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A Primer On Digital Experience Monitoring (DEM)

What is Digital Experience Monitoring (DEM)?

Digital Experience Monitoring (DEM) refers to the practice of tracking and analyzing the performance and quality of digital interactions users have with an application or service. DEM goes beyond traditional system metrics to focus on the perspective of end users, combining real-time monitoring with contextual data about how users navigate digital platforms.

It covers web, mobile, and cloud-based applications, and ensures that companies can measure, manage, and improve the user experience to maintain a competitive edge in the market.

Fig 1: Coverage of Digital Experience Monitoring (DEM)

Why Is Digital Experience Monitoring (DEM) Critical For Business?

DEM is crucial for ensuring that customers have a seamless and engaging experience. By leveraging DEM in conjunction with business journey observability, companies can proactively identify and address issues impacting user satisfaction and business success, such as slow loading times, broken links, or poor responsiveness, to optimize customer journeys and operations, and stay ahead of competition.

Key Elements of DEM

1. Real User Monitoring (RUM): Monitoring real-world usage by capturing performance data as users interact with the application. RUM provides end-to-end visibility into the real-time activity and experience of individual users

2. Synthetic Monitoring: Simulating user interactions to continuously test and monitor the performance and availability of applications.

3. Network Performance Monitoring (NPM): Monitoring network components that affect digital services, including latency, packet loss, and throughput.

4. Application Performance Monitoring (APM): Tracking the performance of code, databases, microservices, etc., to ensure back-end systems are working optimally.

DEM Architecture

The architecture of DEM typically comprises three layers:

1. Data Ingestion Layer: Various sources such as devices, web pages, network sniffers, simulated interactions, and APIs contribute data.

2. Nonrelational Database Management System (DBMS): This layer stores the collected data, facilitating analysis and modeling.

3. AI/ML Layer: Predictive analysis, trend analysis, pattern matching, and data visualizations aid in uncovering issues and informing business decisions.

Fig 2: Architecture of Digital Experience Monitoring (DEM)

This architecture enables proactive identification and resolution of potential issues, fostering continuous improvement in digital user experience.

What Are The Benefits of Digital Experience Monitoring?

DEM provides valuable insights for data-driven decision-making, aligning digital efforts with business goals, and driving customer satisfaction, engagement, and revenue growth.

DEM in observability software also offers a range of advantages for organizations striving to deliver superior digital experiences:

1. Proactive Issue Identification: DEM enables early detection and resolution of potential disruptions across digital touchpoints, ensuring uninterrupted user experiences.

2. Enhanced User Experience: By tracking key metrics like application response times and page load speeds, DEM enables organizations to optimize user interactions, leading to heightened satisfaction and engagement.

3. Efficient Troubleshooting: DEM tools provide deep visibility into underlying factors affecting digital experiences, facilitating quicker issue resolution, and minimizing downtime.

4. Data-Driven Decision Making: Leveraging valuable insights from DEM, organizations can make informed decisions regarding infrastructure, application optimizations, and capacity planning, aligning digital initiatives with business goals and enhanced user satisfaction.

Challenges With Digital Experience Monitoring

In this section, we examine some of the commonly encountered challenges in DEM, given the rapidly evolving application deployment landscapes and the explosion of user and application data.

1. Complex, Distributed Architectures

Many modern applications rely on microservices, and multiple third-party services (like payment gateways or content delivery networks), and are spread across hybrid cloud environments. Monitoring such distributed systems end-to-end and correlating performance issues can be difficult.

For example, a sudden spike in latency could be due to a slow microservice or an external API provider.

2. User Context Variability

Users access digital platforms from various devices, networks, and geographic locations. This results in highly variable user experiences. Identifying the root cause of an issue that impacts only a specific subset of users is a challenge.

E.g.: Users from a specific region may experience slower load times due to network issues that are not visible in synthetic tests.

3. Lack of Business Context

Traditional monitoring often focuses on system performance metrics without connecting these to business outcomes, like user satisfaction, revenue impact, or customer journey completion.

E.g.: A slow-performing login page could lead to user abandonment, but without tying performance to business metrics, the revenue impact of that drop-off could go unnoticed.

A more advanced business-centric observability software like VuNet uses ContextStreams to utilize the full potential of your business data

4. Alert Fatigue and Noise

Monitoring systems often produce large volumes of alerts, many of which may not be actionable or relevant. This can lead to alert fatigue, where critical issues get missed amid irrelevant alerts.

