Mobile teams struggle to solve what they can’t see

For many businesses, mobile is now the most critical channel for engaging users. Mobile apps are where purchases happen, accounts are created, and first impressions are made. But it’s also where users are most likely to abandon their journeys if something feels broken, slow, or unintuitive.

All practitioners struggle to understand what actually happened during a user’s session when something goes wrong or when a user behaves in a way that deviates from the expected journey. This can get particularly puzzling when there are no apparent errors or performance blockers hindering a user’s experience. Traditional tools provide fragmentary details: logs, events, crash reports, or aggregated analytics. However, none of these capture the full context. Mobile engineers are unable to reliably reproduce bugs without seeing exact user actions. Support teams can’t respond effectively to vague or incomplete user reports.

Full visibility into mobile user behavior

This is where Session Replay comes in. This capability recreates real user behavior in a video-like playback, so you can visually step through a session just as the user experienced it: taps, swipes, scrolls, page transitions, and all. And now, for the first time, this powerful capability extends beyond the browser and crashes on mobile apps to include full sessions for native mobile apps.

With Dynatrace Session Replay for mobile apps, teams get a complete, contextual view of how users interact with mobile apps in the wild by collecting and visualizing key signals like gestures, views, UI states, and navigation paths. While Session Replay is often seen as a frontend-focused tool, it can significantly help identify, triage, and resolve backend issues by connecting user actions to system behavior. This helps contextualize backend failures, correlate user actions to backend events, and, in a nutshell, identify misalignment between front and backends.

How to make the most of Dynatrace Session Replay for Mobile Apps

Let’s dive into key use cases where Session Replay delivers tangible value across teams:

Faster debugging

Understanding the problem is often impossible with only data from Logs or Real User Monitoring. In some cases, observing the sessions where the error occurs can provide valuable context and lead to a more accurate solution.

Use case: Imagine your team can’t reproduce a performance issue affecting only a small segment of users still using iOS 17. Logs are inconclusive, and RUM data doesn’t tell the whole story.

With Session Replay, you can:

• Watch the exact gestures and actions related to the issue.
• See which page or interaction triggered the problem.
• Identify whether it’s a device-specific issue, a network hiccup, or a UI bug.

Result: Your dev team fixes the issue in hours, not days, without needing to reproduce it manually.

UX optimization and boosting conversion

The best way to understand users is to observe how they engage with your applications. Session Replay allows you to select a sample of mobile sessions based on various criteria. Watching these sessions helps you learn about annoyances and understand patterns in user behavior, which can then be streamlined into a better user experience.

Use case: Your analytics show a drop-off in the final step of your checkout funnel, and you don’t know why. Is it a confusing UI? A broken button? A slow-loading view?

With Session Replay, you can:

• Watch real user sessions to see where they pause, scroll, or back out.
• Identify if users struggle with form validation, payment options, or navigation.
• Spot rage taps or repeated attempts to interact with unresponsive elements.

Result: You optimize the checkout flow, reduce abandonment, and increase conversions—backed by real user behavior.

Improved customer support

Allowing help desk personnel to review the session that prompted a user’s complaint provides common ground for the conversation and helps ensure user satisfaction.

Use case: A user submits a support ticket: “The app didn’t work when I tried to book a ride.” No screenshots, no steps to reproduce, and the issue can’t be replicated.

With Session Replay, your support team can:

• Instantly view the user’s session to see what they saw.
• Understand the context: which screen they were on, what they tapped, and what went wrong.
• Provide a fast, accurate response, or escalate with full context to engineering.

Result: Faster resolution, happier users, and fewer back-and-forth emails.

Data privacy

Dynatrace adheres to world-class standards for data protection. Mobile session data is secured just like any other captured telemetry. However, privacy configurations must still be reviewed by each customer to ensure compliance with internal and legal requirements. Like web applications, Session Replay for mobile applications offers three levels of privacy controls:

• Safest – Masks all editable text fields, labels, images, switches, and web views
• Safe – Masks all editable text fields only
• Custom – By default, behaves like Safest, but allows you to define exactly which elements or views to mask.

See configure custom masking in the preferred documentation below.

