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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To give your customers a top-quality digital experience, it’s important to make sure your applications are always working properly. Synthetic monitoring, also known as synthetic testing, can help to confirm your applications are performing as intended, and if they’re not, help you quickly figure out what’s going on. Although synthetic monitoring tools have become a crucial part of application performance monitoring, not all solutions cover all types or yield the best results.

As modern cloud architectures are evolving, so too are the ways users can interact with your applications. We’ll get into how the different types of monitoring work, but first, some background.

What is synthetic monitoring?

Synthetic monitoring is an application performance monitoring practice that emulates the paths users might take when engaging with an application. It uses scripts to generate simulated user behavior for different scenarios, geographic locations, device types, and other variables.

After collecting and analyzing this valuable performance data, a synthetic monitoring solution can:

• Give you crucial insight into how well your application is performing
• Automatically keep tabs on application uptime and tell you how your application responds to typical user behavior
• Zero in on specific business transactions — for example, by alerting you to issues users might experience while attempting to complete a purchase or fill out a web form

How does synthetic monitoring work?

In synthetic monitoring, a robot client application that has been installed on a browser, device, or computer transmits a series of automated transactions to your application. These server calls and testing scripts simulate an end user’s clickstream as they navigate through key areas of your application. Typically, they run every 15 minutes, but you can configure them for different frequencies or to run immediately based on a specific action.

Once the robot client receives a response from your application, it reports the results back to the synthetic monitoring system. If the client detects an error during one of its regularly scheduled synthetic tests, the monitoring system will ask it to run that test again. If the follow-up test also results in an error, then the monitoring system will consider the error confirmed and escalate it within the organization as appropriate.

Teams can configure synthetic monitoring tools in various ways according to a company’s requirements. For example, you can set up a robot client on a machine that’s located behind your firewall to confirm that the internal environment is running as you expected, or you can deploy a robot client to a computer outside the firewall to get a sense of how well an application is performing. If you want a more comprehensive view of application availability and performance, you can configure several robot clients on browsers in multiple locations.

Synthetic monitoring vs. real user monitoring

Synthetic monitoring is often compared with another application performance technique known as real user monitoring (RUM). As the name suggests, RUM tracks actions taken by actual users instead of emulating them. Organizations often implement RUM by injecting JavaScript code into a webpage and then collecting performance data in the background as actual users interact with that page.

So, what is synthetic monitoring typically used for, and when might a business decide to use RUM instead? Synthetic monitoring is often helpful to identify short-term performance issues that may impact the user experience while an application is still under development. Early detection helps businesses nip potential performance issues in the bud. This approach is handy for regression testing and production site monitoring, for example. Real user monitoring, by contrast, can help a business understand long-term trends in an application’s performance after it has been deployed.

Why use synthetic monitoring?

If your application doesn’t perform well when your customers try to use it, they will quickly leave in pursuit of a better customer experience. This could play out in a variety of ways. For example:

• High bounce rates. Your website might take too long to load, resulting in a high bounce rate. Or, you might be lagging behind your competitors when it comes to application performance without even knowing it. This will hurt your ability to acquire new customers and grow your market share.
• Difficulty troubleshooting. Even when your organization is aware something is amiss with an application, it may not know where to begin troubleshooting. When it comes to application performance, IT teams can’t always get to the bottom of what’s going on quickly — especially when they’re overextended and juggling several priorities. And while your people are in the dark and searching for answers, your organization could feel an immediate and significant impact on its bottom line.

Emulating user behavior paths in a test environment helps you avoid these issues so you can:

• Monitor system health. Synthetic monitoring can tell you if your website is available, how fast it’s running, if key transactions are functioning as expected, and where a potential slowdown or failure might lie.
• Improve performance. Over time, synthetic monitoring can give you performance benchmarks, highlighting areas for improvement and optimization.
• Prevent issues early. You can also use synthetic monitoring to find and fix potential errors before they affect your users, raising the bar on the user experience. This is particularly useful in continuous integration and continuous deployment (CI/CD) environments.
• Increase resiliency. Synthetic monitoring can also help you prepare for peak traffic periods or anticipate performance requirements in a new region or market.

