💰InApp

InApp is a chart that analyzes the indicators of players' Inapp loading: which stage players load a lot, which events stimulate players to load Inapp the most,...

I. Filter

1. Where

Where to buy products in the game: shop, battlepass,...

2. Product

Products that players buy: treasure_pack, starship,... purchased at different locations.

Where + Product Filter

I. Diagrams

1. Total Inapp by Date

The graph shows the amount of Inapp players have purchased distributed by day, which can track which period players deposit strongly to develop the game (Unit: USD).

For example, Figure 1.1 shows that on August 2, 2024, players deposit the most Inapp during the month, and the strongest when buying buying gold_1.

Figure 1.1. Total Inapp Chart by Date

2. ARPDAU By Date

• ARPDAU: Average Revenue Per Daily Active User.

• The chart shows average Inapp revenue per daily active player.

• Formula: ARPDAU = Total Daily Revenue / Total Daily Active Players

• For example, Figure 2.1 shows that on July 31, 2024, there is in-app revenue of $2,248, 184,043 active users, and an ARPDAU of 1.22¢.

Figure 2.1. ARPDAU chart by day

3. Total Inapp by Level

The graph shows the amount of Inapp players have purchased allocated by level, which can be tracked at which level players deposit strongly to develop the game(Unit: USD)

For example: Figure 3.1 shows that at level 44, the player who loads the most Inapp is between levels 0-56.

Figure 3.1. Total Inapp Chart by Level

The drag bar shows how much the Inapp load rate on a set level accounts for compared to the total Inapp load on the entire level (Inapp load distribution by level).

Figure 3.2. The drag bar shows the ratio of Inapp volume distribution by level

4. ARPDAU By Level

• The chart shows the average Inapp revenue per active player by level.

• Formula: ARPDAU by level = Total revenue per level / Total active players per level

• For example, Figure 4.1 shows that at level 63, there is inapp revenue of $98, 1,202 active users, and an ARPDAU of 8.22¢.

Figure 4.1 ARPDAU chart by level

5. InApp player count by level

The graph shows the number of players who have loaded Inapp distributed by level, which level can be tracked at which level players deposit strongly to develop the game.(Unit: User)

For example: Figure 5.1 shows that at level 44, there are the most players who load Inapp between levels 28-51.

Figure 5.1. Graph of Total Inapp players by level

6. Top in-app player

The graph shows the total number of Inapps that each user has loaded arranged in descending order. (Unit: USD)

For example, Figure 4.1 shows that the 3d8e3b6aa715df67 player has the largest Inapp intake

Figure 6.1. Chart Top players who load Inapp the most

7. Player in-app rate by install day

The graph shows the in-app loading rate of a set of players who install the game during the specified time period.

For example, Figure 7.1 shows that in the period from July 1, 2024 to July 31, 2024, the total Inapp deposits of players with retention days of 3-17 on July 12, 2024 is the largest.

Figure 7.1. Player in-app rate by install day

Filter Retention Day

This is a filter used to select a set of players to compare. For example, retention day is Day 0 - Day 90, which means selecting the number of players who installed the game in the last 90 days (compared to the current time).

We can change the Retention Day range to compare between player sets.

Figure 7.2. Retention day filter

8. Total Inapp by Inapp LTV value

• The graph uses percentiles to segment players based on their Inapp LTV value and sums the Inapp in each of those player sets.

• Example in Figure 8.1: With the set of players with inapp LTV ranging from 41($) to 600($), the 95% to 100% percentile, the user with inapp LTV from 235.44($) to 541.76($) has the largest amount of Inapp Revenue.

Figure 8.1. Total Inapp Chart by LTV Value

• Filter Inapp LTV ($): select the inapp LTV amount to retrieve data on the corresponding user set.

Figure 8.2. LTV inapp interval filter

• Select the percentile range to query.

Figure 8.3. Interquartile range filter

9. ARPPU By Date

• ARPPU: Average revenue per paying user- is a metric used to calculate the amount of revenue generated by paying users, on average, over a given period of time.

• The chart shows the average revenue per in-app user.

• Calculation formula: ARPPU = Total revenue generated in period X / Total number of users loading in-app in period X.

• For example: According to figure 8.1 at the time of August 2, 2024, the revenue is 2,657($), the number of users loading inapp is 464 -> ARPPU = 5.73(¢).

Figure 8.1. ARPPU chart by Date

10. Paying Rate by Date

• The chart shows the ratio of in-app purchases to total daily active players. This provides insights into the game's monetization performance and engagement.

• Formula: Paying Rate = Total number of users who top up in-app in a period of time X * 100 / Total number of active users in a period of time X.

• For example: Figure 10.1 on August 2, 2024, there are 464 users loading inapp, the number of active users is 191,572 -> Paying Rate will be 0.24%.

Figure 10.1. Paying Rate Chart by Date