Welcome to the Game of Pricing. Setting the right price for your IAPs isn’t one-size-fits-all. Many games stick to the most basic default setup: all products for the same price in all markets. This ignores how much players can actually afford or are willing to pay.
Welcome to the Pricing Game (3 Regular Levels + One Secret Level):
Setting the right price for your IAPs isn’t one-size-fits-all. Many games stick to the most basic default setup: all products for the same price in all markets (just pricing—converted to local currencies). —butThis however ignores how much players can actually afford or are willing to pay. We will call this a That’s essentially Level 0 in our Ppricing Ggame.
In many lower-income countries, even $0.99 can feel like a significant purchase—comparable to a meal or essential item. Conversely, in some countries (*cough*Bay Area *cough*), a latte can cost upwards of costs $15, and customersplayers accept it without question. In these marketsthat context, a $0.99 boost in a mobile game feels like a no-brainer. Treating all markets equally in pricing ignores the very real differences in purchasing power and leaves money on the table. The right pricing removes barriers, expanding both player reach and revenue potential.
💡 The revenue upside?
Adjusting your pricing doesn’t just improve monetization—it also helps your User Acquisition efforts significantly. And the best part? The impact is instant for new cohorts. From day one, they see pricing that matches their reality—not a paywall they can’t climb.
Ready to level up your pricing strategy in 3 Levels? Let’s go.
Level 1: Localize More Than Currency
Level Design: Most devs rely on standard platform price conversion (e.g., $4.99 = ₹399), but that’s not enough. Local income and price perception vary widely. Let’s move prices according to the player’s country.
Quick Cheat Sheet:
Keep standard prices unchanged, but offer more value in countries with lower purchasing power—such as bonus currency or items. Essentially, you're giving more for the same price.
Offer ultra-low entry packs specific countries based on purchasing power (e.g., ₹29 or R$3.99 first-time packs). An offer with a low initial price can boost first-time conversion significantly, but it often comes at the cost of a much lower ARPPU. As you increase the discount in these countries, the goal is to find the balance where conversion rises meaningfully, but ARPPU declines gradually. If the discount is too high, ARPPU can drop too sharply—ultimately reducing overall ARPU compared to before, which is exactly what you want to avoid.
Offer smaller discounts in countries with high purchasing power. A smaller discount in practice means a higher price for the same content. Sweet spot is when conversion stays but ARPPU increases for those countries. As you reduce the discount, the ideal outcome is for conversion to remain steady while ARPPU increases. However, if you cut the discount too much, conversion can drop significantly—and that’s exactly what you want to avoid.
How to A/B Test It:
Group users by country
Test “standard” pack vs. “localized value” pack. Experiment by increasing discounts in countries with lower purchasing power, and decreasing them in countries with higher purchasing power.
What to measure? Always track short-term conversion, ARPPU, and overall ARPU.
Level 2: Segment by Country Tiers, Individual Countries, and U.S. States using Big Mac Index
Level Design: Match pricing to local “pocket money” equivalents e.g. moving price based on Big Mac Index can lead to better price adjustment to player monetary possibilities. Segment your markets into economic tiers (e.g., Tier 1, Tier 2, Tier 3)—or even more precisely by country, or by state where possible, such as in the U.S. Sometimes it’s enough to simply change the value offered at the same price, while in other cases you may need to adjust the price level itself. It’s all about finding the sweet spot between price and perceived value that aligns with what players can realistically afford in their region. In fact, it’s very likely that some countries are currently overpriced in your game, while others are underpriced—rebalancing this can lead to double-digit ARPU uplifts across key markets. Most games operate at tier level, but many still fail to fully optimize pricing across countries or states.
Quick Cheat Sheet:
Prepare segmentaiton based on Countries (or even states in USA), for example:
Tier 1 (e.g., US, Germany): Slightly higher price compared to what is currently offered. This lead to lower conversion (but doesnt have to) and higher ARPPU.
Tier 2 (e.g., Mexico, Turkey): Standard pricing and content as is currently present inside the game. No change to those pricings of countries.
Tier 3 (e.g., India, Indonesia): Lower price offers compared to what is currently offered. This lead to higher conversion and lower ARPPU.
