There are always new challenges in the mobile world and as mobile usage continues to dominate almost every business vertical (both native mobile-web), having a testing strategy that can be modified to incorporate new use cases and interfaces is crucial.
Over the next few months I will dive into some of the hot topics and trends in the Digital sphere to look at the horizon. Today we will be talking about the Mobile UX and bounce rate.
Mobile UX will be redefined with measurable bounce rate
“Bounce Rate” is defined as “the percentage of visitors to a particular website/App who navigate away from the site after viewing only one page. Bounce rate is a measurable indicator for engagement and stickiness in almost any digital platform – just not on those pieces of hardware we use the most: Smartphones. Decreasing bounce rate keeps UX experts and other digital leaders busy at all times, as they enhance and optimize the position of page components, customize landing page experience and fitting the digital products to the tastes, interests and behavior of their audience.
Since the dawn of mobile, these smart machines still provide the same lame experience: you use an app and leave your smartphone aside (allowing the screen to be locked). Then, you come back a few hours later and unlock the phone – and the first thing you see is still the last app you were using.
In an age of ‘everything is implementing AI/ML practices’, the apps/screens displayed on smartphones screen still suffer from the poor limitation where they cannot be customized according to the user’s needs or condition.
What is means for you: The Apps you really need, when you need them
Why is bounce rate measurement over smartphones so important? Because smartphones are becoming really smart… in other words: Smartphones will soon actually open and close your apps only when you need/use to consume them. But how is that even possible?
The natural evolution of this pattern might be into the smartphones’ display. As just mentioned, smartphones already know which apps users typically use and when, where the users are when using a specific app and more. Analyzing these patterns should allow the smartphone to know what users want and smartly serve it to the them on any given device unlock.
Ok, I get it. Smartphones are getting smarter & Bounce rate on smartphones will be measurable. What does it have to do with me?
The big deal here is around the ability to distinguish between a bounce from a page/app that was initiated by the smartphone or the user. This is a whole new granular level of bounce rate analysis that will create a new and accurate perspective about UX.
Smartphone initiated bounce (where the page/app are closed) reasons may include:
- Incoming call
- Popup in the page/app
- Device is locked (after a “session” is expired)
- User analyzed usage pattern indicates the it can be closed
User initiated bounce (where user intentionally closed the app/page) reasons may include:
- Broken UX – there is a functional/UI issue that prevents the user to complete the action in the first page/flow. (example: how many apps’ UI were corrupted with iPhone X???)
- User was redirected without true need to view the page/app or opened it by mistake.
- User is being distracted by something else (text message, etc.)
This new reality will put a big mirror in front of digital enterprises with regards to their true mobile UX. Smartphone bounce rate (which was not really discussed during the last decade) will become center stage and increase attention on the smallest details of UX that need to be continuously tested.
How to plan my testing to accommodate the different usage patterns?
New questions around environment conditions and user types should be addressed constantly. Digital Enterprises should strive for segmenting their main user groups & interfaces, naming those profiles as Personas which resemble their main characteristics.
Below are the main questions that will help creating these personas:
- Where is the app being used? (one/many location) is it being used in a static mode / while walking or maybe during driving? (impacts on which sensors are also used on the device: GPS, Accelerometer, Gyro).
- What are the network conditions used (WiFi, 2.5G/3G/4G, Airplane mode)?
- Are there any app decencies (any specific app that triggers the use or running in the background)?
- What is the main screen orientation of the usage? Are there any changes of the orientation during an average flow?
- Which user interfaces are being used (chatbots, physical proximity-based features, biometric authentication such as Touch ID or Facial Recognition, etc.)
- Types of Media being consumed (Video, audio, other)
Mobile services consumption is facing a new challenging future. In the near future, we are expected to see a booming focus on measuring and reducing smartphone bounce rate.
which reinforces the need to increase test coverage and test against clear personas.
In my next article I will dive into how testing should be more focused on location intelligence.
Click here to learn more about persona’s and how to test mobile apps under real user conditions
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