{"id":18336,"date":"2026-09-29T10:23:23","date_gmt":"2026-09-29T10:23:23","guid":{"rendered":"https:\/\/persona.ly\/blog\/?p=18336"},"modified":"2026-09-29T11:07:06","modified_gmt":"2026-09-29T11:07:06","slug":"how-gamee-scaled-royal-escape-retargeting-4x-in-five-weeks-while-beating-the-d1-roas-kpi","status":"publish","type":"post","link":"https:\/\/persona.ly\/blog\/2026\/09\/how-gamee-scaled-royal-escape-retargeting-4x-in-five-weeks-while-beating-the-d1-roas-kpi\/","title":{"rendered":"How Gamee Scaled Royal Escape Retargeting 4x in Five Weeks While Beating the D1 ROAS KPI"},"content":{"rendered":"\n

Download the PDF version of the case study<\/a><\/em><\/p>\n\n\n\n

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We partnered with Gamee Studio<\/strong> to retarget churned users of Royal Escape: King Castle<\/em>, 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.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Results at a Glance<\/h2>\n\n\n\n
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1.7x<\/strong><\/p>\n\n\n\n

outperforming the D1 ROAS KPI<\/p>\n<\/div>\n\n\n\n

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>100%<\/strong><\/p>\n\n\n\n

campaign recoup from D7<\/p>\n<\/div>\n\n\n\n

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4x<\/strong><\/p>\n\n\n\n

campaign scaling across both platforms in 5 weeks<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Campaign Goal<\/h2>\n\n\n\n

The primary objective was to re-engage lapsed Royal Escape: King Castle <\/em>players and bring them back into active gameplay. <\/p>\n\n\n\n

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.<\/p>\n\n\n\n

We received a ROAS-based KPI to measure the success of the campaign.<\/p>\n\n\n\n

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Retargeting had been on our roadmap for a while, and we wanted a partner we could trust to execute it well. Persona.ly\u2019s expertise in programmatic retargeting was clear from the start – the team guided us through the audience strategy and setup rather than simply executing against a brief. \u2028<\/p>\n\n\n\n

What started as a pilot quickly turned into a broader growth opportunity as we saw strong results from the outset.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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The team has been responsive and transparent throughout the campaign, and we\u2019re now looking forward to extending the collaboration across more of our titles.<\/p>\n\n\n\n

Vu Thuy Van Trinh – Head of Marketing at Gamee Studio<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Programmatic Retargeting Process<\/h2>\n\n\n\n

At the start of the campaign, we leveraged Gamee\u2019s first-party data through Persona.ly\u2019s Live Audiences<\/em> segmentation engine to identify and segment lapsed players.<\/p>\n\n\n\n

Live Audiences<\/em>, 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.<\/p>\n\n\n\n

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Worldwide Setup Advantage<\/h2>\n\n\n\n
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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.<\/p>\n\n\n\n

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.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Full-Screen Ad Formats for Incremental Re-engagement<\/h2>\n\n\n\n
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We used exclusively full-screen ad formats, including interstitial and rewarded video placements.<\/strong><\/p>\n\n\n\n

While banner inventory is inexpensive and widely available, banner blindness can limit its ability to capture users\u2019 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.<\/strong><\/p>\n<\/div>\n\n\n\n

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Examples of full-screen ad placements used in the campaign.<\/figcaption><\/figure>\n<\/div>\n<\/div>\n\n\n\n
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Campaign Results<\/h2>\n\n\n\n

ROAS Progression and Campaign Recoup<\/h3>\n\n\n\n

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.<\/p>\n\n\n\n

On iOS, the first week\u2019s cohort recouped the entire week\u2019s spend by D1 and continued to grow, reaching 3x campaign spend by D30.<\/strong><\/p>\n\n\n\n

On Android, matured cohorts reached full campaign recoup by D14 and reached 1.6x campaign spend by D30.<\/strong><\/p>\n\n\n\n

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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.<\/p>\n\n\n\n

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70% ROAS D1 above the KPI on iOS.<\/strong> The campaign exceeded the ROAS KPI from the first week on both platforms.<\/p>\n\n\n\n

Campaign Scaling<\/h3>\n\n\n\n
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As performance stabilized, we increased weekly budgets by 4x across both platforms while maintaining KPI outperformance.<\/p>\n\n\n\n

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.<\/p>\n<\/div>\n\n\n\n

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Weekly campaign budget growth across iOS and Android over five weeks.<\/figcaption><\/figure>\n<\/div>\n<\/div>\n\n\n\n
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Reaching High-Value, Highly Engaged Players<\/h2>\n\n\n\n

Our ML-driven bidder includes vertical-specific features, including \u201cad whale prediction\u201d<\/strong>, 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\u2019s projected value.<\/p>\n\n\n\n

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The main challenge was to sift through millions of Royal Escape<\/em> 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.<\/p>\n<\/div>\n\n\n\n

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Ad Whales<\/h3>\n\n\n\n

Ad Whales – highly valuable users characterized by one or both of the following:<\/p>\n\n\n\n