Here’s an example of how the Big Mac Index can be used to compare purchasing power across different countries (https://worldpopulationreview.com/country-rankings/big-mac-index-by-country#title)
How to A/B Test It:
Define test groups by country tiers (states for U.S.)
Show country-specific pricing/value bundles
Measure: conversion rate, ARPPU, and overall ARPU—always. When you lower prices, you’ll likely see higher conversion and lower ARPPU, but overall ARPU should increase due to more frequent player spending. When you increase prices, expect higher ARPPU and lower conversion, but again, ARPU can increase if the value is strong enough to justify the price. The key is finding the balance where ARPU (conversion × ARPPU) is maximized. An interesting insight here is that sometimes, when you increase ARPPU, conversion remains stable—which means you've hit the sweet spot.
Level 3: Personalize by Location & Behavior in-game
Level Design: Go beyond region. Tailor offers based on what players actually do in your game. Use in-game behavioral and monetization data to identify player purchasing patterns, such as how frequently they engage with offers, their highest historical spend, or how close they come to making a purchase. Then create targeted pricing and offer structures that align with their profile.
Quick Cheat Sheet:
Segment players based on their current league or progression level to determine what types of content and rewards are most relevant to them. This helps identify what kind of offers, boosts, or bundles are in demand right now for their point in the game. For example, early-league players may need upgrade materials or currency boosts, while late-league players may respond better to exclusive cosmetics or high-tier progression shortcuts.
Create a second segmentation layer based on player pricing sensitivity—what price points they've historically responded to, ignored, or purchased at. This will essentially correct any mistakes done in the country pricing on level 2 as this will correlate more to what players react to already in the game.
Combine these two dimensions into targeted variant groups and compare them against a control group.
Now, for some combinations of prices and content (which you scale up or down based on price and discount), you may not yet have any offers available. You’ll need to create these missing combinations. This is a gap in your current offer supply, but it can be resolved by introducing new, the tailored offer vary based on the segmentations created in the previous steps.
Launch custom offers to the variant groups based on their league and pricing history using remote config (e.g. Firebase).
How to A/B Test It:
Compare control (default offers) vs. Variant (relevant personalized offers) but keep frequency and others parameters the same. You are testing the power of those offers so all other variables need to be the same for both groups.
Show packs when the player's current league, progression stage, and historical engagement suggest those offers are attractive. This ensures your in-game offer supply is fully aligned with current player demand in every possible way—by timing, pricing, and content relevance. Avoid showing the same offers repeatedly if they've been ignored in the past.
Measure : the long-term impact by tracking conversion, ARPPU, and overall ARPU. Create structured experiments to validate uplift. Ideally, both conversion and ARPPU increase at the same time—when this happens, overall ARPU tends to grow rapidly.
Secret Level: Macroeconomic Personalization in addition to Big Mac Index
Level Design: Use real-world data (GDP per capita, PPP indexes, income estimates additional to big mac index) to drive advanced pricing logic from the start of the game for each country.
Quick Cheat Sheet:
Group countries using external macroeconomic indicators
Build dynamic pricing clusters based on income expectations. Imagine country-tier pricing on steroids—each cluster has its own tailored base pricing structure for your store and offers. For example, one cluster might range from $0.99 to $30, another from $2.99 to $70, and a third from $5 to $120. This approach ensures that pricing aligns more closely with each region's purchasing power and unlocks the hidden revenue potential.
Adjust prices of all IAPs in the game based on country (or even state, where possible and compliant with local laws) to correct current pricing inefficiencies
How to A/B Test It:
Run pricing experiments by macroeconomic cluster
Apply changes only to new players to isolate effects
Some countries will see the same conversion but better ARPPU—leading to higher ARPU
Some will see lower ARPPU but significantly higher conversion—still leading to higher ARPU
Others may stay unchanged if they already have the “right” pricing
Can be combined with Level 3 (in-game behavioral segments)
Measure: ARPPU lift, conversion delta, engagement post-purchase, long-term churn
Final Tip:
Smart pricing is not about lowering everything. It’s about matching perceived value to the player’s context.
Start testing. Localize. Personalize. Level up your pricing. That’s how you unlock real IAP growth.
