In this second part of the article on app marketing, the focus shifts to post-installation evaluation indicators, including DAU/MAU (Daily/Monthly Active Users), retention rate, ARPU/ARPPU (Average Revenue Per User/Paid User), LTV (Life Time Value), and ROAS (Return On Advertising Spend).
In the first part of the article, we explained indicators such as CPI and CVR and the factors that change them, with the aim of "not only superficial understanding, but taking appropriate action according to the indicators". This time, I will mainly explain the indicators that lead to the evaluation after installation, such as DAU and ROAS, which I could not introduce last time. *This article is based on app marketing. Please note that the definition may differ from general advertising operations.
DAU/MAU refers to the number of active users over a specific period. An active user is one who uses the app, but are they really using the app after installing it? For most apps, revenue is generated not just by installing the app but by using it, so DAU/MAU, which measures actual app usage, is a key metric for marketers to focus on.
Let's examine the difference between DAU/MAU and the types of apps best suited for each metric.
DAU: Short for 'Daily Active Users', it represents the number of active users per day. It's more applicable for apps like social media, games, and manga apps, which are often launched multiple times a day.
MAU: Stands for 'Monthly Active Users', denoting the number of active users per month. It's suitable for apps like e-commerce or travel booking, which are typically used several times a month.
As you can see, the metrics to be looked at differ depending on the app genre, and the numerical value varies depending on the metric to be compared, such as "DAU is low but MAU is high", so let's check the appropriate metric for the app genre! * As some of you may have noticed, the index showing the number of active users per week is called "WAU (Weekly Active Users)".
So, what measures should be taken to increase DAU/MAU? Here we will introduce two measures.
In a particular news app, there was a significant imbalance in user engagement times. Upon closer examination, it was found that there was a strong tendency for usage times to coincide with the periods when push notifications were sent.
Next, let's look at a case involving a change in the UX of an app designed for meal planning. Originally, this app allowed users to plan meals for up to one week. By changing the default setting for the number of days a menu could be created from one day to seven days, the number of people using the app for more than 30 days within a 45-day period increased by 2.3 times! This suggests that many households tend to plan their meals and shopping on a weekly basis.
The retention rate is the continuation rate from the day of app installation. How many users are still using the app after several days?
Retention rate = (number of active users after X days / number of installs) x 100
For example, if there were 500 installs on April 1st and 100 active users on April 15th, the 14-day retention rate would be 20%.
[Calculation method]
Retention rate after 14 days = (number of active users on April 15th / number of installations on April 1st) x 100 = (100/500) x 100 = 20(%)
This means that 20% of users who installed the app on April 1st are still using the app 14 days later.Also, here we calculated the retention rate after 14 days, but in the case of app ads, retention rates after 1, 3, 7, and 14 days are often evaluated.
This is a metric that represents revenue per user, and for daily/monthly terms, it is written as daily ARPU/monthly ARPU, etc.
Let's take a look at the differences between the two.
ARPU: 'Average Revenue Per User', indicating the average revenue per user.
ARPU = Total Revenue / Number of Users
ARPPU: 'Average Revenue Per Paid User', showing the average revenue from paying users.
ARPPU = Total Revenue / Number of Paying Users
For example, if there are 50,000 daily users, 500 paying users, and sales of 500,000 yen, the daily ARPU is $10 and the daily ARPPU is $1,000.
[Calculation method]
Daily ARPU = $500,000 ÷ 50,000 = $10
Daily ARPPU = $500,000 ÷ 500 = $1,000
Also, at this time, there are 500 paying users out of 50,000 users, so the conversion rate to paying users is 1%. In addition, when ARPU is high, there are two factors that can be cited: "there are many paying users" or "high ARPPU (=high billing amount per person)", and it is necessary to consider which is the cause.
LTV, or 'Life Time Value', represents the total revenue a single user generates over their lifetime. To calculate LTV, you typically divide ARPU by the churn rate. For instance, if the ARPU is $500 and the app has a 20% churn rate, then the LTV is $2,500.
[Calculation method]
LTV = $500 ÷ 0.2 (= 20%) = $2,500
If you want to collect 100% revenue here, you need to stay within CPI $2,500, which is an important indicator to know your CPI tolerance!
Difference Between ARPU and LTV
While ARPU shows the average revenue per user, it doesn't account for users who may stop using the app midway. LTV, on the other hand, considers this potential user dropout, representing the average revenue per user over their expected lifetime.
ROAS, 'Return On Advertising Spend', measures the effectiveness of advertising expenditure. It indicates how much revenue is recouped as a percentage of the advertising spend. Unlike CPI, which shows the cost per install, ROAS measures the revenue generated from users who installed and engaged with the app. For example, if the advertising spend for a month is $1 million and the revenue is $2 million, then the ROAS is 200%.
[Calculation method]
ROAS = (sales from apps / advertising expenses) x 100 = (2 million / 1 million) x 100 = 200(%)
This metric also serves as a guideline for advertising budgets. A ROAS below 100% suggests that the investment in advertising is not being fully recouped in sales, indicating a need for strategic reassessment. It's common to track ROAS not just for the current month but also for 2, 3, or 4 months.
In addition to the above formula, it is also possible to calculate ROAS = ARPU ÷ CPI, and it is good to understand the relationship between the three indicators. *ROAS and ARPU need to match the period. For example, an app with a monthly ARPU of $300 and a CPI of $150 will have a monthly ROAS of 200%. At this time, in the case of an app with a monthly ROAS of 300% as the KPI for advertising, the target will not be achieved. In this way, ROAS is a figure calculated from indicators such as CPI and ARPU, and is it a good figure compared to the target? By judging, it becomes an element for thinking about the next action.
In Part 1 and Part 2, we have introduced indicators related to app advertising! By all means, please try to use it for actual advertising operations together with the numbers and terms on the management screen introduced in the first part!
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