Synthetic monitoring tools are also useful for making sure you’re honoring service level agreements (SLAs) with your end-users. If an issue comes up involving third-party providers, you will be better equipped to hold them accountable, as well.

Types of synthetic monitoring

Synthetic monitoring usually includes three types: availability monitoring, web performance monitoring, and transaction monitoring.

• Availability monitoring enables an organization to confirm that a site or application is available and responding to requests. Availability monitoring can also use a more granular approach — for example, by checking to make sure specific content is available or that a specific type of API call is successful.
• Web performance monitoring typically looks at specific web metrics such as page load speed and the performance of specific elements on a webpage. It checks web content, errors, and sluggish response times.
• Transaction monitoring attempts to complete specific transactions such as logging in, completing a form, and checkout.

Within the realm of synthetic monitoring, there are also two main categories of synthetic tests:

• Browser tests – a robot client simulates a transaction a user might attempt (such as making a purchase)
• API tests – an organization monitors specific endpoints across each layer of the network and application infrastructure

Within API tests, there are different types of tests, including HTTP, SSL, and DNS. For example, API tests often use HTTP tests to monitor application uptime and responsiveness. Meanwhile, SSL tests confirm if users can securely complete transactions on a site using valid SSL certificates, and DNS tests make sure the site’s DNS resolution and lookup times are within expected parameters. A company might use multiple API tests to monitor whether a specific workflow is working properly from end to end — this type of API monitoring is called a multistep API test.

Challenges of synthetic monitoring

Modern applications are inherently complex. Because users access them from a variety of locations and contexts, synthetic monitoring is often not comprehensive enough to account for all the potential errors or situations that might arise. DevOps teams are accounting for this problem by placing a higher priority on introducing application testing earlier in the software development life cycle. However, synthetic monitoring is still often difficult to properly set up without specialized technical knowledge, and it is time-consuming even for the team members that have the required skill set.

Synthetic tests aren’t very resilient, and they can easily fail when small UI changes are introduced, generating unnecessary alert noise. This means that whenever a minor application element such as a button is changed, the corresponding test must be, too. And lastly, many synthetic monitoring tools lack the context needed to explain why a specific failure happened or what the business implications might be, lengthening time to resolution and making it unnecessarily difficult to prioritize application performance issues.

Benefits of synthetic monitoring

Proactive Monitoring: Synthetic monitoring allows you to proactively spot performance issues and availability problems. By imitating user interactions, it identifies irregularities before they impact real users. This early detection helps prevent potential outages and ensures a smoother user experience.

Global Testing: You can assess your application’s performance in various locations. Synthetic tests run from multiple regions, providing insights into regional variations in performance.

Browser and Device-Specific Testing: Synthetic monitoring lets you evaluate your application’s behavior across different browsers and devices. This helps identify compatibility issues and ensures consistent performance for all users.

Works Inside and Outside the Firewall: Unlike Real User Monitoring (RUM), which relies on actual users, synthetic monitoring can be completely automated and run inside and outside your organization’s network. This flexibility ensures comprehensive coverage.

Automated with Regular Frequency: Synthetic monitoring can run at regular intervals, such as every minute or hour, 24/7. This continuous monitoring ensures timely detection of any performance degradation.

Synthetic monitoring tools

A good synthetic monitoring solution should give your organization complete, 24/7 visibility into your applications. To accomplish this, it should include the following kinds of synthetic monitors:

• Single-URL browser monitors. A single-URL browser monitor simulates the experience a user would have while visiting your application using an up-to-date web browser. When run frequently from public and private locations, a browser monitor can alert you when your application becomes inaccessible or when baseline performance degrades significantly.
• Browser click paths. Browser click paths also simulate a user’s visit, but they monitor specific workflows in your application. An advanced synthetic monitoring solution can let you record the exact sequence of clicks and user actions you want to monitor, then set the browser click path to automatically run at regular intervals.
• HTTP monitors. HTTP monitors are useful for monitoring whether specific API endpoints are available, and they can also perform straightforward HTTP checks to confirm single-resource availability. HTTP monitoring tools should allow you to set up performance thresholds for HTTP monitors, too.

