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Applications, Behavior Learning and the Personal Touch

Though online businesses can’t offer the same sort of “human touch” as the staff at a brick-and-mortar store, they can go quite a long way toward personalizing and improving the end-user’s experience. End-user behavior learning technology provides the business with a view into how each end-user interacts with their online business services to ensure a superior user experience.

The business learns about user experiences based on past online activity, and quickly and proactively adjusts to meet expected levels of service regardless of the conditions or variables, such as for online shopping during the holiday season, when traffic peaks on many sellers’ websites.

Behavior Learning: The Key to Positive Customer Experiences

Superior, personalized online experiences happen because technology enables the business to deliver desired results based on learned behavior. IT has its own model and technology to identify “abnormal” behavior of applications and systems that affect the user’s experience and behavior. End-user behavior learning tells IT (and application owners) about each person using a specific technology or application and how the application performance affects the user’s actions.

Tools support end-user and application learning by leveraging statistical process control to gather data from multiple sources, establish patterns of behavior, and proactively detect subtle changes in that behavior. If you can monitor end-user and application behavior, and establish norms, then you can more proactively detect a performance issue. The technology can determine the impact on users and the business, isolate the cause of the problem, and drive corrective actions.

Behavior learning technology understands the systems, detects deviations from normal behavior, and provides fewer, earlier, and more accurate alerts. For example, a sluggish response time is a clear indicator that something is “misbehaving” in your infrastructure. End-user behavior learning technology tells you the expected response time based on the time of day, the day of week, load on the system, location of the user, and so on.

By understanding the expected behavior of the applications under various conditions, you can detect a slowdown before a user calls the help desk or abandons your site. You can also quickly assess the impact of new or modified application features, and changes in user traffic or system configurations.

The Starting Point: Behavior Monitoring

By monitoring and learning the normal behavior of your applications and your end users, you can understand what and how elements are being accessed and who is accessing them. If a change in end-user behavior occurs at the time of a slowdown, an alert is generated to notify an administrator or operator. By monitoring user and application behavior and establishing the norms for any given time period, you can proactively determine when changes occur in performance or behavior over time.

Real and “Synthetic” Users
End-user monitoring should extend to both the real user and the “synthetic” user. With synthetic transactions, you can simulate types of actions — setting up critical user scenarios and running them repeatedly to establish a baseline for comparing the performance for that same series of steps from one hour or day to the next. This is especially useful for assessing the availability of key scenarios and determining whether changes to the application or to the environment in which it runs will affect the end-user experience.

When combined with “real” user monitoring, you can determine if performance is impacted by other criteria, such as the volume or location of users, the actions the user takes, the use of mobile or non-mobile devices, or by a change in the application or environment that modifies or introduces new critical user scenarios.

Speed Matters
Advanced application performance monitoring solutions detect problems based on real end-user response times as soon as a single user begins to experience them, capturing all the data necessary to quickly prioritize, diagnose, and resolve the problems. You can know what problems are likely to impact your users and how to prioritize and assign them based on the issue source and the potential criticality and severity of user and business impact. Behavior learning solutions evaluate this data, identifying behavioral patterns so that you know when application response times and the end-user experiences are becoming slower ― or faster ― than usual.

End-User Behavior as a Source of Business Information

If a slowdown occurs in the volume of transactions completed, you can correlate that type of business information to the end-user and application response times. You can quickly determine if there is a potential problem and proactively investigate the issue. The performance of all the individual service components may appear to be satisfactory. Yet combined the services being delivered may not be performing satisfactorily to the end user. This combination gives you awareness of the experience and the potential impact on your business.

Monitoring Your Services in the Cloud
Understanding the real user experience is essential for monitoring your services in the cloud. In the cloud, you don’t always have access to the infrastructure and applications being delivered. If, however, you monitor the real user experience when trying to access the cloud, then you have a better sense of whether you and your customers are getting the service you paid for and expect.

More than Just a “Nice Touch”

Behavior-learning technology observes behavior with the goal of providing a positive customer experience. The technology empowers you to do a better job of identifying the root cause of problems and resolving application and infrastructure issues before they impact critical business services. The result will be greater customer satisfaction and loyalty, as well as an increased ability to attract new customers.

About David Williams

David Williams is a Vice President of Strategy in the Office of the CTO, with particular focus on availability and performance monitoring, applications performance monitoring, IT operations automation, and management tools architectures. He has 29 years of experience in IT operations management. Williams joined BMC from Gartner, where he was Research VP, leading the research for IT process automation (run book automation); event correlation and analysis; performance monitoring; and IT operations management architectures and frameworks. His past experience also includes executive-level positions at Alterpoint (acquired by Versata), IT Masters (acquired by BMC Software), and as vice president of Product Management and Strategy at IBM Tivoli. He also worked as a Sr. Technologist at CA for Unicenter TNG and spent his early years in IT working in computer operations for several companies, including Bankers Trust.

About Leslie Minnix-Wolfe

Leslie Minnix-Wolfe is the Lead Solutions Marketing Manager for Proactive Operations and Application Performance Management solutions at BMC Software. Minnix-Wolfe has more than 25 years of diverse development and marketing experience, primarily in the IT systems management domain, with a broad base of experience, especially in Business Service Management and predictive analytics. She previously held product and development management positions at several high-tech start-ups, including Netuitive and Managed Objects.

