GloSSaRY

Digital Experience Monitoring

What is Digital Experience Monitoring?

Digital experience monitoring (DEM) brings monitoring and monitoring together to enable companies to provide outstanding digital experiences. Digital experience monitoring helps organizations understand and optimize the availability and performance of their applications and services.

The solutions use data collected from real users and synthetic agents to help you understand digital experiences such as:

  • A customer using your website or mobile application to make a purchase.
  • An employee accessing a SaaS application to send an email.
  • How an API is performing as customers use it to log into 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 and monitoring strategy to measure and analyze performance across applications, platforms, devices, and cloud services. They also need to understand the actions that need to be taken to improve situations.

How does DEM work?

Digital experience monitoring 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 digital experience monitoring architecture typically has three layers:

  1. Data ingestion methods. Data is collected from devices and endpoints, JavaScript-injected web pages, network packets sniffers, simulated user interactions, and APIs.
  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 important?

Traditional end-user digital 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 applications, but tend to have highly distributed microservices that work in tandem to meet user requirements.

Active and passive monitoring

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 active 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.

Active 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 together with digital experience monitoring helps companies find and remedy problems before users go on to their favorite social media platforms to share their poor user experience with other existing and potential users. For instance, observing user sentiment on social media sites like Twitter can help an organization identify problems active monitoring may have missed.

The collective user experience can be far different and more unpredictable than the individual user behavior models developed using active 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. Real user monitoring measures performance from actual users visiting the website. Data is collected via a script in real time.

A complete digital experience monitoring and monitoring strategy must include both active and passive data gathering methods.

Building your digital experience strategy

A comprehensive digital experience strategy starts with understanding all the elements and components necessary to deliver a digital application or service. Measuring the digital experience involves leveraging application, passive, and active monitoring methods in tandem:

  • Application monitoring identifies issues that occur at     the application level behind your firewall.
  • Active 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.
  • Real user monitoring allows a business to respond to user experience issues after they occur by gathering real-world data across endpoints, devices, and locations. Data sources collected by RUM methods include help desk and tech support debriefs, monitoring inter-user interactions on social media, JavaScript-injected web pages, network packets, cloud platform endpoints, etc.

A digital experience monitoring solution should:

  • Collect data from the end users' 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.
  • Provide actionable information that helps businesses make quick decisions, so they can keep the digital experience working at its best.

Conclusion

Digital experience monitoring gives organizations insight into end-to-end application performance issues that might impact a user’s digital experience.

Digital experience involves more than just downtime. Latency and other metrics affect user experience as well. It’s essential for a company to monitor both active and passive users to preempt issues and track real-world experience.

Organizations need an optimal digital experience monitoring strategy that leverages application, active, and passive techniques simultaneously in order to get the best results.