Analyzing Individual User Journeys in Tableau with Snowplow Data

Visualizing event-level user journeys with Snowplow data in Tableau can provide detailed insights into user behavior on websites or apps by using a Gantt-style chart to explore individual user flows. This approach leverages Snowplow's granular event tracking, particularly page_view and page_ping events, to create visualizations where each bar represents a single event and its duration on a timeline for a specific domain_userid. This type of visualization is beneficial for debugging behavioral issues, visualizing content engagement patterns, and presenting qualitative narratives to stakeholders. To construct these charts, data modelers need certain fields such as domain_userid, event_name, page_url, and timestamps for ordering events, and it is recommended to use page_ping events for measuring time-on-page. The data should be structured for Tableau by pre-aggregating it to represent task durations over time, filtering for individual users, and calculating event durations. While Tableau is a suitable tool for this visualization, there are alternatives like graph databases and Indicative for more advanced pathing analysis. The visualization helps uncover user struggles, content engagement, and duration of engagement, offering powerful qualitative insights from Snowplow's event data.