Jar aimed to attract and retain quality Android users who were likely to invest in digital gold and save regularly on the app. In India, scaling user acquisition effectively, affordably, and precisely is challenging due to the competitive and fragmented Android user market. Typically, apps like Jar are limited to walled gardens or self-attributing networks (SANs), which limit user data transparency and reach. Despite these challenges, Jar was committed to expanding its user base swiftly, sustainably, and economically, looking to broaden its user acquisition beyond these confines and into the open internet.

Jar partnered with Moloco to develop a marketing strategy using Moloco's advanced machine learning (ML) capabilities. This strategy helped Jar precisely target users likely to enroll in autopay sign-ups, reaching beyond the confines of walled gardens and into the vast open internet.

Utilizing granular, state-level targeting, an essential strategy in India's diverse market, Moloco's ML identified top-performing states for targeted marketing campaigns. Through precise targeting, Jar found high-value users and delivered relevant ads at the right time for the right price, maximizing both the impact of the ad and the efficiency of the campaign spending.

Moloco's ML-driven solution provided comprehensive log-level data, offering valuable insights into publishers, creatives, and exchanges. This level of transparency empowered Jar to manage its campaigns dynamically, utilizing its first-party data further to improve return on ad spend (ROAS). Moloco facilitated this process with quick campaign setups, seamless integrations, expert guidance, and responsive support.