more than enough for most (smaller) websites. Algolia also works very well (you can check out case studies for both Algolia and Recombee) but is a more costly solution, good for bigger websites. If you want to learn more about Recombee, you should check out our detailed review.

Recombee recommendations for WordPress

Recombee is a personalization & recommendations engine that is proven to improve conversion rates greatly. But what if you wanted to implement it into your WordPress website ? Well you’re at the right place. This will explain why you wold want to add Recombee to your WordPress website but also how you could go it. Why integrate Recombee into WordPress? Integrating Recombee into WordPress offers countless benefits : Firstly, it enhances user experience by delivering personalized recommendations tailored to individual preferences, thereby increasing user engagement and satisfaction. Recombee is also a very versatile recommendation engine. It can be used for e-commerce, movie or video streaming and blog or news websites. This is because it offers countless user events (interactions) and trained models to use.

Build a recommendation system using Recombee and PHP

Recombee is a recommender that offers personalized search & recommendations for e-commerce, media, and other industries. It uses machine learning algorithms to analyze user behavior, preferences, and interactions in order to provide relevant and accurate suggestions. With Recombee, businesses can improve their customer experience by offering personalized product recommendations based on each individual’s browsing history, purchase history, and interests. This helps increase customer engagement and satisfaction, ultimately leading to higher sales and revenue. If you wish to learn more about Recombee, you can check out our full review. In this guide, we will learn how to build a recommendation system using Recombee and PHP. Getting started with Recombee and initializing the project Create a Recombee account at the following : https://oauth.recombee.com/ and initialize your

Integrate Recombee into Woocommerce website

Integrate Woocommerce with Recombee

Woocommerce is the #1 solution for e-commerce globally. This WordPress plugin provides a powerful and customizable platform for online businesses to sell their products and services. With its user-friendly interface and easy integration with various payment gateways, Woocommerce has become the go-to choice for many entrepreneurs. One of the key features of Woocommerce is its flexibility. It offers a wide range of extensions and themes that allow you to customize your store according to your specific needs. Whether you want to add new functionalities or enhance the design of your website, there is an extension or theme available for almost any requirement. One of these features you could consider adding is recommendations. Why equip Woocommerce with personalized search & recommendations? Woocommerce already offers users

Woocommerce product recommendations

Woocommerce is one of the most popular and widely used WordPress plugins for e-commerce websites. It offers a wide range of features and functionalities that make it easier for online store owners to manage their products, inventory, orders, and payments. Woocommerce allows users to seamlessly integrate an online store into their existing WordPress website without having to switch platforms or create a separate website for their e-commerce needs. Another major advantage of using Woocommerce is its extensive range of extensions and add-ons. Some of these add-ons can be product recommendations. In this blog post, we will learn about the benefits of these product recommendation plugins but if you wish to discover the best ones you should check out our top 5 list of recommendation plugins

ReQL – How to create business rules for Recombee (with examples)

Recombee is a personalized search & recommendations provider. One of it’s major advantages is that Recombee gives the user the option of modifying the queries from the backend using scenarios and business rules. For example, if you have a Woocommerce website with WPSolr & Recombee, you can hide certain specific items without needing to access the WordPress website, only the Recombee dashboard. You can then construct these business rules using ReQL, a Recombee exclusive Query Language that allows total freedom. You can learn more about it from the official Recombee documentation. How to create business rules Create business rule Click on the ‘Business Rules’ tab in the Recombee dashboard. Click on the ‘+ Create Rule’ button. Set the title in the

AI Recommendations for movie streaming services

Movie streaming platforms utilize advanced recommendation algorithms to enhance content discovery for viewers, making the viewing experience personalized and enjoyable. By providing tailored suggestions based on individual preferences, these platforms boost user retention rates significantly. Personalized recommendations reduce search time, increase user satisfaction, and improve the overall browsing experience, increasing the likelihood of continued subscription. Improve content discovery Movie streaming platforms offer a vast array of content for viewers to choose from, catering to diverse preferences and interests. By utilizing personalization, these platforms enhance content discovery significantly, making the viewing experience more personalized and enjoyable. As a result, the platform’s catalogue appears more extensive and appealing to users, showcasing a wide variety of entertainment options to explore. Acquiring the rights to