Turn on Dynatrace Session Replay for Mobile Apps

Cluster-side activation

Session Replay is now supported for both iOS (including those built in SwiftUI) and Android apps (including those using Jetpack Compose). To get started, you’ll first need to turn it on for each mobile app, as it’s managed separately at the cluster level.

To activate the feature:

1. Navigate to: Frontends → Select a mobile application → Edit → Enablement and cost control
2. Set the Session Replay Mobile toggle to on.

Once turned on, you can define the percentage of sessions to capture. By default, Dynatrace captures 100% of sessions, but you can reduce this based on your data volume and storage needs.

Session Replay for Mobile integrates seamlessly with Session Replay for Crashes. This allows you to:

• Automatically capture 100% of crash sessions
• Sample a configurable percentage of all other sessions

If you’re hosting Dynatrace on-premises, make sure to prepare for increased storage requirements before enabling this feature.

Instrumentation and configuration of a mobile application

Scenarios differ depending on the operating system, so please follow our documentation:

• Configure Session Replay for iOS
• Configure Session Replay for Android

The instrumentation and configuration process is simplified for customers who have already used Session Replay for Crashes or mobile Real User Monitoring.

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When I founded Dynatrace, I aimed to bridge the gap between IT performance and user experience. My goal was to provide IT teams with insights to optimize customer experience by collaborating with business teams, using both business KPIs and IT metrics.

To accomplish this, we traced all digital interactions from device to backend for detailed insights into personalization impacts. Using causal AI, we identified and resolved performance issues automatically. Recently, we’ve expanded our digital experience monitoring to cover the entire customer journey, from conversion to fulfillment.

Shifting to customer-centric IT  

For observability data to be meaningful, it must connect the performance of IT systems to customer experience throughout their journey, across both digital and physical touchpoints. Only then can executives understand whether their software helps to deliver the intended business outcomes.

Dynatrace has been built from the ground up to observe, analyze, and protect customer interactions end-to-end by unifying observability, security, and business data in context. This combination boosts your analytics abilities while also saving costs by consolidating observability, real-time user behavior, and session replay tools within a single platform.

Dynatrace helps executives take the same proactive approach to customer experiences by addressing the following five critical needs:

1. Understand the customer’s business process, including identification of pain points and automation opportunities.
2. Identify where the customer journey can be optimized to improve retention rates.
3. Find ways to boost satisfaction, increase conversions, and accelerate business growth.
4. Automate root-cause and customer impact analysis.
5. Accelerate complaint resolution and establish preventive measures and controls.

Avoid the cost of customer churn by optimizing customer experience

85% of unhappy customers would make the extra effort to go to a company that has better customer service. In 2024, acquiring a new customer costs five to 10 times more than retaining an existing one. Specifically, it can be up to seven times more expensive to attract a new customer compared to keeping one. Additionally, existing customers tend to spend 67% more on average than new customers.

This data speaks to the importance of investing in digital experience and loyalty, which many executives do. However, not many realize the efficiencies they can gain when data from all customer experience processes – observability, customer behavior, and business data – is in a single place, as it is with the Dynatrace Grail data lakehouse. Real-time customer experience remediation identifies and informs the organization about any issues and prevents them in the experience process sooner.

Achieve unparalleled agility and customer satisfaction

As today’s customer experiences span direct access (through web, mobile, and IoT) and indirect access (through APIs, messaging, logistics, and other forms of interactions), customer journeys are omnichannel. This shift highlights the value of observability for a complete and holistic understanding of user journeys. The steps across devices, APIs, server-side service invocations, and information from the inner workings of services can be used to gain a complete understanding of omnichannel user journeys and their associated customer satisfaction and business success.

Dynatrace unifies data from digital and physical touchpoints in a single platform and creates an end-to-end view into the following:

• The performance, reliability, and user experience supported by applications.
• The security, privacy, and regulatory compliance standards of digital services.
• The end-to-end experience for every customer throughout the entire process.

With these insights, you can act on improving the reliability, performance, and user experience of your entire customer journey. This can include live interactions as well as asynchronous interactions across all service touchpoints, whether that’s an order being shipped or a suitcase arriving at the same airport as its owner.

The Dynatrace platform’s granular insights also empower development teams to innovate more effectively so they can deliver faster change, helping executives improve customer experience.

