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Playio Programmatric UA case study text

How Persona.ly Tripled ROAS D14 for Playio’s Play-to-earn App

Download the pdf version of the case study

We worked with Playio to acquire new users for their play-to-earn Android app in Korea. As a top-grossing platform in the category, the main goal of the campaign was to acquire active users who would play the games on the Playio’s app to earn rewards.

Results at a Glance

2.5x

Campaign scaling within 3 months

73%

CPI reduction within 3 months

209%

ROAS D14 growth by week 3

Ha-Young Park - Marketing Lead at Playio

“From day one, Persona.ly’s team demonstrated a deep understanding of our play-to-earn model and the importance of acquiring not just users, but engaged players who would generate revenue. Their sophisticated ML-driven platform allowed us to target the right audience with remarkable precision.

What impressed us most was Persona.ly’s commitment to continuous optimization. They didn’t just set up the campaign and let it run – they constantly refined their targeting, resulting in significant improvements in the performance.”

Ha-Young Park  – Marketing Lead at Playio

Programmatic UA Process

At the beginning of the campaign, using unattributed first-party data, we promptly generated a lookalike audience to target. Our programmatic DSP (demand-side platform) is integrated with all tier-1 ad exchanges. It processes over 4 million auctions per second and analyzes over 60 data-points before serving each impression. This allowed us to quickly gather initial data to narrow the targeting. After the initial phase targeting wider segments, our bidder was able to determine which segments were more likely to install the app.

During the next phase, our ML-driven engine generated a basic targeting model focusing on app installs.

As Playio’s main goal was to acquire active users who would install the app, create an account, and start performing in-app actions (play games, reach milestones, complete streaks), thus generating revenue for Playio, our ML-based targeting engine developed a unique classification model to target audiences that would more likely to retain and generate high ROAS.

Once we were able to identify these audience segments in the bid stream, we could safely scale the campaign while maintaining the CPI and improving ROAS.

Campaign Results

Campaign Scaling and CPI

When we started running the campaign for Playio, within the first few days, we were able to determine which audience segments would install the app. This allowed us to reduce the CPI by almost 60% by week 2. As we gathered enough positive signals to target audiences who would be more active in the app, by week 12 we scaled the campaign by 2.5 times while efficiently reducing the CPI by 73% compared to week 1.

Campaign-Scaling-and-CPI-for-Playio-UA-campaign-persona.ly-case-study

ROAS Growth

Due to the nature of the Playio app (where users are rewarded for in-app actions like playing games), it was crucial to acquire a highly engaged audience who would play games, thus generating revenue for Playio.Shortly after the exploration campaign, our ML algorithm was able to determine the most prominent placements. We used a wider contextual approach where the audience is targeted based on multiple contextual signals such as:

  • App category: Targeting apps based on their contextual proximity to the promoted bundle
  • Rewarded placements: Prioritizing rewarded ad placements

Measuring Bundle loyalty — user tendency to stick to the apps they are using — was another critical feature to shape the success of the campaign. 
As a result, we were able to triple ROAS D14 by week 3 (compared to week 1), and achieve another 80% increase by week 17 — all while scaling the campaign and maintaining the CPI.

ROAS-growth-for-Playio-UA-campaign-persona.ly-case-study

About Playio | GNA Company

Playio is a play and earn premier mobile gaming rewards app and loyalty platform that seeks to transform the industry by recognizing users’ hard work and play time while embracing both leisure and earnings.

Playio tracks valuable user data to recommend customized games, campaigns, and ads, using algorithms and an analytical process to bridge the gap between game developers and users.

Playio creates a community that not only rewards users with prizes and gift cards, but also enables them to interact with each other and feel both acknowledged and included through mobile games.

Rachel SEO - Business Development Director, Korea at Persona.ly (1)

“Collaborating with Playio has been an exceptional experience. Their team’s professionalism, along with deep understanding of the mobile environment, allowed us to leverage the full potential of our programmatic DSP. Together, we achieved remarkable results, showcasing the power of tailored, data-driven strategies in mobile gaming marketing. 

We are thrilled to bring success to another client in Korea and see that our constant efforts in the strategic Korean market help our clients thrive.”

Rachel SEO – Business Development Director, Korea at Persona.ly

About Persona.ly

Persona.ly is a mobile-first DSP operating worldwide. Using our proprietary bidder and machine-learning algorithms, we offer transparent, performance-driven, highly targeted UA and retargeting solutions at scale with access to over 4 million ad auctions per second. We are trusted by Nexon, NextNinja, Papaya Gaming, Rapido, Games24x7, Ubisoft, Tilting Point, and many others.

Persona.ly strives to be more than just a vendor for its partners, but a partner that helps generate actual value, growth, and broad marketing insights that can be used across channels.

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