Website categorization is the task of classifying a domain, URL, or webpage under a pre-classified category.

Website classification has emerged as a pivotal tool, shaping the way we navigate the digital landscape. Its significance extends beyond mere organization, and has become the key to ensuring protected digital experiences, empowering parental control measures, optimizing web analytics and marketing strategies, enhancing ad placement, and protecting brand reputation. Moreover, website categorization tools are integral to developing robust cybersecurity defenses, as well as aiding in regulatory compliance across industries.

Website categorization, underpinned by a well defined taxonomy, is the systematic organization of websites into distinct categories or groups based on specific criteria or characteristics, such as the type of content, functionality, audience, or subject matter. Assigning website categories that fit within a taxonomy’s hierarchical structure serves varied purposes, from facilitating a safe browsing experience, to blocking phishing or malicious websites, to boosting the efficiency of digital advertising efforts, to enforcing internet usage policies and regulatory compliance.

But how does website categorization function in the first place? At its core, it involves a fusion of complex algorithms, Artificial Intelligence, and machine learning. Algorithms, the foundational step, set the rules of classification based on specific parameters. However, due to the vast and dynamic nature of the web, these algorithms must continuously evolve to incorporate advanced elements of AI and machine learning. AI enhances the process with its ability to comprehend context and nuance, while machine learning offers the capacity to ‘learn’ from data patterns and improve over time. Together, they create a powerful and adaptive system that can tackle the dynamic landscape of the internet.

Learn more about website categorization through the blog post, “Harnessing the Power of Website Categorization.”

More Relevancy for Ad Targeting with Greater Granularity

zvelo once offered 53 categories that were used to classify content on websites about Businesses & Services, Politics & Law, Portal Sites and others. This was later raised to 141 categories to help cover even more topics. The latest version boasts nearly 500 categories, making it one of the most granular categorization sets in the industry. We’ve managed to upgrade our categorization systems to better serve the needs of our existing and future technology partners and following is one example why this matters.

Full Path URL Content Classification

Given the dynamic nature of the majority of today’s websites, categorization at the full path URL versus the base domain is superior and now required. Parts of a website include the top-level domain (.com, .org, etc.), the base domain (, sub-domain ( or sub-path ( When categorizing content, it is highly important to recognize exactly what is being classified within a website because content can differ dramatically across full path URLs.

Website categorization and URL Parameters

What is a URL parameter? Quite simply it is a string of characters, or a query string, that is appended to a URL that contains data. This data is passed to predefined web applications to find the appropriate content and return it back to the user’s web browser which then generates the entire web page. The query string can also be used for various other methods such as identifying a user’s session or using it as a way to look up information about your online bank account after you have logged in. URLs with parameters are used by various types of web sites however online shopping, auction, and banking type sites are probably the most prevalent.

Using Keyword Density for Website Categorization

Manually classifying the content on a single web page takes but a few seconds to accomplish. Analyzing the keywords – words or phrases – used and the number of instances of each – keyword density – is one way to go about it. When needing to classify the content on billions of web pages at a time, however, the task becomes overwhelmingly daunting for any human eye to handle. In this scenario, only an automated content classification engine can succeed.