Synthetic monitoring use cases

Financial Services

Online Banking Systems: Synthetic monitoring ensures that online banking platforms remain available and responsive for users.

Payment Gateways: Monitoring payment gateways helps prevent transaction failures and delays.

Trading Platforms: Synthetic tests verify the performance of trading systems, which are critical for financial institutions.

Healthcare Technology

Electronic Health Record (EHR) Systems: Synthetic monitoring ensures EHR systems are accessible and responsive for healthcare professionals.

Patient Portals: Monitoring patient portals helps maintain seamless communication between patients and healthcare providers.

Telehealth Platforms: Synthetic tests validate the reliability of telehealth services, especially during high-demand periods.

General Web Applications

Availability Testing: Proactively detect failures even when there is no user traffic (for example, off business hours).

API Endpoints: Monitor the availability and performance of third-party API endpoints.

How Dynatrace can power your synthetic monitoring

If you’re thinking about better understanding how your applications are performing, you might be wondering what synthetic monitoring tools you need to get started. You’ll want to pick a solution that simulates business-critical journeys through your most important applications across your mobile and web channels. This can give you immediate answers to questions about application availability and the impact it’s having on the user experience. Your synthetic monitoring solution should also be able to help you quickly identify the root cause of any application performance issue so you can resolve it as soon as possible.

Dynatrace Synthetic Monitoring provides all the information you need to know the moment an application’s performance falters. By using all major desktop and mobile browsers to simulate user activity, Dynatrace helps ensure that web, mobile, cloud, and streaming transactions go smoothly for customers around the globe.

This is key for evaluating whether applications meet your SLA requirements, and it can determine whether business outcomes have been impacted. It can also eliminate troubleshooting through AI-driven automation, as well as rank problems in order of importance to the business — significantly reducing the time required for your IT team to identify and address root causes.

To catch those longer-term trends, Dynatrace RUM uniquely captures the full visibility of the customer experience to eliminate user experience blind spots, and Session Replay provides indisputable video evidence of the complete digital experience, so business, development and operations stakeholders can collaborate and agree where to make improvements.

These advanced digital experience monitoring capabilities help you proactively identify and address application performance issues from anywhere in the world. With the right synthetic monitoring solutions in place, your business can go a long way toward ensuring a consistent, satisfying customer experience.

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We’re proud to announce that Ally Financial has presented Dynatrace with its Ally Technology Velocity with Quality award. Ally Financial is the home of the nation’s largest all-digital bank and is an industry-leading auto financing business.

This is the second time Ally Financial has presented its Ally Technology Partner Awards. Specifically, the company recognized five third-party suppliers for delivering outstanding service excellence across various criteria that align with Ally’s core values and performance standards. These criteria include operational excellence, security and data privacy, speed to market, and disruptive innovation.

High monitoring costs and limited visibility drive the need for innovation

Ally Financial uses AI-powered observability for monitoring and automating its technology stack, from its cloud and on-premises infrastructure to its applications and customer digital experiences.

But as a company with a mission to “Do It Right” and be a relentless ally for customers and communities, the high-cost monitoring solutions it was using provided only limited insights into end-user experiences. Ally’s goal was to reduce the number of monitoring tools it was using and its annual spend while gaining better, more actionable—and more automatable—insights into systems that affect customer experiences.

Full-stack observability resolved problems, consolidated tools, and reduced costs

Ally became a Dynatrace customer in 2023. Within hours of starting Dynatrace, the team was solving long-standing problems. They quickly adopted full-stack monitoring and real user monitoring (RUM). With the insights they gained, the team expanded into developing workflow automations using log management and analytics powered by the Grail data lakehouse. As a result, Ally is driving a new level of operational efficiency and saving millions in annual licensing costs.

