Comparing Web vs. Mobile Analytics

Every day a growing number of consumers use their mobile devices to play games, access apps and shop. As the use of mobile devices increases, so does the amount of data that is generated. Companies that realized this in regards to eCommerce and online gaming early on are already analyzing customer data to draw insights and increase ROI. For these companies, analytics is a key part of business, providing invaluable, actionable data.

There are important differences that should be noted when looking into web and mobile analytics solutions.

First off, there is a difference in the structural aspects of both types of analytics. In the past, before the advent of big data analysis and mobile handsets, data was typically generated by users of desktop web applications and web analytics focused on metrics like page views. Nowadays, web analytics has expanded to include more behavior-related metrics like repeat, unique and new users. Analyses based on patterns generated by user cohorts is widely available. These analyses are more complex, enabling the reduction of churn and increased conversion, especially in the fields of eCommerce and gaming.

Mobile analytics focuses on user data generated by games, apps and web sites on mobile devices. This obviously includes simple metrics such as tracking the number of page views, length of visits, origin of users and whether or not they made an in-app purchase. More advance analytics use cohorts to group similar users, or path analysis to understand what users are doing while they are using the app, and why. Additionally, the user’s location serves as a unique asset and differentiator from web analytics.

Besides some of the technical differences listed above, the way users behave on a computer is very different than on their mobile device. On a mobile device, users must download and install an app or game through an app store that requires them to be signed in. This allows each user to be tracked with a dedicated user name, which means developers can segment that user by date, amount of time in game, levels played, location and other specific metrics. Online, a user does not need to download anything and thus it is harder to track individual users. These differences mean that a tool that is dedicated to web analytics will not be suited to mobile without some adjustments.

Another major difference between web and mobile analytics has to do with sessionization. It is most likely the biggest difference when it comes to comparing the two, and it occurs every time a session ID is created and stored when a user visits a web page or mobile application. Behavioral analytics tracks how long the session remains active and how often a user logs in, creating a new session each time. A user is likely to have a longer session on a desktop or laptop computer, but may not access it as often when compared to a mobile device. Advanced analytics can properly analyze the details and their significance. It is not as likely that a user will keep an app open for a very long period of time on a mobile device without closing it, as mobile users tend to interact with an app more often for shorter periods of time. The focus for mobile is on finding out how long the app is in front of the user and their actual engagement time with the app.

Web analytics is faced with very different challenges when compared to mobile. User interaction with ads, which is a major source of monetization for app developers, will differ from platform to platform. On a web application, a user may install an ad-blocker, disabling advertisements altogether, or just ignore the ads and never clicking on them due to the larger screen. Mobile, on the other hand, makes it much harder for users to block ads. Ads are also ingrained in mobile apps and in-app purchases are therefore extremely effective.

Having said all this, while web and mobile analytics may have some distinct differences, they are also becoming more connected as the lines between mobile devices, tablets and home computers continue to blur. In the past, a retailer may have been fine with just having an eCommerce website that was designed for desktop use, but now users expect a mobile app to complement their shopping experience. They may prefer browsing on their home computer and completing the purchase on their tablet, or vice versa. This means that having dedicated web and mobile analytics may not be enough, as a solution that is able to track a user across multiple platforms is necessary, focusing on a custom approach across multiple platforms so that accurate web and mobile analytics are available in one place.

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