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Royal Escape programmatic mobile retargeting case study

How Gamee Scaled Royal Escape Retargeting 4x in Five Weeks While Beating the D1 ROAS KPI

Download the PDF version of the case study

We partnered with Gamee Studio to retarget churned users of Royal Escape: King Castle, a match-3 puzzle game, on iOS and Android worldwide. Royal Escape has exceeded 5 million downloads on Google Play and holds a 4.4-star rating across more than 113,000 reviews. Players match gems to break through barriers and work their way through the halls of a grand castle.

Results at a Glance

1.7x

outperforming the D1 ROAS KPI

>100%

campaign recoup from D7

4x

campaign scaling across both platforms in 5 weeks

Campaign Goal

The primary objective was to re-engage lapsed Royal Escape: King Castle players and bring them back into active gameplay. 

For a hybrid-casual title like Royal Escape: King Castle, the key challenge was to identify, among millions of users, those most likely to re-engage and become highly active players, driving strong IAA (In-App Advertising) ROAS.

We received a ROAS-based KPI to measure the success of the campaign.

Programmatic Retargeting Process

At the start of the campaign, we leveraged Gamee’s first-party data through Persona.ly’s Live Audiences segmentation engine to identify and segment lapsed players.

Live Audiences, available to our clients at no extra cost, is seamlessly integrated with our programmatic DSP. It allows us to update the audience in real time and gain insights from the beginning of the campaign.

Worldwide Setup Advantage

The campaign ran worldwide on both iOS and Android, allowing us to collect conversion signals at scale across markets within hours. Combined with integrations across top-tier ad exchanges and OEMs and over 4 million ad requests processed per second globally, this setup gave our programmatic bidder the data needed to quickly identify which audience segments were most likely to generate strong ROAS.

The bidder then used these early signals to optimize toward the highest-performing audiences and apply the learnings across markets, ultimately reaching hundreds of thousands of lapsed players.

Full-Screen Ad Formats for Incremental Re-engagement

We used exclusively full-screen ad formats, including interstitial and rewarded video placements.

While banner inventory is inexpensive and widely available, banner blindness can limit its ability to capture users’ attention and drive meaningful engagement. By focusing on full-screen placements, we were able we were able to minimize cannibalization of organic returns, prioritize higher-impact opportunities, minimize view-through attribution, and reduce spend on lower-value impressions.

Examples of full-screen ad placements used in the campaign.

Campaign Results

ROAS Progression and Campaign Recoup

By prioritizing users with the highest probability of returning to active play, the campaign exceeded the ROAS KPI from the first week on both platforms.
The campaign also reached full recoup early across both platforms.

On iOS, the first week’s cohort recouped the entire week’s spend by D1 and continued to grow, reaching 3x campaign spend by D30.

On Android, matured cohorts reached full campaign recoup by D14 and reached 1.6x campaign spend by D30.

Across both platforms, precise audience targeting and continuous bidding optimization enabled consistent ROAS growth over time.
More importantly, the campaign did not simply bring users back for a single session. We re-engaged players who had already demonstrated strong engagement with Royal Escape, resulting in users who returned multiple times, played longer sessions, and generated significant ad revenue.

70% ROAS D1 above the KPI on iOS. The campaign exceeded the ROAS KPI from the first week on both platforms.

Campaign Scaling

As performance stabilized, we increased weekly budgets by 4x across both platforms while maintaining KPI outperformance.

This demonstrates that the audience strategy and custom ML-driven targeting model could continue to perform as spend increased, rather than relying solely on a small initial pool of high-performing users.

Weekly campaign budget growth across iOS and Android over five weeks.

Reaching High-Value, Highly Engaged Players

Our ML-driven bidder includes vertical-specific features, including “ad whale prediction”, built for gaming clients focused on IAA or hybrid monetization. This capability identifies top-LTV users in the bid stream and adjusts bids based on both market price and the audience’s projected value.

The main challenge was to sift through millions of Royal Escape users and identify the segments most likely to re-engage with the game and become highly active. For a title monetizing primarily through advertising, these users can be identified through behavioral signals before they churn, including longer sessions and deeper level progression.

Ad Whales

Ad Whales – highly valuable users characterized by one or both of the following:

  • Generating ad impressions that generate premium eCPMs for the publisher
  • Playing longer sessions and watching a significant number of ads

This dynamic bidding strategy enabled us to successfully re-engage lapsed users who are highly valuable in the programmatic auction, where every ad impression they generate during the gameplay can earn a high eCPM for Gamee Studios. It also brought highly engaged players back to Royal Escape – users who play longer sessions and watch a significant number of ads.

The eCPM distribution chart in the case study illustrates the value of re-engaging players whose in-game activity can generate premium ad impressions.

High LTV users hybrid casual programmatic mobile retargeting campaign

About Gamee Studios

Gamee Global develops and publishes mobile puzzle and casual games, with a portfolio spanning match-3, pin-puzzle, and RPG titles, including Castle Match: Royal Quest, Haven Match: Mom’s Journey, Wonder Match: Amazing Family, and Home Pin 2: Family Adventure.

About Persona.ly

Persona.ly is a data-driven product company specializing in mobile user acquisition and retargeting, powered by proprietary machine learning algorithms and a robust first-party data management platform.

We help leading mobile companies including King, Tencent, Papaya, NextNinja, Tilting Point, Nexon and many others reach and exceed their growth goals by accurately predicting which users are most likely to engage and convert. Our machine learning models are optimized to target high-value users based on predicted LTV, driving strong ROAS and long-term user quality.

Our in-house programmatic DSP is directly integrated with top-tier ad exchanges and OEMs, processing over 4 million ad requests per second globally.

By combining real-time predictive analytics with programmatic scale, we empower our partners to unlock smarter growth, higher LTV, and measurable incremental impact.

With IMPACT, our incrementality measurement platform, advertisers can go beyond attribution to understand the true incremental value generated by Persona.ly DSP. IMPACT provides transparent measurement across audiences, segments, and campaigns, connecting media exposure with incremental conversions, revenue, and iROAS.

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