“We partnered with the Dynatrace team to consolidate our observability stack, allowing us to enrich metrics, logs, events, and traces with predictive analytics in a unified fashion across all channels,” said Jason McMunn, Director of System Engineering at Ally Financial. “This resulted in significant savings and much faster ROI. Moreover, we’re able to build automated workflows that help our teams resolve problems, operate more collaboratively and efficiently, deliver software faster, and delight our customers with world-class digital customer experiences.”

For Dynatrace, the Ally award is a cause for end-to-end celebration. “We’re excited Ally Financial has recognized Dynatrace as its Technology Partner of the Year,” said Matthias Dollentz-Scharer, Chief Customer Officer at Dynatrace. “Ally is an agile, modern financial services enterprise that has etched unified observability, AI, and analytics into the core of its cloud strategy. Indeed, by helping their team achieve an end-to-end view of their entire cloud environment—including front-end applications, mobile app experiences, and underlying infrastructure—we are proud to help Ally redefine digital banking.”

The innovation is mutual

The Ally Technology Partner Awards are a way for the company to acknowledge its exceptional partners. “We are proud to honor the vendor partners that play a significant role in our achievements at Ally through the Ally Technology Partner Awards,” said Sathish Muthukrishnan, chief information, data, and digital officer at Ally Financial. “Superior execution, quality, and partnership are showcased by each winner, which we value here at Ally as we aim to provide a best-in-class digital banking experience.”

Earlier this year, Dynatrace presented Ally Financial with its own award as our first Digital Breakout Performer. We present the award to customers who have begun their journey with Dynatrace in the last 12 months and immediately recognize a tremendous return on investment from unified observability, AI, and analytics.

Ally Technical Velocity with Quality award promises more innovation ahead

Receiving the Ally Technical Velocity with Quality award confirms the Dynatrace commitment to delivering customers the tools and technologies they need to make software work perfectly.

Dynatrace is especially proud to support innovators like Ally Financial. “The team at Ally is driving incredible efficiency as they continue to consolidate monitoring tools,” Dollentz-Scharer said. “Ally continues to push the envelope to further monitor their cloud infrastructure costs. I’m thrilled to see what’s in store for Ally Financial.”

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A business process is a collection of related, usually structured tasks or steps, performed in sequence, that achieve a defined business goal. Tasks may be manual or automatic, and many business processes will include a combination of both. Business processes are important because they improve the efficiency, consistency, and quality of the business outcome.

Monitoring business processes is one thing organizations can do to help improve the key business processes that enable them to provide great customer experiences. Business process monitoring refers to continuously tracking and analyzing key performance indicators (KPIs) from relevant process milestones. The goal of business process monitoring is to provide real-time visibility into the performance of a business process, including end-to-end delays so that stakeholders can quickly identify and respond to issues as they arise, and drive business outcomes that will deliver a better customer experience.

Benefits of business process monitoring

Business process monitoring enables organizations to understand how an end-to-end process is performing and pinpoint where in the process they can make improvements. Business process monitoring helps organizations:

• Increase efficiency by identifying and addressing bottlenecks or inefficiencies that may slow down a business process.
• Improve quality control by tracking KPIs and identifying areas where quality may be lacking to enable corrective action.
• Improve customer satisfaction by improving processes to provide customers with faster and higher quality service.
• Make better decisions by providing managers with real-time data about the business.
• Reduce costs. Organizations can reduce their operating costs and increase their bottom line with more efficient and better processes.

Digital transformation increases the importance – and challenges – of business process monitoring

Most organizations rely on many business processes across different departments to meet their goals and deliver outcomes to their stakeholders, whether customers, partners, or employees. As organizations continue to undergo digital transformations, more and more of their business processes are dependent on increasingly complex digital technologies. In fact, most business processes still rely on multiple systems, long ago outgrowing the capabilities of built-in platform-centric monitoring. This leaves business leaders with incomplete visibility into these critical business assets.

