Our role as SEOs has evolved over the years – but more recently there has been a significant transformation in the way people discover and find information.
Search Engines core purpose have become an entry point delivering information based on specific queries but the rise of social media platforms and the reliance on reviews and recommendation for purchases has meant a shift in what we need to optimise.
The primary goal of a recommendation engine is to predict what items or content a user might be interested in and present those suggestions in a way that is relevant and valuable to the user. The recommendations are typically based on patterns and correlations identified from the user's historical data, such as previous purchases, interactions, and preferences.
There are several types of recommendation engines, and they can be broadly categorised into three main approaches:
1. Collaborative Filtering:
User-based Collaborative Filtering:
This method recommends items based on the preferences of users who are similar to the target user. If User A and User B have similar tastes and preferences and User A liked an item, the system might recommend that item to User B.
Item-based Collaborative Filtering:
This method recommends items based on the similarity between items. If a user liked a particular item, the system recommends other items that are similar to it.
2. Content-Based Filtering:
This method recommends items based on the characteristics or features of the items themselves and the user's preferences. For example, in a movie recommendation system, content-based filtering might recommend movies based on genres, actors, or directors that the user has previously shown an interest in.
3. Hybrid Methods:
Hybrid recommendation systems combine multiple approaches, often blending collaborative filtering and content-based filtering, to overcome limitations and provide more accurate and diverse recommendations.
The recommendation engine continually refines its suggestions over time as it gathers more data about user preferences.
What are some of the key differences between SEO & REO?
Objective:
• SEO: The primary goal of SEO is to enhance the visibility of a website or content on search engine results pages (SERPs). The focus is on improving the website's ranking for relevant keywords, ultimately driving organic traffic to the site.
• REO: The primary goal of REO is to enhance user experience by providing personalised recommendations. The focus is on predicting and suggesting content or products that align with the user's preferences, leading to increased engagement and satisfaction.
User Intent:
• SEO: SEO targets users who are actively searching for information, products, or services using search engines. Users have a specific query or intent, and the goal is to match their intent with relevant content.
• REO: REO targets users based on their historical behaviour, preferences, and interactions. Recommendations are provided proactively, often without a specific user query, to anticipate and fulfil user needs.
Data Utilisation:
• SEO: SEO relies on data related to keywords, search trends, and website structure. It involves optimising on-page elements, building quality backlinks, and creating valuable content to align with search engine algorithms.
• REO: REO relies on user data, such as past interactions, preferences, and behaviour. Machine learning algorithms analyse this data to make predictions about what the user might like, allowing for personalised recommendations.
Timing of Interaction:
• SEO: Interactions occur when users actively perform a search. The success of SEO is measured by the website's ability to appear prominently in search results and attract clicks.
• REO: Interactions occur proactively, with the system presenting recommendations without a specific user request. The success of REO is measured by the relevance and effectiveness of the recommendations in keeping users engaged.
Content Presentation:
• SEO: Content is optimised to match specific keywords and user queries. The goal is to provide informative and relevant content that satisfies the user's search intent.
• REO: Content is presented based on predictions about the user's preferences. The goal is to offer a personalised and enjoyable experience by recommending items that align with the user's tastes.
Application Domain:
• SEO: Commonly applied in informational websites, e-commerce, blogs, and any online platform aiming to attract organic search traffic.
• REO: Commonly applied in e-commerce, streaming services, social media, and platforms with a significant focus on personalised user experiences.
The ever-changing landscape means as marketers we need to consider how we ensure visibility across both search engines and recommendation engines.
While both SEO and REO contribute to enhancing online experiences, they serve distinct purposes and cater to different stages of the user journey — SEO for discovery and REO for personalised engagement.
An effective digital strategy often involves a balanced approach that incorporates elements of both optimisation strategies.
Looking for further support with SEO? Get in touch now.
Rebecca Weeks
