Digital Experience Monitoring (DEM)
Digital Experience Monitoring (DEM) helps organizations monitor and optimize the availability and performance of their applications and services based on data collected from real users and synthetic agents. Digital experiences include:
• A customer using your website or mobile application to make a purchase.
• An employee accessing a SaaS application to send an email.
• Using an API for customers to log in to your application using Twitter, LinkedIn or Facebook.
Digital experiences have grown with the proliferation of IoT devices, cloud, SaaS, and mobile websites and apps. It is no longer enough for organizations to monitor and collect data from a single perspective.
Organizations now need a comprehensive monitoring strategy to measure and analyze performance across applications, platforms, devices, and cloud services.
How does Digital Experience Monitoring (DEM) work?
DEM involves collecting and analyzing data from the end users perspective. Availability and performance of applications and services are measured from multiple locations. The data collected leads to the creation of baselines and benchmarks. These baselines are then used to configure alerts and understand the impact of outages.
Digital experience monitoring architecture
The DEM architecture typically has three layers:
2. Nonrelational database management system (DBMS). The collected data is stored for analysis and modeling.
3. Machine-learning components. Issues are uncovered and business decisions are made using predictive analysis, trend analysis, pattern matching, and data visualizations.
This three-layer architecture allows organizations to understand the continuous digital experience from their users’ (human or digital) perspective, and preemptively catch and correct potential problems in the digital user experience.
Why is Digital Experience Monitoring (DEM) important?
Traditional end-user experience monitoring primarily involves application performance monitoring (APM) that monitors parameters like availability, response time, and transaction completion rates. These parameters are based on a single dataset (collected from servers via agents installed on the server, log files, polling of hardware systems, etc.) and are not enough to evaluate the complete user experience.
Approximately 80% of performance and availability issues occur outside the organization’s firewall. Organizations thus need ways to collect data from multiple sources and not just their application end-points. Additionally, organizations no longer have monolith application but tend to have highly distributed microservices that work in tandem to meet user requirements.
Synthetic and real user monitoring (RUM)
Users interact with applications and services, and their overall user experience is an amalgamation of how effortlessly and seamlessly they are able to use them. Organizations can make use of synthetic monitoring tools to simulate user workflows, detect and identify downtime and reachability issues, predict app performance issues before they occur, and preemptively fix the issues.
Synthetic monitoring simulates requests to applications and services to verify performance, availability, and reachability. It includes issuing requests to DNS, FTP, and API, or simulating users that are accessing an application.
Digital experience monitoring helps companies find problems before users go on to their favorite social media platforms to share their poor user experience with other existing and potential users. Monitoring user sentiment on social media sites like Twitter can help an organization identify problems synthetic monitoring may have missed.
The collective user experience can be far different and unpredictable than the individual user behavior models developed using synthetic monitoring methods. To combat this unpredictability, organizations can leverage Real User Monitoring (RUM) methods to evolve the behavioral models based on real-world user experiences.
RUM measures performance from actual users visiting the website. Data is collected via a script in real time.
To see a complete picture of performance a complete digital experience monitoring strategy must include both synthetic and real user monitoring.
Creating a Digital Experience Monitoring strategy
A comprehensive DEM strategy starts with understanding all the elements and components necessary to deliver a digital application or service. Measuring the digital experience involves leveraging application, synthetic, and real user monitoring methods in tandem:
• Application monitoring identifies issues that occur at the application level behind your firewall.
• Synthetic monitoring allows businesses to proactively model and predict individual user behavior and experience. Simulated tests gather performance data from multiple global locations within and outside an organization’s firewall. This information allows a business to preemptively identify problems and take preventive measures before affecting end users.
A Digital Experience Monitoring solution should:
• Collect data from the end user’s perspective to identify potential problem areas.
• Provide a baseline of performance that is used to establish alerting thresholds.
• Visualize data in multiple ways to understand where improvements to the digital experience can be made.
Digital experience monitoring gives organizations insight into end-to-end application performance issues that might impact a user’s digital experience.
Digital experience is more than just a customer’s experience with downtime, but latency and other metrics affect user experience as well. It’s essential for a company to monitor both real and synthetic users to preempt issues and track real-world experience.
Organizations need an optimal digital experience monitoring strategy that leverages application, synthetic, and RUM techniques simultaneously. Click here to download a guide to digital experience monitoring.