Benjamin had already captured user interest with its innovative, gamified reward approach. However, growing competition in the rewards space meant that acquiring the right users was increasingly becoming difficult. The company needed to attract high-quality users who would engage and generate meaningful revenue by driving a strong return on ad spend (ROAS).

Benjamin adopted an advanced advertising strategy designed to identify and engage high-value users across the open internet, enabling sustainable growth despite these evolving privacy regulations.

Benjamin turned to Moloco to solve these challenges by harnessing the power of machine learning. The partnership focused on optimizing user acquisition through a dynamic, data-driven approach to maximize ROAS and long-term user engagement.

From CPA to ROAS

One of the first changes Moloco’s team recommended was shifting Benjamin's bidding strategy from a traditional cost-per-action (CPA) model to a more dynamic ROAS-based approach. This move allowed Benjamin to target users more likely to generate higher lifetime value (LTV). This supported ad spend for a pool of users most likely to engage and benefit from Benjamin’s gamified platform.

Overcoming iOS challenges

With the complexities of user acquisition on iOS, Moloco worked with Benjamin to develop a tailored framework focused on maximizing ROAS. By leveraging predictive models that accurately gauge user value despite limited tracking data, Moloco guided Benjamin in refining their bidding strategies for iOS. Together, they implemented testing protocols across CPA and ROAS campaigns, enabling Benjamin to adjust tactics dynamically and achieve a shorter payback window. This strategic approach efficiently helped acquire high-quality users, reinforcing the partnership's value in navigating an increasingly challenging environment.

Precise audience targeting

Moloco’s platform utilized both behavioral and contextual data to segment users with high precision. This enabled Benjamin to concentrate their marketing efforts on the most promising audience segments, users most likely to engage with Benjamin’s features. This fine-tuned targeting resulted in higher conversion rates and improved user retention, aligning perfectly with Benjamin’s growth goals.

Moloco's tailored solution, integrating advanced machine learning with precise targeting on the open internet, aligns directly with Benjamin's goals. This approach addressed immediate challenges and established a strong foundation for sustained success in the competitive rewards vertical.