Success Stories

Success Story - NOL | Appier

Written by Appier | Aug 18, 2025 10:11:48 AM

The Client’s Challenges : Hard to measure campaign performance in the Post-iOS 14.5 Era

After the rollout of iOS 14.5’s privacy policy, measuring iOS user acquisition performance and collecting sufficient data for machine learning through traditional media channels became increasingly challenging. This shift prompted NOL to explore a partnership with Appier’s Ad Cloud solution, by launching both user acquisition campaign (AIBID) and an engagement campaign (retargeting) in parallel, NOL aimed to drive new iOS user installs, boosting cross-category sales, and improving ROAS.

Achieved High UA Install growth and 180% ROAS through AIBID AI-powered Contextual Targeting of iOS users.

To acquire new app installs and drive ROAS, NOL leveraged Appier’s exclusive AI-powered purchase lookalike model combined with contextual targeting to overcome iOS limitations.
How it works : 

  1. Data Accumulation — During the first weeks, the campaign focused on scaling daily installs by leveraging non-IDFA data to train an install lookalike model, using high-propensity users as seed data for machine learning.
  2. Purchase Lookalike — Once sufficient training data was collected, the system shifted to a purchase lookalike model to identify high-value users not only to install but also to significantly boost ROAS efficiency.
  3. Contextual Targeting — Placing ads based on real-time environmental signals such as app content, inventory type, and user behavior instead of relying on user IDs, this approach identified Toss and Hana Money as top-performing inventories that indicate NOL’s high-value users.

By leveraging strong contextual signals from finance-related apps like Toss and Hana Money, Appier optimized bidding strategies and achieved early success with over 180% D7 ROAS, 600% install growth, and stable CPI in the post-IDFA era.

Creative Best Practices for User Acquisition in Travel Apps 

Beyond that, by analyzing additional campaigns across NOL’s core verticals — flights, leisure, and hotels — during the same period, we uncovered deeper strategic insights.
Insights we found:

  1. Inventory types, such as Toss, Hana Money, and Cashwalk delivered the highest performance, showing that NOL’s high-valued users are price-sensitive and respond strongly to discount-focused placements.
  2. Creatives, those emphasizing price advantages, product variety, seasonal or audience scenarios generated the highest performance, revealing that urgency-driven offers, assortment-focused, and seasonally or audience-relevant visuals represent best practices for travel apps like NOL’s

Given these insights, it’s clear that the campaign’s success was driven by a strong understanding of cashback and financial inventory audiences, the application of creative best practices for travel apps, and Appier’s exclusive AI-driven modeling coupled with dynamic bidding optimization, which enabled the continuous acquisition of high-ROAS users at cost-efficient CPI.

Post-UA Challenge: Reducing Booking Window and Driving Cross-Category Sales

After acquiring new users, NOL faced two key challenges in turning installs into further business growth:

  • Booking Window Length: Many users delayed bookings due to price sensitivity, date uncertainty, or multi-app comparisons — resulting in missed opportunities.
  • Cross-Category Purchases: Users hesitated to purchase full packages, such as flight + hotel or hotel + leisure bundles, and often turned to competitors for additional services.

Through targeted retargeting and personalized offers, NOL effectively shortened decision windows and encouraged multi-service purchases, resulting in 67% ROAS growth, a 71% increase in view-to-purchase rate, and a 24% uplift in GMV.

AI-Powered Personalization with Dynamic Product Recommendations

To enhance conversion rates and drive personalized ad experiences, NOL leveraged AI-driven dynamic product recommendations.

How It Works:

  1. The system analyzes user behavior, such as viewing multiple hotels in the same area.
  2. It generates a recommendation pool based on calculated relevance — for example, hotels located near those previously browsed.
  3. Multiple signals — including similarity to user preferences, popular items, and "view-also-view" patterns — are combined to dynamically score and rank products.
  4. Final product displays are continuously optimized in real time to ensure the most relevant offers appear first.

This AI-driven approach not only improved user experience but also delivered tangible results, driving a 71% increase in view-to-purchase rate.

Boost Cross-Category Sales with Tailored Bundles and Exclusive Benefits

To drive higher-value purchases and simplify decision-making, NOL introduced location-based bundles and exclusive offers.

From user data we found some insights on high value users:

  • High-AOV Travelers: With significant purchases in the past 60–90 days, likely planning their next trip.
  • High-CVR Intenders: Show strong intent through repeated views and searches.

For these groups, NOL offered tailored product combinations — such as domestic hotel + domestic leisure packages — to increase order value and cross-category sales.

For new download users, incentives like 10% off their first purchase and VIP benefits such as a Gold Class free trial were provided to accelerate their first transaction and encourage broader engagement across services.

By combining smart segmentation with relevant offers, NOL successfully encouraged multi-service purchases, contributing to a 24% uplift in GMV.

Looking Ahead: Scaling Success with AI-Powered Solutions

NOL’s strong results highlight the value of AI-driven targeting and personalization in the post-IDFA era.

Donghan Shin, Performance Marketing Lead at NOL, shared: “We’ve worked with Appier for more than three years and truly value their AIBID and Retargeting solutions. Aipper's AI-powered contextual targeting has helped us reach high-value users, while personalized content has maximized cross-category purchases — particularly in the post-IDFA environment. Thanks to this partnership, we’ve seen strong, consistent performance across our core product categories. We truly appreciate the collaboration and look forward to achieving even more together.” 

With continued collaboration, NOL is well-positioned to drive even greater growth.