Approaches to achieve end-to-end visibility have met limited success, in part due to these common challenges:

• Business data is scattered across multiple systems, with inconsistent formats and different means of access. Code changes are often required to expose important business data, delaying implementation. Fragile data pipelines introduce ongoing maintenance overhead.
• Data at rest, the source for many pipelines, can be stale, often by days or longer, preventing real-time business agility.
• Business data lacks connection to the supporting IT context, limiting effective collaboration between business and IT teams. Consequences include delayed anomaly detection and missed optimization opportunities.

The results can include delayed, incomplete, and disconnected views of business process health, impacting a range of stakeholders:

• Business leaders lack real-time visibility into some of their most important assets.
• IT teams lack insight into how the systems they manage impact business outcomes.
• Customers experience product and communication delays.
• Opportunistic competitors encroach on market share.

Traditional approaches to business process monitoring must evolve to provide the end-to-end visibility, IT context, and timeliness that organizations need.

Business process monitoring examples: A retail use case

It can be helpful to put business processes in the context of a specific type of business or industry. For example, consider three common retail industry business processes that must work together efficiently to meet customer expectations:

• Inventory management to anticipate and meet dynamic customer demand
• Order processing workflow triggered by customer orders
• Order fulfillment to deliver orders to customers

Anomalies or delays anywhere in these business processes can impact customer satisfaction and revenue – yet we know these anomalies will occur.

• Without timely inventory data, business owners may be unable to respond in real time to supply chain issues or sudden shifts in customer behavior.
• Without IT context, business owners may not be able to identify the root cause of order processing failures.
• Without viewing the business process as an asset, IT teams will have little understanding of business process health, instead relying on isolated system health.

While the examples above illustrate one industry, it’s easy to see how similar processes or flows would extrapolate to other industries, such as a financial transaction workflow, applying for a loan, or booking and checking in for a trip.

How Dynatrace helps improve business process monitoring

Business Observability helps organizations across all industries gain visibility into their business processes, overcoming many of the challenges outlined above. With Dynatrace, organizations benefit from one AI-powered data platform for unified observability, security, and Business Observability, providing real-time observability for data-driven business decisions. The ability to capture business data from anywhere, whether that’s OneAgent, real user monitoring sessions, log files or external tools and data sources, simplifies access to the real-time, precise business data organizations need for better visibility into their business processes.

With access to topology metadata to automatically enrich business events, Dynatrace enables a straightforward approach to business process monitoring that goes beyond traditional methods, putting individual business process steps in context with business and IT data. Organizations can visualize an entire business process through a purpose-built Business Flow application or a custom dashboard, leveraging Davis AI for root cause analysis and Smartscape to drill down into host and process details.

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What is customer experience analytics: Fostering data-driven decision making

In today’s customer-centric business landscape, understanding customer behavior and preferences is crucial for success. Customer experience analytics is the systematic collection, integration, and analysis of data related to customer interactions and behavior with an organization and/or its products and services. The analysis of this data offers valuable insight into the overall customer experience, enabling businesses to optimize their strategies and deliver exceptional experiences.

Customer experience analytics best practices

As organizations establish or advance their customer experience analytics strategy and tools, the following five best practices can help maximize the benefits of these analytics.

1. Define clear objectives

Establish clear objectives and identify specific insights you want to gain from the data. For example, are you looking to understand customer preferences, improve satisfaction, or identify pain points in the customer journey? Defining clear objectives will guide your analysis efforts and help maintain focus on extracting the most relevant and actionable information. It will also help to gain alignment among the necessary stakeholders across executive leadership, digital, product, development, or analytics teams.

