In my previous post, I discussed how AppDynamics Application Analytics can rapidly troubleshoot gradually degrading apps. In this blog post, I’ll discuss how IT can redeem themselves from unfortunate outages leveraging ITOA or application analytics.
With so many factors impacting application performance today, it is not surprising that applications frequently are either slow or simply stall entirely. Sometimes it’s the server, sometimes it’s the database, and some days it’s the mobile network carrier to blame. With the complexity of today’s environments, business transactions (such as logging in, adding to a cart, or checking out) have many opportunities to fail. These transactions often fail long before they reach the backend operational databases where all the “committed” transactions are stored. So, as far as the traditional business intelligence (BI) solutions — that provide insights only into committed transaction data — are concerned, these in-flight, yet failed transactions never existed.
Another trend that makes the equation all the more complex is IT is delivering more and more modular applications at faster and faster rates making the entire application ecosystem very dynamic and highly error-prone. Applications are bound to be slow or stall; It’s how IT redeems itself from such critical outages with their business stakeholders that matter most.
AppDynamics Application Analytics provides real-time visibility to deliver insights into both aggregated or rolled-up metrics, as well as details into individual customer interactions. The breadth of visibility covers the frontend to backend technology stacks — from clients (mobile or browser apps) to the Java or .NET or other language apps, to databases, to servers and infrastructure components. The depth covers code-level visibility into live in-flight transaction data captured as the application processes it, and is not restricted only to those transactions committed to the operational database.
Let’s say that John is trying to purchase a shirt on his mobile device while commuting back from work. His checkout transaction times out as his mobile device frequently switches cellular towers in the fast moving train. John finally gives up after repeated attempts. Now, this transaction failed on the network carrier and never hit the application inside the data center servicing such requests. So, the application infrastructure has no knowledge of John’s attempt at purchasing the shirt. In another case, Susan was trying to buy a purse from her browser but her order got stuck in a queue due to errors in the messaging queue. Susan’s transaction also never hit the operational database.
In such situations, IT can leverage AppDynamics Application Analytics to not only identify these individuals who had poor experiences, but also to capture what they were trying to accomplish (purchase items, in this case).
Now rather than treating these as lost revenues and giving up on them, IT can redeem itself by extracting key information into a spreadsheet with a click of a button. This information includes account information of the purchaser (name, email, etc.) as well the exact items being purchased. The marketing team can then use this valuable information and run some win back campaigns that offer 10% discounts to win the heart of the customer. The more sophisticated retailers might go a step further by pre-creating a shopping cart that has all the items pre-loaded, with a discount applied, and ready for one-click checkout from the email itself. Now that’s what I’d call going above and beyond!
IT, typically looked at as a cost prevention insurance method, can actually help drive revenue given the right tools!
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