Applovin is an amazing company with an even more amazing stock performance. Half a year ago you didn't need to look at the company's fundamentals to realize something very very very interesting was happening around its stock.
The incrementality challenge in digital marketing reminds me of the fundamental tension we face in e-commerce attribution. After spending years optimizing multi-channel campaigns (across social, search, and display), I've observed that the rush to attribute success to specific channels often overshadows the complexity of the customer journey.
The mention of lift testing particularly resonates - in my experience leading digital transformation projects in publishing and sports retail industries, we often discovered that our assumptions about channel effectiveness were incomplete at best, misleading at worst. This becomes especially critical when managing substantial marketing budgets where even small efficiency improvements can significantly impact the bottom line.
Two key observations worth considering:
1. The true value of new channels like AppLovin lies not just in their immediate performance metrics, but in how they complement existing marketing ecosystems (something often overlooked in the race for alternative platforms)
2. The democratization of lift testing tools could be transformative for SMEs - currently, many decisions are based on incomplete data simply because robust testing frameworks are cost-prohibitive
While Meta's dominance in TOF acquisition remains significant, I believe the future lies in developing more sophisticated, integrated approaches to channel attribution. The challenge isn't just finding new channels, but accurately measuring their true impact on revenue :)
Applovin is an amazing company with an even more amazing stock performance. Half a year ago you didn't need to look at the company's fundamentals to realize something very very very interesting was happening around its stock.
The incrementality challenge in digital marketing reminds me of the fundamental tension we face in e-commerce attribution. After spending years optimizing multi-channel campaigns (across social, search, and display), I've observed that the rush to attribute success to specific channels often overshadows the complexity of the customer journey.
The mention of lift testing particularly resonates - in my experience leading digital transformation projects in publishing and sports retail industries, we often discovered that our assumptions about channel effectiveness were incomplete at best, misleading at worst. This becomes especially critical when managing substantial marketing budgets where even small efficiency improvements can significantly impact the bottom line.
Two key observations worth considering:
1. The true value of new channels like AppLovin lies not just in their immediate performance metrics, but in how they complement existing marketing ecosystems (something often overlooked in the race for alternative platforms)
2. The democratization of lift testing tools could be transformative for SMEs - currently, many decisions are based on incomplete data simply because robust testing frameworks are cost-prohibitive
While Meta's dominance in TOF acquisition remains significant, I believe the future lies in developing more sophisticated, integrated approaches to channel attribution. The challenge isn't just finding new channels, but accurately measuring their true impact on revenue :)
(More thoughts on marketing attribution and experimentation here: https://thoughts.jock.pl/p/ai-tools-guide-2025-practical-implementation-creators)