2. Capture and consolidate data from multiple sources

To get meaningful insights, it’s crucial to collect comprehensive and relevant data by capturing data from various touchpoints and channels that customers interact with. This may include digital experience monitoring, such as mobile or web real user monitoring, product analytics, website analytics, customer relationship management data, customer feedback, Net Promoter Score (NPS), and more. The data should cover both quantitative metrics (e.g., purchase history, and clickthrough rates) and qualitative feedback (e.g., surveys and reviews). By gathering a range of data, organizations can develop a holistic view of customer journeys and uncover meaningful patterns and trends.

3. Use advanced analytics techniques

Customer experience analytics goes beyond basic reporting. Embrace advanced analytics techniques to unlock deeper insights. Employ segmentation to group customers based on shared characteristics, which allows you to tailor experiences and strategies to specific segments. Implement predictive modeling to forecast customer behavior and identify opportunities for personalized engagements. Embrace sentiment analysis to understand customer emotions and gauge satisfaction levels. With advanced analytics techniques, organizations can extract greater value from data and ultimately make better data-driven decisions.

4. Integrate data sources for a unified view

Customer experience analytics often involves analyzing data from multiple sources. To ensure a unified view of the customer journey, it’s important to integrate these disparate data sources. This integration allows you to connect the dots and gain a comprehensive understanding of customer behavior across touchpoints. Consider how easy it is to integrate different tools and data sources. For example, you may benefit from enriching digital experience monitoring data with insights from web analytics or tracking every step in a business process regardless of the data source – to understand the end-to-end customer experience.

5. Foster a culture of data-driven decision making

To make the most of customer analytics, it’s crucial to foster a culture of data-driven decision making within your organization. Encourage cross-functional collaboration and ensure that decision makers have access to relevant insights. Train employees how to interpret and use customer analytics effectively. Regularly share success stories and case studies that demonstrate the impact of data-driven decision making on customer experience. By instilling a data-driven mindset, organizations empower teams to make informed decisions that drive improvements in customer experience.

Driving decisions with data

Customer experience analytics has the potential to transform how organizations understand and optimize customer interactions. By following these best practices — by defining clear objectives, collecting comprehensive data, using advanced analytics techniques, integrating data sources, and fostering a culture of data-driven decision making, you can extract the greatest value from customer experience analytics. Embrace the power of data to gain actionable insights, enhance customer satisfaction, and drive business growth in today’s competitive landscape.

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Driving better business outcomes has more organizations focusing on the customer journey. “Within the past few years, differentiating through customer experience has become a corporate mandate,” says Gary Kaiser, Product Manager of Business Analytics at Dynatrace.

And it’s easy to see why. One report found that companies that adopt a customer-centered mindset are 60% more profitable than companies that don’t. From the users’ side, 77% of consumers reported that poor customer experiences diminish their quality of life.

“Our roles as IT monitoring professionals have expanded to embrace collaboration with the business users,” Kaiser explains at the recent Dynatrace Perform 2022 conference. But in most organizations, IT and business teams work in silos.

Along with Dynatrace Insights Analytics Manager Adam Russo, Kaiser discusses the importance of customer experience along the customer journey and explains how IT teams and business stakeholders can collaborate. “The business users own the digital experience strategy, but depend on us for insights,” Kaiser says.

IT metrics vs. business goals

To align with business users, an organization must first conduct a business impact analysis to understand the goal of an application and determine the number of affected users. “If you’re being proactive, you might look at an Apdex score to identify high-volume pages with lower scores, which may have a large impact on users,” Kaiser says. Although important, these starting points provide IT metrics, not business metrics.

To understand how IT metrics relate to business goals, teams must ask: “Does this metric impact business outcomes?” If the answer is yes, then consider the following questions:

• Is the application customer-facing or internal?
• Are the users geographically relevant buyers or browsers?
• Are these conversion pages with key interactions or incidental pages with less impact?
• How do you measure customer experience?

IT teams often think about conversions, which carry across all industries. For example, a bank conversion occurs when someone opens an account. An insurance company conversion happens when someone files a claim.

