As the internet-savvy generation moulds it’s ways to unlimited access, the need to access their usage patterns through metrics becomes persistent. Analytics can thus help businesses in providing invaluable insights and actionable data to improve the overall user experience for customers.
It’s important to note the structural differences between the two types of analytics.
Before the widespread popularity of mobile phones and the advent of big data analysis, data was generated mainly by desktop web application users. At that time, web analytics focused on metrics like page views primarily. On the other hand, modern web analytics includes an assessment of behaviour-related metrics like repeat, unique, and new users. Web analytical solutions analyze based on patterns generated by user cohorts to reduce churn and increased conversions.
In general, Internet users do not need to download, which makes it harder for web developers to track individual users. Further, they are more likely to have longer sessions while they use a desktop or laptop computer. However, they may not access it as frequently as compared to a mobile phone.
User interaction with ads is the primary source of revenue for most businesses. However, users often install ad-blockers on web applications to disable advertisements. They also ignore the ads and avoid clicking them thanks to the larger screen sizes.
Mobile App Analytics
On the other hand, a mobile phone user is always on the move, using different apps, multitasking his/her way through life. With the increase in the adoption of mobile technologies, there is a consistent increase in the amount of data that is generated. Mobile app companies feel a pressing need to analyze customer data to draw insights and increase their ROIs. Advanced mobile app analytics use data 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.
Using mobile phones, users download and install apps through a dedicated app store by signing in. Sign-ins make it easy for developers to track users, segment them using different metrics. Moreover, mobile app users do not keep an app open for long durations, but they tend to interact with it more often for shorter periods. Mobile analytics thus focuses on finding out the actual engagement time of a user with the app.
While ad-blockers play a major role in consumer navigation on web applications, it becomes harder for app users to block ads on mobile devices as ads come ingrained in mobile apps.
Although web analytics and mobile app analytics are inherently different, they find themselves converging, as mobile devices, tablets, and home computers continue to evolve in terms of design and functionalities.
A decade ago, businesses were content with an online presence in the form of a website designed for desktop/laptop use. Still, the modern mobile-first generation demands a mobile app to enhance their online shopping experience.
Thus, there is a need to leverage both mobile app analytics and web analytics to ensure customer satisfaction on all platforms.