Recombee Review : The most versatile AI recommender

Recombee is an AI-powered recommender that offers both recommendations & personalized search. Whether it’s recommending products, articles, or movies, Recombee leverages advanced algorithms and machine learning to deliver personalized recommendations & search that keep users engaged and satisfied. With its easy integration and customizable features, Recombee empowers businesses to optimize content discovery, increase user retention, and drive conversions effortlessly. Highly-performing recommendations Recombee prides itself in increasing conversion rates and in turn revenue tenfold. You can verify this by reading their case studies. Using the case studies, you can observe that Recombee improves website performance in most situations whether it is general purposes, e-commerce, streaming, news, etc… Here are the main types of recommendations : 1. Item recommendations

Top 5 Recommendation Plugins for Woocommerce & WordPress

Recommendations are an emerging technology today, often used in e-commerce or video streaming. If you wish to equip your WordPress or Woocommerce website with recommendations, there are quite a few plugins available. However, not all of them are created equal. Some may be limited in functionality, while others may lack compatibility with certain themes or other plugins. Here are the top 5 : 1. WPSolr WPSolr is a complete search and recommendations WordPress plugin that integrates countless search engines & recommenders into your WordPress website. Apache Solr, Elasticsearch, Opensearch, Weaviate, Algolia, Recombee, Google Retail are all compatible (check out our engine features comparison). It is versatile and can be used for multiple purposes : blog website, e-commerce website, news website,

Overview of different filtering algorithms (for personalization)

In the past, websites aimed to boost click-through and conversion rates by improving search features. Now, a new technology called recommender systems has emerged. These systems work subtly in the background, requiring little user interaction. They personalize recommendations, closely linking with personalized search to tailor the user experience. But how do these recommendation systems work ? They use algorithms to filter the results that will be returned to the user. These algorithms are : content-based filtering, collaborative filtering, hybrid filtering and knowledge-based filtering. Diagram explaining how collaborative filtering works Collaborative filtering We will start of with the most popular type of filtering algorithm today : collaborative filtering. Collaborative filtering makes use of machine learning to quickly filter (recommend) the most relevant items

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What is Retrieval-Augmented Recommendation (RAR)?

I bet that the name Retrieval-augmented recommendation reminds you of something. That’s right! It’s a similar process to RAG (retrieval-augmented generation) but with a twist. Instead of using a search engine to retrieve the items and then feeding them to a generative AI, you retrieve the items using a search engine and then re-rank them using a recommender (personalization). This way you get the best of both worlds : any search engine of your choice but with personalization. This is powerful since you can basically build your own personalized search. Why? At WPSolr (WordPress search and recommendations plugin), we came up with this new method of search because one of our clients needed a personalized vector (AI) search for their e-commerce website

What is personalization ?

Personalization has become impossible to ignore in today’s digital landscape, permeating various aspects of our online experiences. As consumers increasingly expect personalized experiences, businesses across industries are investing in personalization technology to enhance user engagement, drive conversions, and foster customer loyalty in today’s highly competitive digital market. What is personalization? Personalization can be used whenever content is delivered to the user. It works by tracking user events that trigger whenever the user interacts with elements of interest in the website (page views, added to cart, added to favourites, etc…). This data is then used to train a model that comprehensively learns about users, enabling it to provide personalized recommendations tailored to each individual’s interests. What are some uses of personalization

What is personalized search?

Search has evolved over the years, first starting with traditional keyword search, then moving on to Vector (AI) databases. But nowadays, a new type of search is being popularized : personalized search. As it’s name implies, this technique consists of personalizing the search (keyword or vector) using stored events (or interactions) for each user. It is closely related to the other popular personalization system called recommendations. What is personalization ? Personalization consists of customizing the search results based on the user’s preferences. This is done by collecting user events, that are triggered whenever the user interacts with or does an action on the website, and using this to tailor the search results to the user’s preferences and needs. The personalization model

AI vs non-AI recommenders

Recommenders are intelligent systems designed to analyze user preferences, behaviors, and interactions to provide personalized recommendations. These systems utilize various algorithms and techniques to suggest relevant content, products, or services to users, aiming to enhance their browsing or shopping experience. By leveraging data such as purchase history, browsing patterns, and demographic information, recommenders offer tailored suggestions that align with individual user preferences, increasing engagement, satisfaction, and ultimately driving conversions. But there are two different types of recommenders : AI vs non-AI recommender. Non-AI recommenders This type of recommendation suggests content based on explicit user or programmatically entered data and metadata. It is fairly limited since it can only make use of two filtering algorithms : content-based filtering and knowledge based filtering. This