Dynatrace’s advanced digital experience management capabilities, including Session Replay, provide unparalleled visibility into the customer journey. Our customers frequently run team meetings to visually review customer sessions to better understand issues with experiences. Typically, without session replay, if a customer experiences a problem, the IT team logs into an admin account or looks for errors in logs, but often doesn’t find anything wrong. With Session Replay, they can directly replicate what the customer saw and identify the exact problem they are describing. That result can be automatically documented and passed to the development team, providing them with full context of the problem. Session replay sessions are anonymous, having implemented highest standards in the market for privacy management.

User experiences go into many dimensions: business events, dashboards, session replay, synthetic checks which help with performance, reliability, and experience of digital interactions.

A proactive approach to analytics

One of several reasons to observe real user behavior instead of running synthetic tests is that modern applications serve different and individualized content. Personalization, user profiles, pertinent customizations, user permissions, and so forth make almost every web or mobile page unique in their behavior and how they access the backends. Hence, only deep, end-to-end insights can provide the actionable information required to improve experiences and complement common marketing-related analytics tools (e.g. Google or Adobe Analytics).

Analyzing real user behavior with end-to-end context provides value to many use cases, including the following:

• React to issues faster, automate, and quantify the customer impact with the help of Dynatrace AI.
• Optimize business outcomes (revenue/business goals vs. cloud cost and R&D effort) towards inflection points of business goal vs. experience through unified technical, experience, and business data analytics in a single space.
• Improve software delivery by observing customer success on a subset of customers first before going broad (for example, progressive delivery, dark launches, and A/B testing) with Dynatrace support for feature flags and software delivery observability.
• Eliminate finger-pointing as end-to-end visibility connects the data points across departmental needs. Finally, as an executive, you have the means to quickly identify the right team to fix and improve.
• Prioritize investments in new features vs. improvements by better understanding actual customer experiences, utilization, satisfaction, sentiment, and errors. For example, if you have too many rage clicks, you likely want to spend the next sprint on experience improvements vs. new features.
• Automate smarter using actual customer experience metrics, not just server-side data.

All of these use cases go beyond commonly used analytics tools. Dynatrace collects information from the front-end and APIs, backend, and the inner workings of services in full context.

Finally, I hear from executives that while they can leverage Dynatrace to get the best out of their data, they sometimes need additional expertise so that their teams know where to focus and what to act on. This expertise can often come in the form of a Dynatrace partner and our Business Insight team (or both). The Dynatrace Business Insights team are global experts who can help executives get to the platform’s value faster. And by leveraging precise data modeling, the Business Insights team can help executives understand how to strike the balance between optimization of customer experience and investing in new features.

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As online services become more complex, end-to-end observability that spans the full customer journey, from request to fulfillment, is becoming harder to achieve. People now depend on digital experiences for access to goods, services, and entertainment. Consequently, organizations need a way to capture and understand user behavior so they can make their services more reliable.

For the British Columbia Lottery Corporation (BCLC), end-to-end observability has become imperative for understanding and quickly responding to customer experiences. BCLC is a government ministry corporation that provides lottery, casino, and sports betting services to benefit the province’s healthcare, education, and community programs. As such, the corporation’s mission is to deliver exceptional—and healthy—gambling entertainment experiences.

At Dynatrace Perform 2023, Ben Rushlo, Business Insights leader at Dynatrace, and Navid Mehdiabadi, BCLC’s APM expert, discuss how the right business insights are crucial to making data-driven decisions and improving business outcomes.

Business Insights is a managed offering built on top of Dynatrace’s digital experience and business analytics tools. The Business Insights team helps customers manage or configure their digital experience environment, extend the Dynatrace platform through data analytics, and bring human expertise into optimization.

Journey to data-driven decisions using end-to-end observability

BCLC has been partnering with Dynatrace since 2021. Mehdiabadi explains that, though BCLC’s strategic vision isn’t fully realized yet, its number one goal is to proactively manage incidents and provide increased visibility with end-to-end observability to improve the player and employee experience.

“It’s a journey in Dynatrace,” Rushlo said. “There’s a maturity journey, and it’s not just a maturity journey within the overall company. It’s even within app teams and different parts of your organization as they are implementing Business Insights”

Before Dynatrace, BCLC was considered a reactive company. “We relied on customers (our players) to call us and let us know if something was broken and had scattered monitoring tools,” Mehdiabadi says. “Each team had their own tools, and every time we had a failure, we had to go into the war room with each team looking into their own monitoring tools trying to come up with something that might be connected to the issue and find what’s broken.”

