Analytics, Mobile Analytics, oh my! High-level math, double oh my! Add infrastructure, and you’re probably thinking, “Get me out of here… or bring in the science guy!”
In fact, there is no reason to shy away from the topic of analytics, and I will tell you why. First, believe it or not, you already understand analytics. How is that? Let’s take a look at some analogies that provide an easy way to relate the concept, starting with sports.
Four analytics analogies
- As a kid, did you ever have to choose sides for a game of soccer, football or dodgeball? Well, you or the captain used analytics to pick players. The data points were assumptions—right or wrong—based on individuals’ gender, size, strength, speed and past game experience. In essence, you were performing analytics with real or simulated data and associated attributes to pick players.
- Or think about the draft in fantasy football. Why do you pick players? Because of their stats. You know the rules and how points are assigned from play each week. Midseason trades too—these are all based on analytics.
- How did you choose your last car among the various alternatives? Gas mileage? Reputation of the manufacturer? Repair history? Cost comparison? It’s all analytics!
- Have you ever picked up a copy of Consumer Reports to help pick out a washing machine, entertainment center, kids cereal or something else? Yup, that too is analytics.
In each of the cases above, decisions are made based on analytics. In some cases, you’re more familiar with the data; in others, you just used looked at the Harvey Balls. (Yes, they have a name.)
In simple terms, mobile analytics is very much the same. Like choosing sides for a game, picking fantasy players, or guessing which teams will make the final four, you, your staff or trusted vendors decide what attributes of your business infrastructure relate to mobility and should be tracked and measured.
Then tools, such as IBM Tealeaf or AppDynamics, do the heavy lifting (all the math and calculations) so that you take the insights from your graphically represented customized dashboard of qualitative data instead of Harvey Balls) and transform them into actions that will improve customer experience, reduce customers abandoning the site and increase sales.
What do mobile analytics look like in real life?
Turning to a more practical example for discussion: say your company has had a website presence and maybe even a web storefront for sales. You’ve enabled it for mobile devices or even created a mobile app. Maybe you’ve also developed a mobile application for employees to conduct daily business.
The questions you need to be asking yourself are:
- How are the employees doing?
- Are they more productive?
- Is the help desk getting calls?
- Are sales increasing?
- Is brand awareness increasing?
- Are customers returning to the storefront, completing purchases or abandoning carts?
- Where do they spend their time when browsing?
- Where do they experience trouble or give up?
- Are sales appropriately distributed across the population of device types, or are more transactions completed by tablet than phone?
This is where mobile analytics tools and services do the heavy lifting and provide you with actionable intelligence. Mobile analytics can let you know what’s working well and what is not, with specific insights to why. In particular, for the enterprise, AppDynamics, SAS, IBM Tealeaf and Cognos , are Analytics technologies can provide dashboard graphics that can be drilled into to determine measures and quantify the data to answer your questions.
Did a customer abandon a cart because the network was slow, there was an error or they were just looking? Maybe they bailed because they couldn’t really see what they wanted on the smartphone screen. With good analytics tools and service, you can see what your customers did, when they did it and sometimes even why.
In addition to helping with user experience, IBM Infrastructure Analytics Services can correlate user events with network and back-end server logs to determine if there was slow response time or even an error that caused the user to abandon the cart or application. From the measurements, the analytics software can proactively generate alerts for infrastructure issues so they can be corrected before the customer or employee experiences a problem.
You’re already familiar with analytics!
There is no mystery to it. Implementing analytics mobile or otherwise for your enterprise is simply a matter of knowing the important stages of application use, what’s important important to measure, and letting the tools or a service do the heavy lifting.
Without additional Hardware, Software and training, an analytics service can provide you with a graphical view of that critical data and help you correlate user behaviors in your mobile application in real time. With predictive analytics help achieve better understanding of usage patterns, abandonment, availability, performance and capacity allowing you to make needed adjustments to meet business goals. Or a service can “host” the heavy lifting while your staff implements the capture and reporting for actionable decision making.
Want to learn more? I suggest a look at:
Hopefully, this blog post has made mobile analytics easier to relate to and given you some insight to mobile analytics and how tools can provide actionable insights into your mobile application infrastructure, performance and your customer or employee user experiences? I suggest a look at the following links for more information:
- Companion blog post, “Mobile Analytics, Should I care?”
- Short, “Simple” Mobile Analytics Demo
- Gartner’s Market Guide for Mobile App Analytics:
Why Analytics are Paramount to Success
Please leave comments below or contact me for further discussion on LinkedIn.