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7 Best User Events to Track for Training AI Recommenders

AI recommenders (and personalization in general) are used to suggest pertinent content to your website’s visitors. They work by being trained using data that is passively being sent by visitors (called user events) so the AI can learn about their behaviours and needs. Some of the most popular recommenders are Algolia, Recombee and Google Retail. They are a great way of increasing CTR. Here are some of the 7 best events to train your AI recommenders : Detailed view of an item (clicked) This user event is sent whenever a user views any page or product on your website. They are valuable for recommenders since they can give insights into what the user might be interested by and is one of

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How Product Recommendation Systems Boost your E-commerce Sales

AI Recommendation systems play a crucial role in enhancing the shopping experience for e-commerce customers. E-commerce platforms (example: Woocommerce) can provide personalized product recommendations tailored to each individual shopper’s preferences, browsing history, and purchasing behavior. They are a major driver for achieving higher conversion rates and selling more products. Here are the reasons why it could help your bottom-line : Your own dedicated salesman in a digital landscape Trust your recommender to recommend the most relevant content to potential customers. Like an ordinary salesman would, the recommender system will try to learn more about visitors. Instead of blindly suggesting random items, the recommender will collect user events/interactions (page views, add to cart, etc…) and use this data to recommend the

Post image : Learn about conversion rates and CTR

What are CTR and Conversion rate, and why should you care?

There are many ways of measuring success when evaluating your website’s effectiveness, but the main ones are probably CTR & conversion rate. CTR (or Click-Through Rate) is a percentage that illustrates user engagement with your content. It is estimated from the number of users that clicked on a particular link compared to the total number of users who viewed it. Conversion rate on the other hand is the percentage of your website’s users that completed a process (that can vary depending on your website goals). Some examples could be the user purchasing a product, completing a form, opening an email you sent, etc… Different impacts on your businesses CTR Click-through rate, calculated using ‘(clicks ÷ impressions) x 100‘ , can be

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What are AI-powered Recommendation systems : A 2024 complete beginner’s guide

In the past, you used to increase your website’s click-through/conversion rate by adding a high performance and relevant search experience. But recently, a new type of technology has emerged : recommender systems (or recommenders). Recommendation systems often operate more subtly, with users interacting minimally with the recommendations and not fully registering their presence. They rely on personalization and are closely related to personalized search. Some of the most prominent recommenders on the market are Recombee, Amazon Personalize, Algolia and Google retail. Why choose a recommendation system? Example of the Amazon homepage full of recommendations to guide the user Recommendation systems offer an effortless browsing experience Forcing your users to search for the products or articles they want adds unnecessary steps to a

Algolia’s impact on user engagement metrics

Introduction Algolia is a powerful search-as-a-service platform that has revolutionized the way websites and applications implement search functionality. Its impressive search capabilities combined with its developer-friendly API have made it a favorite among developers and businesses alike, and it has had a significant impact on user engagement metrics. User engagement metrics, such as average time on site, bounce rate, and conversion rate, are critical indicators of a website or application’s success. Algolia’s fast and accurate search results greatly enhance the user experience, leading to increased user engagement and ultimately improved metrics. Algolia’s Impact on User Engagement Metrics Algolia’s key features, such as instant search results, typo tolerance, and relevance ranking, contribute to higher user engagement on websites and applications. Let’s take a closer look at

Using Weaviate to personalize the shopping experience in WooCommerce

Introduction In today’s ultra-competitive e-commerce landscape, delivering personalized shopping experiences to customers is crucial for success. Personalization allows online retailers to tailor their offerings to individual preferences, increasing customer satisfaction and driving conversions. One powerful tool that can help achieve this is Weaviate, an open-source knowledge graph that acts as a vector search engine. By incorporating Weaviate into your WooCommerce store, you can harness the power of AI and machine learning to provide personalized product recommendations for each customer. Getting Started with Weaviate To begin personalizing the shopping experience in WooCommerce using Weaviate, you’ll first need to set up and configure Weaviate. Here’s a step-by-step guide: 1. Install Weaviate: You can download Weaviate from the official website and follow the installation instructions provided. 2. Set