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Applications, Behavior Learning and the Personal Touch

Though online businesses can’t offer the same sort of “human touch” as the staff at a brick-and-mortar store, they can go quite a long way toward personalizing and improving the end-user’s experience. End-user behavior learning technology provides the business with a view into how each end-user interacts with their online business services to ensure a superior user experience.

The business learns about user experiences based on past online activity, and quickly and proactively adjusts to meet expected levels of service regardless of the conditions or variables, such as for online shopping during the holiday season, when traffic peaks on many sellers’ websites.

Behavior Learning: The Key to Positive Customer Experiences

Superior, personalized online experiences happen because technology enables the business to deliver desired results based on learned behavior. IT has its own model and technology to identify “abnormal” behavior of applications and systems that affect the user’s experience and behavior. End-user behavior learning tells IT (and application owners) about each person using a specific technology or application and how the application performance affects the user’s actions.

Tools support end-user and application learning by leveraging statistical process control to gather data from multiple sources, establish patterns of behavior, and proactively detect subtle changes in that behavior. If you can monitor end-user and application behavior, and establish norms, then you can more proactively detect a performance issue. The technology can determine the impact on users and the business, isolate the cause of the problem, and drive corrective actions.

Behavior learning technology understands the systems, detects deviations from normal behavior, and provides fewer, earlier, and more accurate alerts. For example, a sluggish response time is a clear indicator that something is “misbehaving” in your infrastructure. End-user behavior learning technology tells you the expected response time based on the time of day, the day of week, load on the system, location of the user, and so on.

By understanding the expected behavior of the applications under various conditions, you can detect a slowdown before a user calls the help desk or abandons your site. You can also quickly assess the impact of new or modified application features, and changes in user traffic or system configurations.

The Starting Point: Behavior Monitoring

By monitoring and learning the normal behavior of your applications and your end users, you can understand what and how elements are being accessed and who is accessing them. If a change in end-user behavior occurs at the time of a slowdown, an alert is generated to notify an administrator or operator. By monitoring user and application behavior and establishing the norms for any given time period, you can proactively determine when changes occur in performance or behavior over time.

Real and “Synthetic” Users
End-user monitoring should extend to both the real user and the “synthetic” user. With synthetic transactions, you can simulate types of actions — setting up critical user scenarios and running them repeatedly to establish a baseline for comparing the performance for that same series of steps from one hour or day to the next. This is especially useful for assessing the availability of key scenarios and determining whether changes to the application or to the environment in which it runs will affect the end-user experience.

When combined with “real” user monitoring, you can determine if performance is impacted by other criteria, such as the volume or location of users, the actions the user takes, the use of mobile or non-mobile devices, or by a change in the application or environment that modifies or introduces new critical user scenarios.

Speed Matters
Advanced application performance monitoring solutions detect problems based on real end-user response times as soon as a single user begins to experience them, capturing all the data necessary to quickly prioritize, diagnose, and resolve the problems. You can know what problems are likely to impact your users and how to prioritize and assign them based on the issue source and the potential criticality and severity of user and business impact. Behavior learning solutions evaluate this data, identifying behavioral patterns so that you know when application response times and the end-user experiences are becoming slower ― or faster ― than usual.

End-User Behavior as a Source of Business Information

If a slowdown occurs in the volume of transactions completed, you can correlate that type of business information to the end-user and application response times. You can quickly determine if there is a potential problem and proactively investigate the issue. The performance of all the individual service components may appear to be satisfactory. Yet combined the services being delivered may not be performing satisfactorily to the end user. This combination gives you awareness of the experience and the potential impact on your business.

Monitoring Your Services in the Cloud
Understanding the real user experience is essential for monitoring your services in the cloud. In the cloud, you don’t always have access to the infrastructure and applications being delivered. If, however, you monitor the real user experience when trying to access the cloud, then you have a better sense of whether you and your customers are getting the service you paid for and expect.

More than Just a “Nice Touch”

Behavior-learning technology observes behavior with the goal of providing a positive customer experience. The technology empowers you to do a better job of identifying the root cause of problems and resolving application and infrastructure issues before they impact critical business services. The result will be greater customer satisfaction and loyalty, as well as an increased ability to attract new customers.

About David Williams

David Williams is a Vice President of Strategy in the Office of the CTO, with particular focus on availability and performance monitoring, applications performance monitoring, IT operations automation, and management tools architectures. He has 29 years of experience in IT operations management. Williams joined BMC from Gartner, where he was Research VP, leading the research for IT process automation (run book automation); event correlation and analysis; performance monitoring; and IT operations management architectures and frameworks. His past experience also includes executive-level positions at Alterpoint (acquired by Versata), IT Masters (acquired by BMC Software), and as vice president of Product Management and Strategy at IBM Tivoli. He also worked as a Sr. Technologist at CA for Unicenter TNG and spent his early years in IT working in computer operations for several companies, including Bankers Trust.

About Leslie Minnix-Wolfe

Leslie Minnix-Wolfe is the Lead Solutions Marketing Manager for Proactive Operations and Application Performance Management solutions at BMC Software. Minnix-Wolfe has more than 25 years of diverse development and marketing experience, primarily in the IT systems management domain, with a broad base of experience, especially in Business Service Management and predictive analytics. She previously held product and development management positions at several high-tech start-ups, including Netuitive and Managed Objects.

Hot Topics

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...