Four Use Cases for Leveraging Business iQ

The application and the business have converged.

In fact, the performance of your business is now inseparable from the performance of your apps. Customers who are connected to the code you write or the applications and infrastructure you manage demand a flawless experience, and they are loyal to the brand that delivers it. The challenge, however, is that the traditional ways of managing services and operations are falling short, jeopardizing business success.

Many BI tools today help analyze business data, but they are mostly for historical analysis and trends. Web analytics tools on the other hand help analyze customer conversion rates and how end-users are using your website, but don’t tell you why it’s happening. And then there are traditional APM tools that tell you whether your applications are healthy or performing poorly, but offer little visibility into the impact on your business. As a result, many organizations are struggling to connect data to business outcomes.

Business iQ offers real-time context from customer to code – connecting application performance data to business outcomes to enable both the business and IT.

To see how you can leverage AppDynamics Business iQ, check out these four common use cases.

Business Health

Let’s take a scenario where there is a major event, like Black Friday or a launch day for an important product, or simply any day you need to win customers. If you are using AppDynamics for your APM solution, your DevOps may receive alerts about anomalies in your application’s performance. When this happens, business owners may want to understand the impact on key business drivers, as well as any revenue and customer experience implications. With Business iQ, you can monitor critical business KPIs to get real-time insight into the health of your business.

Figure 1

Using Figure 1 (above), let’s say you are an e-commerce site and manage a number of different brands. Overall, you care about your site’s conversion rate, number of orders processed, total sales, and the percentage of customers moving to your loyalty program.

It can be inferred from the dashboard that in the last hour, ‘Total Sales’ may be declining since not many of your loyal customers are shopping today. What’s more, you can also see from the dashboard that there’s a clear correlation between the drop in sales revenue and the the % errors in APDY Electronics. However, with just a 1% error in APDY Books, there may be a business problem impacting sales versus an IT issue.

With this level of insight, DevOps teams will be able to investigate root-cause for the performance issue, or declare that it’s not an IT problem. Business health monitoring attempts to converge business data with application and infrastructure data to give you visibility into business KPIs that allow you to diagnose and fix problems in real time.

User Journey

Now that we’ve covered business health monitoring, let’s move on to our second use case: User journey monitoring, which measures how business components and customer experience come together to drive top-level KPIs. Figure 2 (below) helps illustrates this use case:

Figure 2

Let’s say you’re a bank that would like to understand how your users are moving along the loan processing journey – from viewing rates online, submitting an application on your website, running a credit check, and finally getting the loan approval.

Business teams might be interested in knowing how many customers are in the loan journey, where there are drop-offs, and how KPIs are impacted. Your operations team, however, may be curious if customer drop-offs are a result of slow application performance. And lastly, from a developer standpoint, you may want to know how you are impacting a larger process and causing real-business impact.

In the above dashboard, you can see that a longer response time during the “Submit Application” step at 7s, is probably causing a higher drop-off, and therefore impacting the loan amount processed at $10M. Furthermore, a 15% error rate at “Credit Check” is further compounding this problem at the “Loan Approval” stage.

User Journey Monitoring allows you to visualize different parts of a process, driving a common language between business and IT, whether you are a bank looking to optimize your processes or a retailer trying to visualize how your customers shop online.

Customer Segment

Interested in understanding the end-to-end experience of your critical customer segments? With Business iQ, you can. Check out the use-case below for customer segment monitoring.

Figure 3

Let’s say you’re a travel company that connects back-end travel inventory (think flights, hotels, etc.) to multiple front-end buying channels (think websites used to book travel, like Expedia, Orbitz, Priceline, etc.) With Business iQ, you can compare customer experience across these various buying channels, and segment customers based on error codes, slow transactions, and more. You can also analyze customer experience across various travel agents or hotel brands.

This deep-level end-user monitoring is critical for businesses, as it allows you to monitor customer issues so you can proactively avoid them in the future.

Your DevOps team might also be interested in customer segment monitoring to understand where to prioritize troubleshooting efforts. For example, by looking at the above dashboard, it’s clear that Priceline customers are experiencing issues with reservation confirmation and search availability, and that the “5 Star Luxury” hotel class segment has the highest error reservations. This information allows DevOps teams to have visibility into how their critical customer segments are performing and prioritize what they want to work on.

This capability allows your business to get visibility into how application performance impacts customer interaction with your features.

Release Validation

You can also use AppDynamics in real-time as you release newer versions of your application, or migrate from a legacy infrastructure to a new infrastructure. Business iQ also allows you to compare KPIs from your previous and current versions.

Figure 4

Let’s consider this example using Figure 4 (above): APDY media has an entertainment site where customers sign up for subscriptions. The journey they go through starts with creating a profile, selecting their favorite content, setting alerts on what content they want to be notified about, and finally, subscription confirmation.

Looking at the above dashboard, it is evident that in Version 1.0 of APDY media, the subscription rate starts to decline significantly, and it appears to be linked to a performance issue when selecting “Favorite Content.”

You can use Business iQ to help identify the problem and understand where to fix the issue. You can also use Business iQ to compare releases and identify if the problems you wanted to fix in your latest release are indeed fixed. You can do this by seeing if performance in the “Favorite Content” step improved post-release and how it correlates to an increase in conversion.

You can also see from this dashboard that while you are sending a smaller amount of traffic to Version 2, you still managed to triple your conversion rate while also driving much higher subscriptions.

The above use cases are just some of the common scenarios we are seeing in our customer environments. As you try our product, you’ll learn that there’s a lot more you can achieve with Business iQ.

