Back to all articles
Memoriki Social Casino Programmatic Re-engagement case study text

How Persona.ly Outperformed Memoriki’s Full House Casino ROAS-based KPI by 290%

Download the pdf version of the case study

We worked with Memoriki — a top-grossing social casino publisher, to re-engage churned users for their Full House Casino app on Android. Full House Casino allows players to choose from an extensive range of popular casino games including Blackjack, Texas Hold’em, Baccarat, Sic Bo, and a great variety of Slot and provides an incomparable ultimate social casino experience.

Campaign Goal

The ultimate campaign goal was to re-engage churned users who had lapsed in the past 30 days. To measure the success of the campaign, a ROAS-based KPI was introduced.

Results at a Glance

2 Weeks

time to reach and start outperforming the KPI

2.91x

outperforming D7 ROAS KPI by week 4

2.5x

average IAP value growth by week 5

Nic Tso Memoriki

“I greatly appreciate our work with Persona.ly’s team. Their professionalism proved itself from the very first week of the campaign, when the results exceeded our KPIs. We look forward to continuing this successful partnership and driving further growth and innovation together.”

Nic Tso – Marketing Lead at Memoriki

Programmatic Re-engagement Process

In the case of Memoriki, we combined two approaches to target the audience:

  • Using Dynamic Audiences – our proprietary segmentation engine, we promptly generated an audience of users who had churned over 30 days ago.  
  • Audience provided by the client based on certain criteria.

Dynamic Audiences segmentation engine is Persona.ly’s programmatic platform feature, available to our clients at no extra cost. Integrated directly and safely (and adherent to global privacy-centric standards) with our clients’ first-party data, it allows us to update the audience in real-time, eliminating the need to pay for an external segmentation platform. With virtually any audience setup available, it allows setting multiple sets of rules to find the most prominent combinations for the highest performance.

Real-time audience updates  guarantee that the audience is added as soon as it fits the criteria (which might be crucial as with time the intent might get lower), and is excluded once users have converted or come back organically, which helps avoid overspending.

After collecting a substantial sample of re-attributions, including both re-engagements and re-installs, we utilized attributed data to refine our target audience. This approach allowed us to focus on users that would more likely to re-open or re-install the app. Once our programmatic bidder was able to define the criteria and determine which audience segments are more likely to convert by making multiple purchases after re-attribution, we were able to focus solely on those segments.

As the learning progressed, our DSP was able to better determine which segments would generate higher ROAS by either making higher purchases or making multiple IAPs. This approach allowed us to reach the ROAS-based KPI by week 2 and keep outperforming it in the following weeks.

Campaign Results

ROAS

By focusing on audience segments with a higher probability of making deposits after re-attribution, we were able to reach the ROAS-based KPI by the second week of running the campaign.

Our ML-based DSP allows us to focus on a specific goal and is able to determine the most prominent audience segments. We were able to outperform the KPI by almost three times by week 4.

Developed specially for our gaming clients, ARPPU prediction (or as we like to call it, “Whale Spotting”) feature allows our platform to better identify and determine “whales” (heavy-paying users) in the bid stream. This is done thanks to our platform’s age and gender-prediction capabilities, along with data enrichment based on multiple criteria.

Memoriki-programmatic-RT-ROAS-outperformance

The Effect of Bid Optimization on Average IAP Value

In order to reach a ROAS-based KPI, our bidder focused on two sub-targets:

  1. Acquiring audiences who would make multiple IAPs.
  2. Acquiring audiences who would make higher-value transactions

At the beginning of the learning process, the bid price was more conservative. Processing over 60 data-points before serving each impression, and our platform’s data-enrichment capabilities, allow for building a bidding model that would considers thousands of features’ combinations to find the right audience.

By adjusting the bid price to bid higher and essentially win the auction on the most prominent audiences, we were able to re-activate the audiences who would make higher and more IAPs.

This approach allowed us to increase the average IAP value by 2.5x by week 5.

The Effect of Bid Optimization on Average IAP Value

About Memoriki

Memoriki is a social casino developer and publisher that aims to provide its players with a grand variety of casino games while ensuring an unmatched gaming experience. With its focus on valuing quality and creativity, Memoriki constantly and consistently grows its international user base throughout its games.

“Partnering closely with Nic and the Memoriki team has been a great experience from day one. Their trust in our collaboration and shared goals allowed us to grow the campaign to great success, and unveil the huge potential for re-engagement campaigns in the social casino vertical.”

Dana Purinson – Business Development Manager at Persona.ly

About Persona.ly

Persona.ly is a mobile-first programmatic 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 3 million ad auctions per second. We are trusted by Nexon, OctaFX, 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.

Share
Processing...
Thank you! Your subscription has been confirmed. You'll hear from us soon.
ErrorHere