Accessing business insights and data with precision and long-term context

After working with Dynatrace, BCLC now has a twenty-four-seven data center team with an easy-to-share, intuitive datacenter hyper wall dashboard showing the overall health of the entire system — infrastructure, applications, networks, and user experience. Mehdiabadi says the company can now easily forecast both frontend and backend data to see everything that’s going on.

Monitoring both the frontend and backend is critical to achieving its strategic goals. “Our players just see the frontend. They go on the website and play the games,” Mehdiabadi says. “And that’s all they care about. Before Dynatrace, we didn’t have a view of what’s going on with them. But now, we can see the user behavior and get the information we need, like browser version, OS version, [and] IP address.”

When players call for assistance, customer support has all of that information in front of them in real time. “We can see the player’s journey,” he says. The BCLC support team has information on the player’s entry point, which path they went through, each pass to reach a certain destination, how well the application functions, and so on. “A lot has changed and it’s a lot better now that we have a detailed view of how our players behave in the system.”

Accelerating maturity with Business Insights

Partnering with Dynatrace Business Insights has resulted in on-demand, automated real user monitoring (RUM) and end-to-end observability of their high-value, big-money players, including key metrics, session replay, and monthly reporting. To accomplish this, the Business Insights team helps customers with three major items:

1. Configuring and managing the digital experience environment, such as setting up dashboards and making sure the right data is collected.
2. Troubleshooting issues, such as when a customer turns on real user monitoring but doesn’t get the right data (e.g., the right names or the right alerts).
3. Optimizing with expert knowledge from cross-vertical teams who understand why things are running slow, issues with content delivery networks, JavaScript, and backend calls.

“We also have some big data analytics use cases that help extend the Dynatrace platform, see how performance is affecting behavior, and identify long-term trends,” Rushlo said. “I would estimate 80% of our largest Dynatrace customers use Business Insights.”

End-to-end observability is central to BCLC’s strategic vision

BCLC’s beginning goal was successful monitoring and end-to-end observability for its online gaming business, helping it gain data-driven insights to improve the customer and employee experience. The company is now extending that vision to its lottery business and brick-and-mortar casinos. “We want to bring all of them into Dynatrace,” Mehdiabadi says. “It gives us end-to-end visibility and that single pane of glass for troubleshooting.”

BCLC has started onboarding developers into Dynatrace and monitoring additional services. “Everyone is very interested in using Dynatrace during their development,” he adds. “We’ve moved on to a champion concept that every team must have a Dynatrace champion if they’re interested in using Dynatrace for monitoring.”

Harnessing user behavior analytics for data-driven decisions and insights

With visibility into front-end performance and user behavior tied to end-to-end observability, Dynatrace provides quantitative and qualitative insight for actionable answers to improve customer experience and business key performance indicators (KPIs).

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With companies across industries strengthening their digital offerings to cater to demanding customers who can switch to competitors with a few clicks, it’s imperative to make digital offerings that are more performant, feature-rich, and immersive. This necessitates that millions of microservices and thousands of apps be updated regularly per continuous delivery. When multiplied by the amount of traffic that these offerings attract, it’s nearly impossible for application developers to tie in user experience insights with errors that are discovered in production.

To complicate matters further, it’s often difficult and time-consuming to determine the impact of errors, not only to prioritize them and promptly deploy appropriate fixes but also to develop permanent solutions that will improve the experience of future users. An inability to retain customers impacts short-term conversion goals and affects long-term positive business outcomes, such as brand value.

Connect logs with user sessions and see each user’s experience

When it comes to ever-increasing customer demands, simply troubleshooting and deploying a fix is only a band-aid solution. Customers who have experienced issues in the past might have switched over to competitors already. To counter this, large teams of frontend and backend developers collaborate on log analysis and identify potential issues that could result in significant errors or crashes. Now that logs are connected to user sessions on the Dynatrace platform, practitioners have unhindered visibility into the frontend context where they can replay any user session to see exactly what went wrong. This unique ability paves the way for a few helpful use cases that proactively improve business outcomes:

• Keep in mind that the vast majority of generated logs are noise that can be ignored. Davis AI not only filters out such noisy log entries, it also prioritizes and highlights all log entries that are rich in helpful information. So addressing issues is primarily about fixing them rather than looking for them. When Session Replay is turned on, a frontend developer can gain troubleshooting insights by identifying real users and seeing what they were trying to achieve during a particular session. This is especially helpful when such information is not self-evident from the log entries.

