Digital Experience Monitoring (DEM)

 

Digital Experience Monitoring (DEM) helps organizations monitor and optimize the availability and performance of their enterprise applications and services based on data collected from human and machine users.

 

With the proliferation of IoT devices, cloud and SaaS, mobile websites and apps, ever-evolving network protocols, and the incessant barrage of information via social media, it is no longer enough for organizations to monitor and collect data from a single perspective.

 

Organizations now need a comprehensive strategy to monitor, model, and analyze user behavior across applications, platforms, devices, and cloud endpoints.

How does Digital Experience Monitoring (DEM) work?

DEM involves collecting and analyzing data from multiple sources to monitor the availability and performance of apps and services. Collected data helps IT model end user behavior (human and digital) based on previous user interactions with apps and services.

Digital experience monitoring architecture

The DEM architecture typically has three layers:

  • Data ingestion methods (for example, data is collected from devices and endpoints, JS-injected web pages and network packets, simulated user interactions, and APIs)
  • Nonrelational Database Management System (DBMS)
  • Machine-learning components (for example, data visualization, pattern matching, predictive analysis)

 

This three-layer architecture allows organizations to understand the continuous digital experience from their users’ (human or digital) perspectives, and preemptively catch and correct potential problems that will affect 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 microservices that work in tandem to meet user requirements.

 

Synthetic and real user monitoring (RUM)

Users interact with each of these applications, and their overall user experience is thus an amalgamation of how effortlessly and seamlessly they are able to use each application. Organizations can make use of synthetic monitoring tools to model and simulate user behaviors, predict app performance issues before they occur, and preemptively fix issues.

 

However, with social media being pervasive in our digital lives, users no longer interact with the application individually. Instead, they go on to their favorite social media platforms to share their 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.

 

The definition of user

Finally, organizations need to be mindful about how they define “users”. With cloud technology and automation being the norm of the day, users might not be humans clicking away at screens; instead, users might be digital agents trying to accomplish their programmed tasks. The application performance then relies on how these digital users interact with the application and if they can complete tasks easily and successfully.

 

To help illustrate, let’s consider an e-commerce website. The website has several components that together make up the digital experience: DNS, CDNs, payment APIs, social media plugins, and human users.

 

Each of these components are “digital agents,” and the website’s overall digital experience depends on how each of these components interact with the website. To guarantee positive digital experiences, a business must monitor, collect data, analyze, and optimize the digital experience for each of these components.

 

For a detailed case study, see 3 Reasons Ecommerce Needs Digital Experience Monitoring.

 

The data that the organizations collect and analyze must replicate the comprehensive user experience across data points, applications, and social media. Organizations should leverage multiple data ingestion methods, analyze and synthesize findings, and implement a cohesive, end-to-end digital experience monitoring strategy.

 

Creating a Digital Experience Monitoring strategy

The gist of Gartner’s recommended DEM strategy is as follows:

 

• Leverage the strengths of diverse data ingestion mechanisms to model and analyze how end-users interact with the app or service. Synthesize the multiple data streams into a single, cohesive model.

• Use traditional end-user experience monitoring (EUEM) methods to develop a baseline for the user experience model. Then determine performance metrics and monitor a user’s experience across applications and interactions.

• Develop not only an individual user experience model, but a collective user experience model. Develop metrics to measure and analyze how group sentiment affects perceived user experience.

 

A comprehensive DEM strategy involves leveraging application, synthetic, and RUM monitoring methods in tandem:

• Application monitoring allows you to identify and fix 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 many end users.

• Real User Monitoring (RUM) 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.

 

Conclusion

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

 

To maximize positive user experience and to minimize negative user experience, businesses should monitor not only behind the firewall, but each piece of their infrastructure outside of the firewall.

 

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.

About Catchpoint

Catchpoint is the leading provider of digital experience monitoring solutions including synthetic, real user, and SaaS monitoring.