If you haven’t already done so, I recommend reading Virtual Economies - Design and Analysis by Edward Castronova and Vili Lehdonvirta. In the book’s introductory chapter, the authors discuss amongst other topics the difference in earning potential between premium and freemium revenue models for games. Let me TLDR it for you:
If your game is sold for a flat fee of X$, you’re limiting your potential market to people who can afford to spend X$. On the other hand, people who are able and willing to pay more than X$ have nowhere to do so in your flat fee game, resulting in figure 1
figure 1
Conversely in the freemium revenue model, in which you normally sell virtual goods for any price between 0.1$ - 10K$, every person that downloaded your game is a potential spender , see figure 2.
figure 2
This post explores how to tap into the “everyone is a potential spender” mindset and maximize your game’s revenue through strategic segmentation of paying users.
Segmenting Users by Price Points
Not all players are going to respond to the same price points!
To truly maximize your game’s revenue potential, it’s crucial to align your in-game offers with what your players are actually willing to spend. This means tailoring your offers to match their spending habits and preferences.
For instance, players who regularly drop $50 or more on in-game purchases aren’t going to be tempted by a $5 offer—they’re looking for premium content or exclusive bundles that match their investment level and deliver serious value or prestige. Conversely, players who typically spend in the $1 to $5 range might find a $50 offer overwhelming and out of reach. These players are far more likely to convert with micro-transactions that offer small but meaningful upgrades at accessible prices.
Implementing Granular Pricing Strategies
You could of course broadly categorize users into just three tiers, such as High, Moderate, and Low spenders, but I recommend a more granular approach to segmentation. It’s far more effective to create multiple, finely tuned segments based on precise spending habits. The idea here is that the wider the net, the poorer the results; therefore, a narrower focus on specific user spending habits yields better outcomes.
Let’s consider the following segmentation example of a made up game:
Segment | Details |
|---|---|
Non-Paying Users | These are players who have not yet made any in-game purchases. The goal with this segment is to convert them into paying users by offering irresistible entry-level deals, such as a heavily discounted starter pack or a one-time-only offer that provides significant value at a low price point. |
Payers Below $5 | This segment includes users who have made small purchases, typically less than $5. For these players, microtransactions and low-cost bundles are the most effective. Offering them frequent, affordable deals keeps them engaged and encourages regular spending without overwhelming them. |
Payers Between $5 and $15 | Users in this category are comfortable with spending a bit more but still appreciate value. Mid-tier bundles that offer a mix of currency, consumables, or cosmetic items work well here. These players might be tempted by limited-time offers that provide a slight discount or bonus for purchasing within this price range. |
Payers Between $15 and $25 | These players are willing to spend more for a premium experience. Target them with offers that include rare or exclusive items, larger currency packs, or special event-related content. The focus here is on providing content that feels valuable and justifies the higher price point. |
Payers Between $25 and $50 | This segment includes our high spenders, who are likely to respond well to exclusive content, such as rare items, VIP passes, or high-value bundles that offer significant in-game advantages. For these users, consider personalized offers or packages that cater to their preferences and spending patterns. |
Payers Above $50 | These are our “whales,” and for them, the sky’s the limit. Crafting highly exclusive offers that appeal to their desire for status, prestige, or significant gameplay advantages is key. These could include unique cosmetic items, early access to new content, or even custom experiences tailored to their in-game preferences. |
Your segments may very well look different. They need to be tailored to your specific game and user population through data-driven optimizations. Start with something and fine tune as you go along.
To effectively segment users based on spending habits, it’s essential to define the criteria for each tier. For example, being categorized as a player with a “purchase habit” between $15 and $25 could be determined by different factors depending on your approach. One method might be to consider the amount spent in a single transaction, meaning that any player who makes a purchase within that range at once would fall into this segment. Alternatively, you could base it on cumulative spending over a specific period, such as daily totals. In this case, a player who spends between $15 and $25 across multiple purchases within a day would be placed in this segment.
There is no right answer for everyone, the choice of metric should align with your monetization goals and the spending patterns observed in your player base, allowing for more precise and actionable segmentation.
Leveraging RFM (Recency, Frequency, Monetary) Analysis for Advanced Segmentation
RFM analysis has been around for many years, is considered somewhat easy (technically) to implement, and is a powerful tool for user segmentation. RFM analysis helps to categorize players not just by their spending habits, but also by how recently they made a purchase, how frequently they spend, and the total amount they’ve spent over time. This method allows for an even more nuanced understanding of user behavior, enabling the creation of targeted offers that consider a player’s overall engagement with the game, their purchasing patterns, and their long-term value. This method eases the task of monitoring user drifts between segments. By integrating RFM analysis with traditional price point segmentation, you can refine your approach even further, ensuring that each offer is not only aligned with a player’s spending capacity but also with their overall activity and loyalty to the game.
The Impact of Tailored Offers
When players are presented with offers that match their spending capacity, they are more likely to make purchases and, importantly, continue spending over time. This approach not only boosts your immediate revenue but also enhances player satisfaction by providing them with offers that feel personalized and relevant.
In contrast, a one-size-fits-all approach can alienate players who either feel the offers are too expensive or not valuable enough. By missing the mark on price point segmentation, you risk leaving money on the table and losing potential long-term customers.