  
  
  

• Along with frontend waterfall data, developers will have a much easier time fixing issues and focusing on strategic initiatives such as innovation. This is particularly useful when a distributed trace is missing due to sampling settings of less than 100% or when OneAgent isn’t deployed.
• Developers can track backward from specific or arbitrary user sessions. This can be useful, for example, when a customer calls in to complain about an issue they experienced. This allows developers to decipher any error or bug that results in user frustration. A developer can see why a user deviated from the happy path, or worse, why they abandoned the app. Developers can confidently determine which log lines are relevant and tie that to a real user along with the factors that resulted in the issue.
• With DevOps leaning more towards proactively preventing issues before customers become aware of them, it’s a great advantage to be able to run health checks from the Dynatrace Log Analysis dashboard.

Pushing the boundaries of understanding user journeys

Other platforms offer similar capabilities that enable practitioners to jump from logs to the frontend context. However, Dynatrace is the only solution that takes things a step further by connecting logs to the best Session Replay available in the observability space. And while point solutions may have a few additional tricks up their sleeves with feature add-ons, the combined package of having a single OneAgent that enables automatic instrumentation of all apps, across the board, frontend and backend visibility, and best-in-class digital experience monitoring is impossible to beat.

In the future, Dynatrace won’t only be able to support the storage of logs exponentially larger in volume compared to today, but the retention period will be multiple years to meet stringent criteria in certain industries. With costs becoming less of an issue, the stage is set for eliminating gaps and blind spots when it comes to understanding end-user experience.

How to get started

If you‘re curious to see this in action, find out more about activating Session Replay. You can also learn more about how Session Replay offers the highest level of data privacy.

This feature is available as of Dynatrace version 1.244.

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Businesses today are fighting fires across the DevSecOps spectrum — from staving off ever-evolving security threats to remediating slowdowns and outages. As a result, many IT teams are turning to artificial intelligence for IT operations (AIOps), which integrates AI into operations to automate systems across the development lifecycle. AIOps enables self-healing IT before problems impact operations, which makes life easier for DevSecOps teams.

Dynatrace’s AIOps platform uses causation-based, deterministic AI to spot potential slowdowns and outages before they occur and to trigger automated actions that prevent failures. Organizations can also automate diagnosis and remediation with Dynatrace’s AIOps. This automatic analysis enables engineers to spend more time innovating and improving business operations.

The combination of Dynatrace, ServiceNow workflows, and the Ansible automation platform can proactively self-heal countless workflows and critical outages. At Dynatrace Perform 2022, David Walker, a Lockheed Martin Fellow, and William Swofford, a full-stack engineer at Lockheed Martin, discuss how to create a self-diagnosing and self-healing IT server environment using this AIOps combination for auto-baselining, auto-remediation, monitoring as code, and more.

Automating AIOps with automatic and intelligent observability

An IT organization is often unaware a critical server has gone down until a user reports it. Then, the server administrator must investigate the cause, create a service ticket, and remediate the problem, which can take anywhere from minutes to hours.

An AIOps stack featuring Dynatrace, ServiceNow, and Ansible automates and shortens that process for Lockheed Martin, Walker and Swofford explain. Each piece of the AIOps triumvirate plays a crucial role in the automation process to speed innovation.

Dynatrace’s automatic and intelligent observability and causation-based AI identify the root cause of the slowdown or outage in context. This platform-based approach to observability enables IT teams to automate remediation efforts. In the event of an outage or slowdown, Dynatrace generates a ticket in ServiceNow, which manages the workflow. Dynatrace also issues a playbook request to Ansible, which begins the DevSecOps toolchain automation with a self-healing script. The script then restarts the web service and checks the server’s health.

An example of the self-healing web

For example, a typical use case involves a web server running an analytics and reporting system. If the service goes down, Dynatrace recognizes the failure and, through its integration with ServiceNow, automatically creates an IT ticket to trigger the remediation (Figure 1).

