Markov Chain-Based Web User Journey Prediction
At ThatWare LLP , we’re pioneering the union of advanced AI and SEO — and our latest feature, Markov Chain–Based Web User Journey Prediction , exemplifies that commitment. By applying Markov Chain models to website page-flow data, we move beyond simple analytics and into true predictive navigation analysis. For example: if a visitor lands on your homepage, the model uses historical probabilities (say: 40% to About Us, 30% to Products, 30% to Contact) to forecast where they’re likely to go next. Why does this matter? With these insights, you can optimise site architecture, menus, CTAs and page flows so that users are guided deliberately toward high-value pages (such as conversion pages) rather than wandering. Data comes from tools like Google Analytics 4, Hotjar or Mixpanel and then we build the transition matrix, normalise probabilities and simulate journeys. In practical terms: you discover the most common sequences (Homepage → Services → Contact), identify drop-off point...