However, it is important to consider the entire funnel or the customer journey from when a user enters a site down to the conversion.

KPIs that focus on customer experience and business context

Associating KPIs with these different user interactions can create a foundation for many business analytics use cases. “We want to go beyond a simple count of conversions and provide some business context or business value,” Kaiser explains.

This process is relatively straightforward because most organizations have already identified and codified business tracking goals in the website data layer. They may categorize these business goals as follows:

• Transaction data: Product, quantity, and cart value
• Behavioral data: Page views, scrolls, and clicks
• Audience segment data: Loyalty status, characteristics of users, and geographical data.

With defined goals, any tool can take advantage of this data or a subset of data to obtain customer experience analytics. One example is Adobe Analytics, which uses data enrichment and data cleansing in the UI. But many of these tools don’t capture the whole picture. “Typical use cases with Adobe share a common problem we see, which is lack of visibility into all functional errors,” Russo explains.

How to overcome lack of visibility into the customer journey

Three common reasons for this lack of visibility are the following:

1. Cascading style sheet (CSS) selectors may be overly complex and setting up a property is not possible
2. Action names don’t match between Adobe and Dynatrace
3. Naming rules might be difficult to manage because of the structure of the uniform resource identifier (URI).

But organizations can solve these problems in the following three ways:

1. Pushing errors to the data layer
2. Define Adobe custom insight conversion variables (eVars)
3. Capture Dynatrace Real User Monitoring (RUM) as a user session property

You can also pull Adobe pagename and pagetype variables, which are common across the industry and apply to naming rules.

Using these methods, teams can use Dynatrace to achieve faster visibility and automatically identify root causes of customer experience problems. Using Session Replay, teams can easily filter errors in user sessions and clean user action names using synchronous data between Adobe and Dynatrace.

Tracking the customer journey: Adobe data layer use cases

“The data layer is a great starting point for business analytics,” Kaiser says. “Many business analytics use cases can be solved exclusively through metrics and context available through the data layer.” If an organization has RUM or Digital Experience Monitoring (DEM), they already have access to this data. Other data sources include real user sessions, application business logic, and log files.

The first use case involves pushing errors to the Adobe layer and capturing them within Dynatrace.

“There are specific error codes related to specific actions,” Russo says. “Then, we can go from there and filter user sessions, then dive down and see which users are being impacted by these errors.”

Another use case demonstrates how Dynatrace can enable both IT and business teams to look at the same customer experience data from different angles. “Marketing folks may use ContentSquare to measure behavior analytics, while IT uses Dynatrace to measure performance analytics,” Russo explains.

In this case, Dynatrace captures properties from ContentSquare as Dynatrace user session properties. “We’re looking at behavioral data,” says Russo, “but we’re taking into account the performance impact on that user behavior.” As a result, IT analysts can understand the effects of a problem on the customer journey, and business analysts can understand its root causes.

Gaining insight into the customer experience using APIs

You can extend insights beyond the data layer by ingesting other data sources, metrics, and context from external business tools using an API. One example is Voice of the Customer (VoC) data. “A VoC solution allows a customer to provide feedback about their customer experience, either while they’re navigating a site or afterward through a survey,” Kaiser explains. “Some of that data can be valuable to IT.”

For example, a customer may rate website performance with three stars and give usability one star. Often, there can be a days-long delay between when a user submits feedback and when teams analyze, categorize, and escalate it to IT.

Using the API, you can directly ingest VoC metrics into Dynatrace so IT analysts receive instant feedback about IT-relevant ratings. With the two tools connected, teams can switch contexts and investigate individual complaints.

“You can alert on these or graph them over time to look for trends,” Kaiser explains. You can also drill down in Dynatrace and identify the underlying problem.

“The message is to start thinking about the business tools your business peers rely on, that they use in your organization, and what business metrics, what business context those tools might have,” Kaiser explained. Then, they can bring those tools into Dynatrace to speed up and enhance critical insights for business leaders and peers. The result is a better customer journey.

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