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Yanolja enhances campaign efficiencies using predictive modeling in GA4
Discover how the leading Korean travel super app optimized the efficiency of their advertising budget.
Discover how the leading Korean travel super app optimized the efficiency of their advertising budget.
Yanolja is the fastest-growing travel platform and the only 'Unicorn' among travel related companies in South Korea. Their global travel super app offering all kinds of services related to accommodations, leisure, transportation, restaurant, and shopping. Yanolja wanted to look for new ways to optimize the efficiency of their advertising budget designated for driving acquisition (new app installs).
Jellyfish and Yanolja collaborated to explore the potential of leveraging the predictive modeling functionality of Google Analytics 4 (GA4) to uncover new audiences and increase advertising efficiency:
33% Decrease in Cost Per Install (CPI) when compared to control group.
“After utilizing GA4's predictive modeling, we noticed a higher install volume and an excellent Cost Per Install (CPI) compared to the control group. The performance is comparable to our existing campaigns, which have been optimized over the medium to long term. We plan to expand this approach to iOS in the future.”
Seungwon Cha, Performance Advertising Team Manager, Yanolja
After two years of existing happily alongside GA4, Google Analytics Universal (or GA3) will be deprecated and will give way to GA4 next year. This handover marks a turning point in data-driven marketing, because, as we already see it, GA4 radically changes data usage, from collection to activation
Read ArticleGoogle has announced that in July 2023, Universal Analytics will stop processing new hits, effectively sunsetting the platform. In its place is the already available Google Analytics 4 (commonly known as GA4), the newest generation of Google’s analytics measurement solution.
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