Every pricing strategy has trade-offs. Exchange rates ignore purchasing power. PPP can underprice wealthy markets. GDP ratios produce extreme discounts. A custom blend lets you combine multiple data sources with your own weights, creating a pricing model that hedges against the weaknesses of any single approach.
A custom blend takes the price output from two or more strategies and calculates a weighted average. For example, a 60% PPP + 40% Exchange Rate blend for India would calculate:
PPP price for India: ₹349
FX price for India: ₹849
Blended: (₹349 × 0.60) + (₹849 × 0.40) = ₹549
→ Snapped to nearest Apple tier: ₹549
The result is a price that's lower than exchange rate alone (better for conversions) but higher than pure PPP (better for revenue per sale). You choose how far to lean in either direction.
There is no universal “best” blend. Here are starting points for different goals:
60% Exchange Rate + 40% PPP
Apps with strong US/EU revenue that want modest emerging market expansion
70% World Bank PPP + 30% GDP
Consumer apps targeting maximum global downloads
50% Netflix Index + 30% PPP + 20% Exchange Rate
Subscription apps benchmarking against digital spending patterns
40% PPP + 30% Big Mac + 30% Exchange Rate
General-purpose blend for apps with diverse global audiences
FAQ
Start with a hypothesis about what drives willingness-to-pay in your market. If you believe purchasing power matters most, weight PPP heavily. If you think digital spending habits matter, weight Netflix higher. Then test: compare the output of different blends for 5-10 key markets and see which produces prices that feel right. You can iterate over time based on conversion data.
In principle, yes — you could apply 80% exchange rate for developed markets and 80% PPP for emerging markets. In practice, a single blend formula is simpler to maintain and explain. If you find yourself wanting very different weights by region, it may be easier to use one strategy per region group instead.
That's precisely the value of blending — it smooths out outliers. If Big Mac Index says India should be $2 and exchange rate says $8, a 50/50 blend gives you $5. This hedges against any single index being distorted for a particular market. The more diverse your component strategies, the more robust the blend.
Two or three is usually optimal. More components add complexity without proportional accuracy. The incremental value of adding a 4th or 5th signal is typically marginal, and it becomes harder to understand why a specific market got a specific price.