“Instead of the trigger being a failure, our trigger is a point of time before failure,” Swofford says. “Now, we know beforehand what’s going to happen. We’re actually moving our failure point to just a slowdown point or a nuisance point instead of it actually being a down service.”

The auto-generated incident in ServiceNow sends a call to Ansible Tower to initiate a remediation script. Ansible sends an API to document self-healing IT activity in Dynatrace. Then, Ansible generates the self-healing script, recovers the service, and closes the problem in Dynatrace and ServiceNow. The benefit for DevSecOps teams is the incident report allows them to conduct a root-cause analysis using the information ServiceNow receives from Dynatrace.

“Any incident we generate has a root-cause analysis,” Swofford says. “You can actually go and solve the root-cause issue instead of just [continuing to] keep resolving and remediating.”

Dynatrace AIOps solves the case of the forgotten archive

In a hypothetical scenario Walker and Swofford presented, an enterprise service director needs to access a budget report each month. But performance is typically so slow that the report doesn’t load. After several months, the service director asks the system administrators to investigate.

It turns out a colleague has been adding new records to the database without archiving old ones. That causes the size of the database to grow and performance to suffer. The employee has been asked to archive old records in the past, but frequently forgets.

The solution is to orchestrate Dynatrace, Ansible, and ServiceNow, making the server self-healing. Dynatrace Synthetic Monitoring and Real User Monitoring (RUM) are set to run every minute to provide a realistic view of the server’s performance.

Dynatrace Synthetic Monitoring shows availability, uptime, and average load and response times. The simulated user monitoring service can take these measures from locations simultaneously and across many different types of site content. Additionally, it can show response time by request, so DevSecOps teams can compare normal responses with those from the slowed-down server.

An example of service self-healing using Ansible

Dynatrace Synthetic Monitoring and RUM simulate real-life events, such as reports and database queries. Now, when someone adds new database records and doesn’t archive the old ones, Dynatrace will detect the long loading times. If the load times exceed a certain threshold, Dynatrace sends an event to ServiceNow. In turn, ServiceNow logs the service ticket, posts a message to Slack, and passes the Dynatrace data to Ansible (Figure 2). Ansible then logs into the database, archives the old records, refreshes the web server, and reports the restart to Dynatrace.

Database and application teams can perform root-cause analysis using the Dynatrace data and ServiceNow event logs. The goal is to prevent failures entirely by isolating the triggers that precede an outage or slowdown and moving remediation to a point before failure occurs. This fully automated workflow generates all the necessary data to fix the problem. Additionally, the DevSecOps team can add a failsafe process to automatically archive the old records when a colleague adds new ones.

“The cases are endless of what you can do with Dynatrace and all these things,” Swofford says. “We can kind of see before things happen.”

Intelligent AIOps automation enables healing without humans

When the enterprise service director comes back to run a critical financial report, the server is already self-healed. The whole automated process took less than two minutes — about the time it takes an admin to log into the system.

When the website goes down, an event pops up in Dynatrace and kicks off an action. Troubleshooters can see Dynatrace initiated and completed service remediation. They can also see the affected infrastructure component and walk through the sequence of events. Logs show when Linux servers were restarted, and operations engineers can dig into the steps that started the process. Additionally, the engineers can drill down into the ServiceNow alert to see how long it took to fix issues. The alert includes SLA times, events, and incidents — Dynatrace tags all details.

These metrics can show DevSecOps teams whether the problem is with Apache, the central processing unit, MySQL, or a query issue. Admins can see the factors affecting load time, such as download speed, time spent waiting, TLS handshake, TCP connect, DNS lookup, and response time thresholds.

End-to-end self-healing IT

Thresholds set in Dynatrace can trigger alerts. Ansible logs show a script kicked off a Linux server restart. ServiceNow reveals the exact message from Dynatrace that triggered the script in Ansible.

ServiceNow Service Central shows the flow from the trigger to the creation of an incident record, posting a message to Slack, launching a job template, and completing the job.

“So now when we hit our threshold, we actually have a problem initiated. That’s what we’re triggering off of now,” Swofford explains.

Ultimately, Lockheed Martin’s AIOps stack uses automation to log the entire remediation process — from the start of the slowdown to the response and a return to normal operations.