Harish Doddala is leading product growth and adoption initiatives of Business iQ at AppDynamics. He has over 10 years of Product Management and Software Engineering experience delivering results for Cisco, VMware, and Oracle.

A Look Back Before Leaping Forward: How We Got Here and Where We’re Heading

Blackberries, Blockbusters and AS400s ruled supreme back when we were building the company nine years ago. At this time, most phones didn’t have GPS, most shopping was in person and most computing happened in one place. It seemed like much simpler times, right? Yet massive disruption was on the horizon that would completely shake up how people used and thought about technology.

Brace yourself – SaaS is coming. This radical movement proved that abstracting complexity can not only free businesses from fretting over the nuts and bolts of infrastructure, but it can also free them to think bigger about what they can accomplish through technology. This was a huge wake up call for our entire industry, and became my obsession, and our inspiration for AppDynamics.

What if the principles of SaaS were applied to monitoring solutions? What if stripping away complexities of reporting and alerting about applications could free businesses in a similar way?

After many late nights working out how software can be more of a business enabler and less of a management burden, came the invention of our machine-learning powered Business Transaction, the foundation of AppDynamics.

It’s hard enough for businesses to stay on top of the latest trends and shifting needs of consumers, managing applications should come secondary to hitting business goals. So, we engineered our product with business performance as the top priority. By pairing the right business metrics with the noise-cancelling abilities of machine learning, the root cause of business-impacting problems are brought to the forefront and many intricacies of related symptoms are collapsed underneath. As a result, enterprises get a straightforward, dynamic baseline that intelligently evolves with the business. And, for the first time, the world’s most complex systems can transform into real competitive advantages.

As time went on, digital strategies became synonymous with business strategies and consumer expectations rose to a point where “next-day” isn’t fast enough. To keep up with the pace set by titans like Apple, Google and Amazon, enterprises entered uncharted territories in cloud, DevOps and IoT causing new levels of strain on technical teams. On top of that, these developers, IT pros and CIOs were challenged to defend these changes to business colleagues who are asking if it’s worth their time and money.

The evolution of enterprises’ needs have always been the fire for our innovations and today’s announcement is no exception. With systems continuing to sprawl, businesses need a way to make sense of it all – from the depths of networking to the edge of multi-cloud. So we’re widening our scope to capture exactly how devices and the network impact the business. Another side effect of distributed systems are blind spots in customer interactions, which make it harder for CIOs to map customer journeys. To help provide a more complete view, our vision for the next generation of Business iQ is to link various distributed business events for a fuller picture that can boost opportunities to stay competitive in customer experience.

With the unrelenting rush of data coming in from countless sources, we see machine learning as the next big disruptor on the horizon. Machine learning, which sounded like science fiction not too long ago, has reached critical mass in its abilities to spot patterns for predictive analytics and automation. It can also be found in our latest announcement simplifying troubleshooting to a click. With new devices coming out daily, we don’t see data slowing down anytime soon, so expect to see more developments in machine learning from us that will help enterprises achieve the scale and speed needed to take on whatever is next in this on-demand, data-driven world.

Just how complex can a Login Transaction be? Answer: Very!

People in our industry always talk about IT complexity and cost. Cost is pretty easy to calculate, because IT budgets are allocated and audited every year. Complexity is very different–we know it exists, but we can’t really see or measure it. Complexity is often when our brain tries to understand something and stalls in the process, trying to make sense of information that has never been seen before.

Well, this happened to a few of us in AppDynamics last week. A customer was kind enough to share how a single login business transaction flowed across their entire infrastructure. You might be thinking: “How can a login transaction be complex? That’s just a simple call to an LDAP or SiteMinder tier”–which is pretty much what we all thought it was. However, the screenshot that graced us was one of shock, beauty and amazement. In fact, I’m looking at it right now before I scrub the customer details, and I’m still thinking “Hmmmm, this is bonkers.”

Without delaying further, here is that very screenshot showing the Login Business Transaction:

Scary huh? What you see is the flow and timing of a Customer Login business transaction as it executes across a well governed, regulated, SOA environment consisting of many services (denoted by the Java Tiers). The Customer Login transaction begins at the Java node to the right marked “START” and propagates across the entire SOA environment using a combination of sync/async JMS messages, HTTP and RMI communication to notify other Services that a customer is now active and logged in. You can also see many services writing to a database as a result of this transaction. These invocations are simply auditing the customer login to satisfy the legal regulations that this organization has to comply with. So if you ever wonder what impact Governance and Legislation has on IT, this is a perfect example of the complexity storm it creates. What’s interesting is that the Logout business transaction for this application was just as complex!

The screenshot above unfortunately reflects the enormous complexity that many IT departments have to deal with everyday, especially when a user complains that their business transaction is slow. The problem for 95% of IT departments is they don’t have this type of visibility in production. They can feel pain, but they can’t see it. A slow business transaction may take 25 seconds to complete and touch many infrastructure tiers along the way. Unless IT sees this end to end journey they’ll always struggle to troubleshoot and manage it.

The good news is you’re 30 minutes away from getting this visibility in production by evaluating a next generation application monitoring solution like AppDynamics Pro. AppDynamics will auto-discover your business transactions, map their specific flows across your infrastructure, and give you a latency breakdown across and inside every tier the business transaction touches.

To manage and master IT complexity you have to visualize and see it.  Seeing how your business actually runs across IT is completely different to guessing how your business runs across IT. Next time a user complains that their business transaction is slow, what will you do? Bury your head in a log file, or visualize how that business transaction executed using an application performance monitoring solution like AppDynamics?

Isn’t it about time you mapped your app?

App Man.