Clickrelated

Clickrelated is a term used in digital analytics to describe metrics, models, and data that focus on the relationships between user clicks within a session or across sessions. The term is not tied to a single standard specification, but is used to denote analyses that examine how one click relates to subsequent clicks, sequences of clicks, or co-click patterns on related items.

In clickrelated analysis, researchers treat clicking events as nodes in a graph or states in a Markov chain. Features often include inter-click time, transition probabilities, co-click likelihoods, and path similarity. The aim is to understand navigation behavior, user intent, and attribution in ways that go beyond simple totals like total clicks or page views.

Applications include web analytics to improve site navigation and search, in recommender systems to predict next items, in marketing attribution to allocate credit across touchpoints, and in fraud detection to identify atypical sequences.

Common approaches comprise graph-based models of clickstreams, Markov models (including higher-order variants), sequence mining, and neural sequence models. Visualizations of clickrelated networks can help identify bottlenecks, popular transitions, and latent communities of pages or products.

Data and ethics considerations mirror other forms of clickstream analysis. Like related work, clickrelated analyses rely on event logs that raise privacy concerns. Best practices emphasize data minimization, anonymization, opt-out options, and clear user consent.

See also: clickstream, user journey, attribution, sequence modeling, and Markov chains.