Knowing which mobile game players might need a gentle nudge to return to a game is hard to tell in advance. Yet that critical information is necessary for optimal retargeting and retention.
Leading mobile entertainment provider SciPlay produces popular social casino and casual games. Millions of users worldwide play its games daily.
SciPlay had a solid retargeting campaign in place. However, after deep analysis, the company concluded that targeted campaigns aren’t necessary for all players. SciPlay decided to streamline that process via Pecan’s tech.
By implementing Pecan’s predictive analytics, SciPlay has a more efficient process in place to identify the right players for retargeting. With the refined foresight into player behavior, the company is also saving millions annually. Additionally, better-targeted offers and messaging also improve the player’s gaming experience.
Moving beyond business rules for improved retargeting
Like many mobile gaming companies, SciPlay previously guided retargeting campaigns with a set of business rules.
“We needed to allocate budget more efficiently, and doing that based on historical data and simple rulesets proved to be inefficient. We either limit our reach or spend more than we should on irrelevant audiences,” says Evyatar Livny, Vice President of Marketing Technologies at SciPlay.
Retention efforts are more effective when informed by predictive analytics. Machine learning models identify which players may need a nudge to return, allowing for better-targeted ads or offers that conserve marketing resources.
“Many users return naturally, and most will return within a few days or a week,” says Evyatar. “To retain a user effectively, you would need to reach that user with an ad as soon as possible, while the user is still ‘hot.’ We also want to offer a better experience. For example, we might offer an even bigger bonus for them to return or an enhanced feature based on their likelihood to return — hoping to create a bigger retention impact upon their reactivation.”
Pecan’s connectivity and flexibility have enabled faster predictive project turnaround times. SciPlay’s data flows into Pecan for modeling. Predictions are passed directly to Adjust as app events for directing campaigns across platforms.
The marketing team internally built and deployed models for each of the company’s seven games — generating “quick wins.”
SciPlay’s return on retargeting campaigns soars with Pecan
With Pecan’s predictions, SciPlay’s ROI and marketing efficiency have improved significantly.
“We’re able to get much better margins and invest our marketing budgets much, much more wisely with Pecan’s help,” Evyatar says. “We’re able to measure the real revenue impact accurately and determine the actual incrementality for retargeting. That saves us a lot of time and effort around lift testing, focusing on scaling the activity and the user journey itself, while also improving ROI.”
SciPlay continues to refine its predictive strategy with Pecan.
“We’re constantly striving to improve our models and getting into more granular levels, whether it’s a user-level, campaign-level, or source-level forecast,” Evyatar says. “Reacting faster saves money, makes us more efficient, and helps us spend the next dollar in the best possible way.”
- Pecan’s predictions guide more precise marketing to users who would benefit from retargeting, dramatically improving campaign ROI
- The marketing team could create predictive models internally using Pecan, without creating additional workload for other teams
- Players enjoy an enhanced game experience by receiving tailored special offers
- Data connectors streamline data sharing, including sending predictions directly to SciPlay’s MMP