Anyone who has designed or developed a new product knows that understanding the environment in which the product or solution will be used by its end users is extremely important.

The environment is where we can successfully connect audience and purpose not only to leverage the technology’s strengths but also to minimize its weaknesses within a supported infrastructure.

We need to go beyond just identifying the basic parts of our environment and instead taking a holistic view of the entire system in order to deliver an integrated mobile solution that is consistent and predictable at each layer.

Many of the considerations for the environment may largely be influenced by your organization’s build vs. buy decision on mobile analytics solutions. A close review of the key components that make up the mobile analytics environment can prove to be beneficial.

Mobile device is the host

This is where the mobile analytics journey starts for end users. It’s critical to know and understand:

• Which kind of mobile device (smartphone or tablet) is targeted? This influences both how we design the actual mobile asset user interface, and how we improve the steps of mobile consumption.
• What the users will do in case of an issue. So they won’t be confused and discouraged right at the onset of their mobile analytics journey, there must be a commitment for end-user support and the required resources for the project to succeed.

 

Mobile app is where the action takes place

• Once the user successfully gets through the setup and configuration steps, the mobile app is where they will spend most of their time. We need to:
• Gauge our users’ overall mobile readiness. They will need to get used to standard mobile features (smaller screen and different functionality) in addition to unique mobile app components such as navigation, personalization, or custom query execution.
• Consider if there are also opportunities to supplement with additional mobile assets that may be executed outside the app. These may be in the form of a simple PDF document or as complicated as integration with another mobile apps or systems.
• Be aware of the strengths and weaknesses of our solution (app or otherwise). Instead of using cookie cutter solutions, we need to take into account the unique elements of our environment.

Mobile network is what makes it live

The mobile network is the equivalent of a “digital bridge” that allows us to connect to our platform and execute our mobile analytics assets. However, people frequently forget that this digital bridge can be made up of multiple networks.

Different conditions will directly impact the availability as well as the performance of our solution:

• In office environments where we have direct access to our corporate networks through local Wi-Fi, we can enjoy a fast connection.
• When we are connecting remotely (like using VPN), the bandwidth may be limited.
• With remote access conditions (limited Wi-Fi at the airport or lack thereof), we may not even have access to the network.

This is, again, why understanding your audience becomes crucial— so you can provide additional options both on the software (such as offline viewing once the mobile asset is downloaded) or on the hardware (such as mobile hotspot through the wireless service carrier).

Bottom line: Your environment dictates your design

Understanding your environment at all levels—not just what happens within the app or device but also how the device is used—is critical to mobile analytics design because it gives us a chance to validate our assumptions and proactively manage both user perceptions and expectations.

If you’re delivering the solution and you’re the face of mobile analytics, your users may not necessarily differentiate between what’s in your control and what isn’t. When you better understand your environment and how your users will operate in that unique environment, you set your mobile analytics project up for success.

Stay tuned for the next installment of the Mobile Analytics Design Series!

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This series was adopted from the Mobile BI Design Framework series, which was originally published on turnali.com in 2013. It also appeared on the SAP Analytics blog.