Mobile apps have become the central part of our lives and businesses. And developing an app is a business in itself, and that to a very profitable one. Building a mobile app can be a cash cow if done correctly. To understand how your app fares in the market, we should formulate some solid metrics. Let’s today discuss on some key metrics we would like to measure, with which, we can not only understand how our app fares, but can also improve our app in a very big way.
While downloads alone cannot determine if an app is a winner or not, number of downloads is surely a key metric to analyze. In freemium model, the more downloads, the higher the probability of success, since we rely only upon in-app purchases for revenue. In paid app, it’s a much bigger deal, downloads are directly proportionate to revenue. So in freemium business model, make sure that the metric does not stop with the number of downloads alone. We should be measuring the number of active users. To be more accurate, this metric should have data platform wise, measure how your app performs across different platforms, measure the traction during a particular drive, or it is even better to monitor whether the loses or gains popularity over a certain period of time during data driven marketing campaign. According to Distimo’s report 76% of all revenue in Apple app store comes from freemium apps. So careful monitoring is necessary.Here it is better if you set up a plan to get two major reports:
1.From where the highest number of downloads come from?
2.From where the best customers (high LTV – see Retention Metrics for definition) come form?
Understanding these things would help you to streamline your marketing strategies.
You might consider using third-party tools like AppFigures or App Annie to track the app and get more insights.
Engagement can be measured in many ways. Basically engagement metric refers to time active users spend in the app. Keep in mind, an active user roughly refers to someone who had completed at least 5 sessions with the app.
The next thing you need to monitor is the session duration. Check how much time a user spends on your app. Longer the session, more the chances of completing an event or goal. Event or goal is a specific action you want to customer to perform, which in turn generates revenue, it may be a facebook like or share or viewing an in-app advertisement or filling a form or visiting a website or anything else which generates revenue according to your marketing strategy. Since goals are easy to measure, it should be programmed into your app using app analytics tools. User loyalty is another challenge app developers face. User Loyalty is nothing but he average time a customer remains as active user. Statistics say, user normally stop using an app after 3 months.To sum up, metrics to measure engagement of an user are:
1.Number of active Users
You cannot build a mobile app campaign with acquisition alone. You must have engagement. User engagement is customer experience. If user acquisition is the life blood, then user engagement is the muscle, which shows the growth when fed. It is what that drives the mobile industry. If the users are not engaged, it directly results in growth being stagnant.
This is another metric you would want to keep a close eye on. You would not only want your customer base to grow but also to make sure that these customers stay. Retention rate exactly shows that and is measured in percentage.
Example, if you have 100 users this month and at the end of 30 days you have 80 users, then user retention rate is 80% (or churn-rate 20%) When you keep a tab on this metric on daily, weekly and monthly basis, it would again give a clear picture of the performance of your app.
Why Retention is important?
If retention is not dealt with seriousness and fixed in an app, the same customer behavior may follow in your other products as well. High retention rate follows with higher LTV (Life-time Value). LTV is nothing but the revenue generated by a customer.
Consider the Scenarios:1.You acquire 10 users and these customers generate $ 5 each and you were able to retain 7 customers (Retention rate 70%), total revenue generated is %35
2.You acquire 10 users and again they generate %5 each and the retention rate is 50%, the revenue would be % 25
In both these cases the cost spent on acquisition would be same. So higher retention rate results in higher returns on investment. Important information we get from retention rate is market viability. A higher retention rate shows higher market viability and if people are adopting your product, success is not very far.
This metric shows the quality of your code. It is nearly impossible to develop an app that is immune to any issues. Quality does not always mean perfect, and totally free of all errors. Instead, it means finding and fixing errors as soon as possible and keep the users happy and keep them assured that the app being continually improved to delight them.
This can be tracked with 3 sub metrics:1.Automatic crash report
2.Manual Customer Feedback
The first two should be in the app, from the very first and third is monitored over time.Automatic crash report should be coded into the app. When an app crashes it creates a log and it is mailed back to you. You should reverse engineer the error, and fix the issue. The fix should be given as an update. Manual Feedback is better than automatic crash report because this monitors user experience, while crash report is generated only when the app has crashed, manual feedback will give you the opportunity to understand the need of the customer and get this done. Reviews is basically a more detailed feedback, while feedback is given by the user, review is done by an expert. So you would get lots of ideas and suggestion for the betterment of the app. Once you have these key data, its time to put these into action. These are called as “Meaningful Data” since they show the trend and highlight the problematic issue and give us key insights into opportunities to perfect our product. Clearly defined data will surely help us in making accurate decisions. Raw, un-segmented and disorganized data will lead to guesses and presumptions which is dangerous for business. Our job is to create a system which gives us these clear and refined data, which will help us to take exclusive and precise decisions.