Exploring monetization: Using data to guide decisions

Author’s note: This is the last part of the GameAnalytics’ monetization series, exploring various models to help you identify both traditional and alternative monetization strategies to maximize your revenue.

Missed the first 3 parts? Check them out below:

Exploring game monetization: Traditional strategies
Exploring innovative game monetization: Alternative approaches
Exploring monetization: Maximizing game revenue
Exploring monetization: Using data to guide decisions

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Why is revenue data important?

Having access to data is important for optimizing your monetization strategies and ensuring their effectiveness for several reasons:

Insights into player behavior: By tracking purchase events and other business metrics, game developers can gain deep insights into player behavior. This includes understanding which items or features are most popular, how often players make purchases, and what factors influence buying decisions.
Performance evaluation: Data allows developers to evaluate the performance of different monetization strategies objectively. They can measure metrics such as conversion rates, average revenue per user (ARPU), and the lifetime value (LTV) of players.
Optimization and iteration: Armed with data, developers can iterate and optimize their monetization strategies continuously. They can experiment with pricing models, promotions, and in-game offers based on real-time feedback and analytics.
Personalization: Data-driven insights enable personalized monetization approaches. Developers can segment players based on their spending behavior, engagement patterns, and demographics.
Forecasting and planning: Data helps to forecast future revenue streams and plan for scalability. By analyzing historical trends and performance metrics, developers can predict revenue projections and plan their monetization strategies accordingly.
Competitive edge: In the competitive gaming market, data-driven decision-making provides a significant competitive edge.

The GameAnalytics’ monetization features are built with these reasons in mind.

GameAnalytics’ monetization features

To support you and ensure you maximize your revenue data, we’ve enhanced our monetization view into a stand-alone overview with improved features. The most significant update is the integration of Web Shop functionality, enabling you to track revenue directly from your Web Shop.

Note: Currently, GameAnalytics supports tracking of In-App Purchase data for mobile games only.

Let’s take a look at individual features:

Revenue overview and ARPPU

The core feature is the comprehensive revenue view. Positioned prominently at the top of your Monetization Overview, this tool displays your total revenue over time and offers comparisons between iOS, Android, and Web Shop earnings for your game.

This view enables you to address key questions:

Which platform generates the highest revenue?
Is revenue consistent or does it fluctuate with peaks and valleys?
Are there indications of growth on any particular platform?

To uncover and understand your revenue trends, we recommend to:

Analyze your user base across each platform. While one platform may dominate in revenue, this could simply be due to having a larger player base on that platform. For instance, if 650 out of 1000 players use Android devices, it’s likely that Android generates the highest revenue. However, this doesn’t necessarily indicate the spending potential of iOS users or those using your Web Shop.
Compare revenue generated per platform with the average revenue per paying user (ARPPU). This comparison can show you spending patterns across different platforms. Building on the previous example, while Android may generate more revenue overall due to its larger user base, iOS users might spend twice as much per person. This insight could prompt a strategy shift towards acquiring more iOS users, who potentially have higher spending capabilities
If you observe notable changes in your revenue generation, evaluate the events leading up to and during the period of deviation. Consider the following:

Did you recently release a new game build or introduce fresh content that could influence user spending behavior?
What was the overall health of your game during this time? Were there any technical issues or bugs that might have impacted player experience and spending?
Are there recurring patterns in your revenue trends, such as higher generation during paydays or lower revenue towards month-end? Understanding these patterns can help in aligning monetization efforts with peak spending periods and optimizing revenue throughout the month.

Converting users, paying users, and split by items

Other crucial charts to consider include displaying the total number of converting users and paying users.

Who are converting users? Converting users are those who made their first purchase on a specific day, identified by the “converting=true” event filter. These users indicate first engagement with monetization features.

Who are paying users? Paying users encompass all users who made a purchase on a given date, identified by events where “is paying” equals “true.” This metric reflects ongoing engagement with in-game purchases.

Both charts are invaluable as they reveal the likelihood of players making repeated purchases, giving insights into player satisfaction with available content and monetization strategies.

If the number of paying users is higher than the number of converting users, it indicates that players find your purchase items appealing and beneficial to their in-game experience. They appreciate the value of owning premium items and make purchases repeatedly, reflecting a strong monetization strategy.

However, if the number of paying users closely matches or even equals the number of converting users, it signals a need to reassess and optimize your strategy. One effective step is to utilize the ‘Revenue grouped by item’ feature.

This feature categorizes all your revenue by the purchased item, providing insights into which items drive consistent purchases. Items that perform well can be further enhanced or diversified to increase sales, such as offering more skins or rare items within successful categories.

Conversely, if players purchase an item once but don’t return for another purchase, it suggests that the perceived value may not meet expectations. Evaluating different item offerings through A/B testing can help refine and optimize your monetization approach, ensuring that items resonate well with players and drive sustainable revenue growth.

Reviewing the durability of items in your game can also give you an idea of player spending behavior. If players are buying passes or items that offer extended benefits, they may not feel tempted to make frequent additional purchases. To address this, you can consider the following strategies:

Shorten the duration of passes or items to encourage more frequent purchases.
Limit the availability of rare or exclusive items within these passes to maintain their value and desirability.
Increase the price of passes while enhancing their content to justify the higher cost.
Convert passes into subscription models that automatically renew, providing ongoing value and convenience to players.

First transaction revenue data for in-app purchases

Understanding the First Transaction Revenue chart is also interesting as it uncovers player spending potential within your game. This data reveals how much players are willing and able to invest in in-app purchases the first time around, providing insights that can optimize your pricing strategy and prioritize items effectively.

By analyzing this chart, you can identify the spending thresholds of your player base and strategically place items within these price ranges to maximize conversions. Highlighting items that align with players’ willingness to spend can increase their likelihood of completing purchases, enhancing both player satisfaction and revenue generation.

Generate more revenue by building your own Web Shop

In Part 2 of this series, we highlighted how Web Shops enhance mobile game monetization by facilitating direct sales of in-game items, virtual currency, exclusive content, and subscriptions through a web-based storefront.

Building on this in Part 3, we emphasized the cost-effectiveness of integrating a Web Shop with GameAnalytics, reducing platform fees significantly. If you haven’t yet integrated your Web Shop, our calculator in the Monetization Overview can estimate potential revenue and savings, with Xsolla charging only a 5% fee.

Use the calculator to project your Web Shop revenue by adjusting sliders for estimated revenue and capture rate.

Xsolla Calculator

Revenue with platforms

$350k

Revenue with Xsolla

$379.3k

Revenue uplift with Xsolla

$29,250


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If you are ready to explore this opportunity, simply submit this form to connect with an expert for guidance on Web Shop implementation, no obligations attached.

Ready to scale with Web Shop? Speak to an expert now.


Learn more

Now that you understand all the features and tricks to tracking your revenue and optimizing monetization strategies, you are ready to take action. The knowledge of tracking your revenue and the data will help you to make informed decisions, refine your monetization efforts, and ultimately maximize your game’s profitability. The last step is to go ahead and connect your business events to GameAnalytics, accessing all the insights you need to drive your game’s success.

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