For instance, a flood of alerts due to minor latency in one service might overshadow a more severe issue affecting the user checkout process.

Sarika Atri talks about these “Silent Failures” and more in the latest episode of Observability Talk. Click here to watch it

5. Siloed Monitoring Tools

Different teams (DevOps, Security, Network Operations) often use separate tools for monitoring their components (infrastructure, application code, network). This leads to siloed data, making it hard to get a unified view of the digital experience.

E.g.: A network slowdown might not be correlated with a spike in database queries due to fragmented visibility.

Addressing DEM Challenges via Business-Centric and Journey-Centric Observability Software


1. Business-Centric Observability

Business-centric observability (BCO) aligns technical performance metrics with business outcomes, such as revenue, conversion rates, or user satisfaction. This approach ensures that any performance degradation is viewed through the lens of its impact on the business.

For instance, instead of simply tracking page load times, a retail company can use BCO and DEM to monitor the impact of page performance on cart abandonment rates. If page load time exceeds 3 seconds, they might see a corresponding drop in completed purchases. By monitoring the correlation, teams can prioritize fixing the page performance issue based on its business impact.

Fig 3: Combination of Digital Experience Monitoring and Business Observability

Another use case for correlating business KPIs with business processes could be in the context of an E-commerce Checkout Process, where the entire checkout funnel (search, cart addition, payment) can be monitored and correlated with business KPIs like conversion rate. A sudden drop in payment completion could trigger an alert that ties the issue to revenue loss, allowing the team to focus on resolving it quickly.

2. Journey-Centric Observability

Journey-centric observability is a flavour of business-centric observability which focuses on the user’s entire journey across multiple touchpoints (e.g., from login to purchase completion) and associates key business metrics with each micro-journey. It involves mapping user flows and monitoring their performance to ensure that users complete key actions. This approach helps identify issues within specific stages of the journey that can significantly affect user satisfaction.

For example, a banking app can monitor a user’s journey by logging in, transferring money, and receiving a confirmation. If an issue occurs, such as a delay in the confirmation page, journey-centric monitoring would highlight that the problem specifically impacts the “completion” phase of the journey.

A specific use case to illustrate journey-centric observability in observability software could involve a telecom company using DEM in the digital onboarding process for new users—from registration, to plan selection, to service activation. It allows for easier correlations

  • Cause: A large number of user drop at the “Plan Selection Stage
  • Effect: Issue with specific part (leg) of the journey (e.g., confusing UI or slow performance)
  • Business Impact: Drop in customer acquisition.

Specific Approaches in BCO with DEM

1. Correlating System Performance with Business KPIs

Integrating business metrics with system performance data allows for real-time insights into how technical issues affect business outcomes. E.g.: A video streaming service can monitor stream latency and buffer times and correlate them with user retention or churn.

2. User Journey Mapping and Heatmaps

Heatmaps or user journey maps help to visualize where users are dropping off or experiencing performance degradation. For instance, in a banking app, mapping the journey from login to successful transaction completion helps identify where users are facing delays or errors.

3. Deep Observability into the Stack

Deep observability, integrates network performance, infrastructure, and application monitoring across multiple APIs, microservices, and touchpoints with real-user interactions. This allows teams to address issues holistically. For example, a SaaS provider can use full-stack observability to monitor both infrastructure health and user experience, ensuring that infrastructure slowdowns are quickly identified and correlated with end-user issues.

Conclusion

DEM is a valuable tool in the arsenal of IT Operations Management (ITOM) and Business Operations (BizOps) teams as it provides real-time insights into user interactions with digital applications.

For ITOM teams, DEM helps quickly identify, diagnose, and resolve performance issues, ensuring optimal system uptime and enhancing user satisfaction.

For Biz Ops teams, it offers visibility into user behavior, enabling data-driven decisions to improve customer experiences, increase engagement, and drive business outcomes.

Fig 4: Digital Experience Monitoring (DEM) Benefits

By adopting business-centric and journey-centric observability, organizations can overcome the challenges of DEM by focusing on the real-world impact of system performance. This improves user experience and improves the ability to prioritize fixes based on business impact. By bridging the gap between technical performance and user experience, DEM supports operational efficiency and strategic business growth.

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