Interactive Path Discovery on Customer Journeys with Outcome prediction using Markov Algorithms
Join Karthik Guruswamy, Principal Consultant, Big Data & Advanced Analytics at Teradata Aster Analytics, at the LinkedIn Building where he will demonstrate an interactive Guided Analytics Visualization Tool used to study customer behavior.
He will also review two common algorithms – Markov Chains and Hidden Markov. These methods are used to understand event transitions and latent behavior/intent that drives observable behaviors. RSVP Now!
Understanding customer journeys or paths is very critical to understanding customer behaviors. Observing how your customers browse and arrive at a product page or decide to click on items can lead to deep insights in web-page design anomalies, propensity to buy, churn and other outcomes.
Interactive visualizations can answer what-if questions. Quantitative techniques such as Markovian processes can help model from historical browsing behavior. These methods can also help predict potential outcomes in real-time, given a path taken by customer.
Business Analyst, Product Analyst, Digital Marketing Specialist, Product Managers, Data Scientist, Statisticians, and SEM/SEO managers.