Hi Splunk Community, I'm currently building a digital membership card application for museums, zoos, attractions, and other membership-based organizations. The application captures thousands of visitor events every day, including QR code check-ins, digital wallet pass usage, membership renewals, guest passes, event participation, and mobile app interactions. My goal is to use Splunk to convert this event data into meaningful dashboards that help both technical teams and business users understand visitor engagement and operational performance. For example, the digital membership card application records every member interaction, allowing us to analyze: Real-time visitor check-ins Hourly, daily, and monthly visitor trends Active vs. inactive members Membership renewal rates Repeat visitor behavior Event attendance by membership type Peak entry times QR code scan failures Mobile app performance Digital membership card adoption across locations One area I'm particularly interested in is correlating application logs with visitor behavior. If check-ins suddenly decrease, I want to quickly determine whether it's due to lower attendance or an issue within the digital membership card application, such as API latency, authentication failures, or QR scanning problems. Another objective is to build executive dashboards that combine visitor analytics with application health, so operations teams can monitor member engagement, system performance, and renewal trends from a single Splunk dashboard. For those who have built similar dashboards in Splunk: Which visitor or membership KPIs have been the most valuable? Do you use accelerated data models for high-volume event data? What visualizations work best for visitor analytics? Any recommendations for designing dashboards that serve both technical and business stakeholders? ... View more