Yanolja enhances campaign efficiencies using predictive modeling in GA4

Yanolja enhances campaign efficiencies using predictive modeling in GA4

Discover how the leading Korean travel super app optimized the efficiency of their advertising budget.

Yanolja screenshots on pink background


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).

Our solution

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:

  • We implemented GA4 on Yanolja's app, ensuring it was setup to measure the complete user journey within the app along with key performance signals (bookings).
  • We allocated a 28-day period for the GA4 AI model to learn from and train itself on the collected user app data.
  • Following the training period, GA4 was able to predict customers who were likely to make a purchase within the next 7 days.
  • Leveraging the native integration, we activated the newly identified audience with Google Ads and tested it through a Google Ads App Install campaign.
GA4 and Google Ads diagram


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


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