How Persona.ly Topped Cost Per Trader KPI by 40% for Exness Go Multi-asset Broker App
Persona.ly worked with Exness, a global multi-asset broker to attract new traders for their app Exness Go. Exness Go is an app allowing over a million of brokers around the world to trade their assets on stock markets.
Campaign Goal
The ultimate campaign goal was to bring users who would register an account and become active traders in the app by making their first transaction, with a certain cost per active trader acquisition being a KPI.
Results at a Glance
41%
Topping the cost per active trader acquisition KPI
+93%
Campaign scaling on week 6 vs. week 1
44%
More deposits per trader by week 5 vs. week 1
2x
IPM (Installs per Mille) increase by week 5
“Working closely with Persona.ly’s team has been an exceptional experience for us at Exness. Their dedication, expertise, and proactive approach were instrumental in achieving our goals and hitting our KPIs. We look forward to growing our partnership and continue to leverage their ML capabilities to drive even greater success in our future endeavors.”
Pei Ning Lee – Senior Paid Media Specialist at Exness
Programmatic User Acquisition Process
During the campaign exploration phase, our approach was to target a lookalike audience based on the first-party data provided by the client.
Integrated with all the major ad exchanges and processing over 3M ad requests per second, our bidder shortly received enough positive signals (impressions and installs) helping our models classify which user cohorts will install the app. This allowed our machine learning-based platform to build the initial targeting model focusing on app installs.
Following the initial exploration, as more data was acquired, our programmatic bidder was able to train an advanced classification model to distinguish between the audience segments who would click the ad, install the app, and complete the registration and those who wouldn’t register.
Having access to over 60 data-points before serving each impression helps our bidder identify the most prominent user segments to run effective UA and retargeting campaigns. Based on the learnings from the previous phases, a custom ML model was built. This model allowed us to focus on audience segments with a higher probability of becoming active traders (new users who have registered in the app, made their first transaction and most likely will keep making transactions).
Finally, being able to classify and safely predict the most prominent audience cohorts to bid on, we managed to safely scale the campaign while topping the KPI by a significant margin of 40%.
Campaign Results
Campaign Scaling
The initial campaign setup targeting lookalike audience based on the existing app audience had outperformed the cost per trader acquisition KPI by 60% in the first week of running the campaign.
As the learning progressed and our bidder collected more positive signals to predict which audience cohorts will more likely to convert by becoming active traders, we were able to scale the campaign almost twice while topping the cost per trader acquisition KPI by 41%.
Over time, being able to better classify the audience cohorts and bid more precisely, we managed to double the IPM (Installs per Mille – installs per 1000 impressions) by week 5.
Deposits per Trader
Our platform’s ML capabilities allow our programmatic bidder focus on cohorts of users with the highest potential of becoming recurring traders.
In the case of Exness Go, by targeting audiences based on their predicted gender, age class and affinity to the Exness Go app, we have managed to acquire highly engaged user cohorts who will make multiple deposits to their account. This approach allowed us to increase the average number of deposits per trader by a significant 44% by week 5 into running the campaign.
About Exness
Exness is a leading broker that offers a wide range of trading products and features, with its main goal being to provide the most comprehensive and beneficial trading experience. Using their innovative technology and scientific approach to trading, Exness has been able to create a stellar trading environment and allowed them to become the largest retail market maker in the world.
“Partnering closely with Exness has been an incredible experience. Their team’s professionalism and trust in our expertise has played a crucial role in delivering those great results and showing once again the power of machine learning-based UA in the trading niche. It’s truly gratifying to see our collaborative efforts translate into tangible success, and I’m excited to continue achieving even greater milestones together, fueled by our mutual trust and dedication.”
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.
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