Apptica Talks. Episode #9. Gamelight Effect: Wave of Rewarded Apps with Günay Aliyeva, Co-Founder at Gamelight

In this episode Apptica Talks about the Gamelight’s role in the rewarded UA industry with Günay Aliyeva – Co-Founder at Gamelight.

Gamelight is the largest Rewarded Marketing Platform for Mobile Games! Their AI algorithm analyzes users' playtime, engagement, competitor game usage & demographics data to identify users with the highest likeliness of long-term engagement on our partners' games.

What we have covered:

• Evolution of Rewarded UA
• Inspiration behind Gamelight's approach to rewarded UA
• Challenges when introducing a new model to the market
• Gamelight’s rewarded UA model
• Case studies of Gamelight with key metrics
• Gamelight’s Influence on the Industry
• The Future of Rewarded UA and Gamelight’s Vision
• What makes rewarded UA so effective in driving user engagement and retention
• Gamelight’s innovations to be released 
• Advice for leveraging rewarded UA for growth

Key Takeaways:

• Optimizing Rewarded Ads: Gamelight has transformed rewarded ads into a major growth driver by automating and optimizing processes that were previously done manually. Their AI-driven algorithm dynamically targets users and defines reward structures based on user behavior and game data, improving efficiency and maximizing the potential of rewarded marketing.
• AI Algorithm Advantages: The AI system uses large data points (age, gender, device data, game usage) to find patterns in user behavior and make precise targeting decisions. This approach is more effective than traditional manual targeting, which often relied on averages and predefined categories.
• Consent and Data Use: Gamelight ensures compliance with data privacy laws by obtaining consent from users to use their data for targeted ads. In return, users benefit from rewards in the games they play, making this a mutually beneficial system.
• Successful Case Studies: One key success was with AppQuantum, where Gamelight exceeded their return on ad spend (ROAS) targets, delivering over 91% higher results on day 30 for a specific game. The entire process was automated, showcasing the effectiveness of the algorithm without manual intervention.
• Applicability Across Genres: The AI algorithm works for various game genres, including both in-app purchase (IAP) and ad-monetized games. It can dynamically adjust reward structures for different users and games, ensuring high engagement and retention across genres, including casual, social, and strategy games.
• Content and Game Structure: Games with limited content or without a strong monetization structure are less suited for rewarded ads. Games need enough content and levels for users to engage long-term; otherwise, the advertising budget may not yield profitable results.
• Increased UA Budgets for Rewarded Ads: Initially, companies allocated small test budgets for rewarded ads, but with proven success, many companies now dedicate a large portion (up to 78%) of their UA budgets to rewarded ad channels like Gamelight, surpassing traditional UA methods in terms of performance.
• Challenges from Competitors: Gamelight faces competition from companies attempting to replicate its product, with some even copying the app's design or misrepresenting Gamelight’s work in pitch decks. However, Günay Aliyeva emphasized that competitors can’t replicate the back-end AI algorithms, which are key to Gamelight's success.
• New Product Innovations: Gamelight is constantly innovating, with one of their latest features being a ROAS bidding model, allowing partners to bid specifically for long-term ROAS optimization instead of just focusing on cost-per-install (CPI) or cost-per-engagement (CPE).

In summary, Gamelight’s AI-based approach has revolutionized the rewarded ads space by enhancing targeting precision, increasing user engagement, and improving UA performance across various game genres, making it a dominant force in the mobile marketing industry.

To get in touch with Günay:

LinkedIn

⬇️ Click the links below to discover the game-changing strategies behind rewarded UA:

Spotify

Apple Podcast

YouTube