Four Use Cases for Leveraging Business iQ

October 19 2017
 

Learn how you can leverage AppDynamics Business iQ to analyze how application performance is impacting customer experience and business outcomes.


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.

Harish Doddala
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 AppDynamics/Cisco, VMware and Oracle. Harish is a Fellow at Massachusetts Institute of Technology, System Design and Management and has published in international speech and audio conferences. Harish has filed two patents: one for querying machine learning models and one to uncover root cause analysis.

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