How can you monetize an online game without being intrusive?

These features should enhance the gameplay and provide additional benefits to players, while not disrupting the core experience for free users. Some examples could include cosmetic upgrades, exclusive items, or faster progression. Ensure that these premium features are not essential to gameplay, so that free users can still enjoy the game fully. Additionally, provide clear information about the benefits of upgrading and make the pricing reasonable. By offering optional premium features in a non-intrusive manner, you can provide a way for players to support the game financially while still respecting their gameplay experience.

Full DLCs are still a very good way to monetize; few years ago, the major industry players shifted towards smaller in-app purchases, overlooking DLCs just as they were gaining widespread acceptance. Take EuroTruck Simulator 2 with its 97 DLCs for instance: the bigger ones, priced close to the original game, are top-sellers. By offering rich additions - new storylines, missions, maps... - DLCs can stand out as a player-friendly alternative to microtransactions, notorious for small but frequent costs disrupting gameplay. DLCs provide substantial, distinct content that players can choose, ensuring they get real value. This approach not only enhances the gaming experience but also aligns well with player preferences and spending patterns.

Firstly, ensure the ads are optional, granting players the choice to engage or dismiss them. This helps to maintain a non-disruptive gaming experience. Secondly, integrate the rewarded ads seamlessly into the game, aligning them with in-game rewards such as extra lives, power-ups, or virtual currency. This motivates players to willingly engage with the ads in exchange for valuable game resources. Additionally, limit the frequency of ads to prevent annoyance and burnout. By striking a balance between monetization and player satisfaction, you can successfully monetize your online game while minimizing intrusion and enhancing user engagement.

Offer a tiered system that provides additional perks and benefits to subscribers, such as exclusive in-game items, bonus experiences, or early access to new features. Ensure that the game remains enjoyable for non-subscribing players by avoiding a "pay-to-win" scenario and maintaining a fair playing field. Integrate cosmetic customization options that are available for purchase separately, allowing players to personalize their characters or game elements without impacting gameplay. Additionally, consider offering limited-time events or special challenges exclusively for subscribers as an added incentive.

Create limited-time events that offer exclusive rewards or bonuses, enticing players to participate. Offer cosmetic items, such as unique skins or customization options, that can be purchased during these events. Integrate in-app purchases for event-related items, but ensure they do not interfere with the core gameplay experience. Implement a fair and balanced system, where players can earn these items through gameplay or choose to acquire them more quickly by spending money. By leveraging in-game events effectively, you can generate revenue without disrupting the player's immersion or enjoyment. Keep in mind that maintaining a positive player experience should be a priority to ensure long-term success.

Having a robust BI suite is extremely helpful in these cases. Some of the basic KPIs you'd want to look into include MAU/DAU, MARPU/DARPU, Retention Rates, Paying Users Rates. Data can also be used in the monetization design itself. I.e. older players prefer having an interrupted gameplay loop and have a stronger buying force, thus opting for ads probably makes less sense in their case, when in-app purchases would be an enticing prospect for them. AB testing monetization and gameplay features can also be a huge help in terms of optimisation and speeding data collection up. I believe that having a robust AB testing infrastructure in the game is a must in terms of the proper introduction of such features.

AB testing, about which I talked about in the point above, speeds up experimentation and testing. An example: You want to introduce a new feature, but you don't know what the values should be. So, you create 3 versions: the "default" one, the worse one, the better one. Then, you create 4 testing groups: - the control group without the feature, - and 3 groups with each version of the feature. You can choose the best version after the tests and introduce the best-performing version of the feature. Later, you can introduce additional tests with, say, limited supply, other, less extreme values and such.