Let’s say that you’ve launched a much-in-demand mobile application to the app store and now your main responsibility is to build strong bounds with the audience. Well, easier said than done. Luckily, these "relations" are easy to analyze and improve, making use of the illustrative mobile app KPIs.
In this article, we introduce you to the key analytics metrics you can track in Google Analytics, Mixpanel or any tools you like in order to get the sense of how well your product performs and which direction to take to go wheels up.
Where to start?
In case you only dip your toe into all the analytics intricacies, we suggest not rushing to check all possible metrics you can find but focus on the following 5 universal points that are equally important regardless of the scale and type of your application.
Key Metrics of Your App Success
1. Retention Rate
Retention rate is the percentage of active users returning to your app over a given period of time which makes it the core highlight of your app prominence.
As a rule, the first consistent decision that comes to the mind of most market entrants is to attract as many new users as possible. Well, fair enough! But it’s crucial to remember that attraction is only the first tiny step to success as it is retention that becomes the hard nut to crack.
To check your current customer retention situation, follow the formula:
A = (B - C) / D x 100%
a - Retention rate
b - Number of users at the end of the period
c - Number of users acquired during the period
d - Number of users at the beginning of the period
The formula can be applied for any period you like. Most analysts check the metrics of 1-day, 7-day and 28-day retention.
Tip: We’d like to draw your special attention to the retention rate in the 1 – 3 day mark. Statistics say that almost 80% of users drop off within the first three days after installing a mobile app. Such outcomes are often caused by interface issues so if users quit before they even started, it’s a “wake-up call” for testing UI more thoroughly.
In fact, user retention rate should be one of the defining factors of your marketing strategy as it shows user satisfaction with your mobile application. Monitoring the dynamics of retention rate changes allows you to understand how to optimize the app performance in the most efficient way as well as how users react to certain changes you make to your mobile app.
2. Installation Source
The source that provides a user with the information about your application is a strategically important metric for understanding the effectiveness of the advertising channels you utilize.
Tracking the installation source is as simple as ABC, following the same principle as with any website. All you need is to create UTM tags for each of the advertising channels and insert them into the link leading to the app store.
Tip: You may use such services as Tilda for generating appropriate UTM tags.
Once installed, the application reads these tags and captures the source that, in its turn, will be displayed in your analytics system.
This metric detects the most beneficial advertising channels and helps to avoid excessive spendings on unprofitable ones.
3. Number of Unique Users
Checking the number of unique users illustrates the value of your application to the users who installed it.
There are 3 parameters that can give you a better understanding of the unique user activity per certain period:
DAU (Daily Active Users) = number of individual users who open your app in a day
WAU (Weekly Active Users) = number of individual users who open your app in a week
MAU (Monthly Active Users) = number of individual users who open your app in a month
Tip: Based on this data, you may also calculate the Sticky Factor which shows user engagement and the regularity of logins to the application. As such, follow the formula:
Sticky Factor (per month) = DAU / MAU x 100%
Sticky Factor (per week) = DAU / WAU x 100%
The metrics mentioned above demonstrate audience loyalty to your app so you’ll be able to see if your product "hooks" users or you have to revise and upgrade some parts of the app.
Speaking of the session analysis, it is vital to check the average session length (ASL) and the visited app screens as these markers allow you to understand user in-app behavior.
The average session length indicates how much time users spend in your app and how interesting the product is. ASL is calculated by the formula:
ASL = T / N
T - the total duration of sessions for the period
N - the total number of sessions for the same period
Note: ASL tracking is especially useful if your app has some paid content as the more time users spend inside the app, the more likely they are ready to pay for your services.
As for the visited app screens, such analysis provides you with the information about app sections that are most catching and handy for users and how users interact with the in-app functionality.
It is even more important to take notice of the screens where most user sessions end. This metric is especially prominent if your app has authorization which can scare off users and become the reason for leaving.
Reviewing user behavior inside the app can enhance your development strategy by finding out which screens are successful and which ones can be completely removed, improved or redesigned to provide more value to your customers.
This group of metrics is directly related to your income, detecting how much and how often users pay.
Though in the very beginning you may be just excited to be gaining popularity of your product, you should always keep an eye on how much this is all costing. To be precise, we suggest checking the following markers of the effectiveness of your monetization policy:
ARPU (Average Revenue Per User) = Gross / MAU (can also be calculated for DAU or WAU)
Since this metric refers to the effectiveness of the entire project, it can be a core indicator of the attractiveness of the app pricing policy for users.
CPA (Cost Per Acquisition) = Costs / Number of acquisitions or conversion
This indicator will allow you to understand how expensive it is to attract new users to the application in the context of a specific marketing campaign.
LTV (Lifetime Value) = ARPU x Average Lifetime of a user
Note: Average Lifetime is the average lifespan of a customer showing how long the average customer is using your app. When calculating LTV, Average Lifetime must be a multiple of the period for which the ARPU was calculated. For instance, if you take ARPU for a month, then Lifetime should also be measured in months.
LTV helps you assess whether you’re having extra costs for your users, given the value they bring to your company. The takeaway here is that LTV should be higher than CPA, otherwise you’ll need to revise your marketing strategy.
Measuring your success is a vital part of any project so following the metrics outlined above is quite a good place to start. But most of all, you should learn to interpret the analytics data right in order to timely detect in-app issues and target at the continuous improvement of your product.