The interaction of people with an app is quite different with what they have on the websites. Analytics of mobile app is concerned about the conversion of ad budgets to app installs. Then it is about app installs to repetitive app usage as well as in-app purchases. Ultimately, the major goal of a mobile app developer is to understand and estimate the lifetime value of the user. He should also evaluate the retention rate and usage frequency.

1. The first thing to evaluate is tracking installs of the apps. Daily installs as well as their sources are the major basic metrics a developer should track. If there are no installs, then it means there are no users. This eventually means no revenues. Understanding the installation sources is also quite important. It is important data to evaluate the advertising and marketing channels’ effectiveness. It is suggested to hire an independent tracker to eliminate any conflict of interest. For instance, utilizing a tracking system from an advertisement network. A tracker provided by an ad network with a sole goal is to sell as many installs as it can, may bewilder you about the actual picture.

2. The retention metric is based on the app sessions frequency. Most platforms for mobile analytics continuously record the sessions’ number without analysing about what the session is. They usually define a session as an act of app opened by the user. This is not an accurate definition. A user may get distracted from the app due to push notifications, phone calls or messages. Google Analytics takes into account the session which has 30 minutes gap between them. This is quite an acceptable definition.

• The “retention” metric is actually the division of number of users who daily return to the app by the total app users from the monitored group.
• The “churn” rate is exactly the opposite of retention. It is the percentage of the app users who don’t return to a particular app in consideration.
• The retention metric helps in evaluating user lifetime that defines the lifetime value of the user.

The user lifetime or the LT is defined as an average number of days an app user from a given group spent in entirety interacting with the app. This metric allows the evaluation of the number of users the app needs to acquire on a daily basis to maintain or generate revenue growth. This metric is essential to understand the mobile app engagement.

3. The main purpose of any app is to generate revenue. This is measure by user lifetime value. It is calculated on the basic of the generation of the revenues from the user over their lifetime. It is entirely a marketing metric in order to calculate the ROI or return on investment in advertising and marketing.

The ARPU or average revenue per user is calculated by division of total revenue generated per user from the user lifetime. An app may ask the users to share links on social media. These new links and new users who arrive due to these links can easily be tracked in order to calculate the virality metric. It is essentially the measurement of a viral campaign through social media.

4. Cohort analysis is important app marketing engagement metric. It is about grouping the users into different sections. Finally analysing the metrics of these groups. Cohorts are dependent on traffic source, device and country. By identifying the most profitable cohorts assist in the better targeting of the user through ads to increase app revenue. It also helps in increasing user lifetime value.

5. App development, especially iPhone app development may have quite specific requirements. It is related to which metrics need to be tracked to increase retention rate. It is also about tracking metrics for better user experience. Analytics services may fail to provide read-to-use metrics displayed on their dashboard. But they do provide an option to setup different custom variables to create custom reports. These custom reports allow the app developers to segment the paying users. It also allows them to tag them and analyse them separately.

The developer has to work alongside the marketer. He has to work together to collect and analyse the app metrics and its technical implementation. One solution is to implement any existing analytics company’s SDK. It should have extensive lists of metrics which are predefined.

Conclusion

Businesses like e-commerce require web and mobile presence with equal importance. The division between web and mobile may be different from mobile-fast businesses. It is especially in case of tracking entirely different set of metrics. The mobile application development and app marketing engagement tracking is witnessing a new trend. It is to move from diversified analytics to single source of data of the app. The industry will most probably adopt a different platform model. This model will have a single data source to be used by different specialized providers. This single platform will also offer a better picture to app developers. It will reveal the actual reality with the app as well as in the app.