To learn more about how to speed innovation with AIOps through automation, watch the full session, “Integrated Self-Healing with Dynatrace.”

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In this post, I wanted to share how I use Google Analytics together with Dynatrace to give me a more complete picture of my customers, and their experience across our digital channels.

Whilst these tools have overlapping capabilities, I believe they are best used in parallel.

Google Analytics

Almost all marketers will be familiar with Google Analytics. For those not familiar, I use it on a daily basis with standardized reports, but I also self discover insights on the fly.

Specifically, I look at:

• How many sessions, page views, bounce rates, time on site and conversions?
• Which pages are viewed the most, how did they get to that page, and what are they doing after? i.e I selfishly look at my blog posts (like this one) and see whether LinkedIn, or Twitter, drove more traffic!
• Which channels has my users (or robots and spam for that matter) come in from (direct, search, social, email)?
• For each channel – what did they do next (convert, view more pages, bounce off)?
• Lastly, I often do a week on week or quarterly comparisons with simple date toggles so I can compare time periods.

This doesn’t fully sum up how I use Google Analytics, but for those who aren’t familiar with it, it should serve as a basic overview.

Dynatrace – understanding customer experience

Dynatrace provides some overlap with Google Analytics; specifically visits, conversions, bounce rates, and top landing pages.

My primary reason for using this additional tool-set, however, is to understand the experience of the visitors, and if there are errors, our web team can drill into these;

• What is the experience of those people coming to my site for every single user – satisfied, tolerating or frustrated?
• If I see tolerating and frustrated visitors, is it related to a region, country, device, or an operating system?
• Are these visits impacted by response time or code/application issues?
• Are marketing conversions being impacted by poor user experience?
• Are my top landing pages impacted by poor user experience? (i.e People are more likely to abandon a landing page that has a poor user experience, than a deeper page).

Digital and Business Analytics

The simplest way to understand if your users are having a good experience or a bad one is in my business dashboard which focused on both dynatrace.com and my Marketo pages.

Above I get a really simple view of user experience, bounce rates, types of users, trials and response times.

I’m also pretty fond of the user experience world map.

For me, it’s as simple as green is good, yellow not so good, and red is bad. This is a calculation derived from the response time of the application and error errors that occur during the visit. Technically it’s called Apdex and you can learn more about it here.

First impressions count – reviewing entry actions

The other simple dashboard I use, which is available by default is below.

In this view, I tend to focus on entry actions, but first impressions are critical.

For me, the most important landing pages are the homepage and paid search campaign pages. It’s critical these are fast and error-free as customers are most likely to bounce if these pages are slow.

If we see an issue, or more importantly if Davis® (The Dynatrace AI engine) picks up a reduction in traffic or an increase in errors, we are quickly able to pinpoint why and fix it.

Session Replay – See every user experience in 4K

One of the newer features to come into the Dynatrace solution is Session Replay.

Once I discovered I could query user sessions based on the pages users went to (user action name), I was hooked.

Now I have immediate feedback into how people are browsing our site and how we can improve our design.

Notice on the video below that the words are appearing slowly, which I’m not sure we would pick up without Session Replay. Also, the speed at which people scroll means we will consider A/B testing pages with far less copy.

Using Davis, the AI Engine

Lastly – I don’t even really need to drill into user experience because Davis alerts me, and our web teams if there are issues.

Just a few weeks ago I was notified of a response time degradation on one of our key pages.

What happened? We trialed Twitter advertising. For as little as $5k, we slowed our page down to a crawl. At 10+ second action duration, there is no way anyone converted (our bounce rate was 95%) and impacted our other campaigns.

So we turned it off.

Thanks, Davis!

The three most important marketing questions that Dynatrace addresses, that Google Analytics doesn’t tell me are:

1. Are my users impacted by poor user experience (slow loading pages or errors)?
2. Are my most important pages, those that I’m heavily invested in (paid search, advertising, blogs etc) responding fast enough in order to maximize conversions? (2.5 seconds is my goal!)
3. How are users engaging with the page? Are they scrolling to the bottom, reading lots of words, clicking images? Session Replay goes a long way in helping me, and our design team, optimize pages.

The questions you might ask are going to be specific to your use case and your job. Hope this helps.

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