사례 연구
Acquiring high-value users for Tokocrypto with predictive analysis and lowering customer acquisition costs
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Discover how Tokocrypto leverages ADA predictive analysis to reduce customer acquisition costs and target high-value customers, driving efficiency and growth.
As the crypto industry experienced a global boom in late 2021, Tokocrypto, an Indonesian-based crypto trading app, faced the challenge of sustaining growth amid increased market volatility in early 2022. To tackle our goals, we focused on the following:
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The strategy began with targeting a broad audience and refining actions based on gathered insights. Additional factors like offline and online behavior were considered, focusing on a mid to high affluence demographic in Jakarta and Java. Customized creatives were produced to align with specific audience segments, and programmatic affiliate channels were utilized to build look-a-like audiences. Predictive analysis models, behavior-based targeting, and device-based targeting were employed for optimization.
reduction in CAC against benchmark
growth in Monthly Active Users
growth in funnel conversion rates


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M1 needed to rethink how customers pre-ordered the Samsung Galaxy S25. The traditional experience of long queues, complex forms, and multiple customer service calls wasn't delivering the seamless journey their customers expected from a leading Singapore telco.
As the crypto industry experienced a global boom in late 2021, Tokocrypto, an Indonesian-based crypto trading app, faced the challenge of sustaining growth amid increased market volatility in early 2022. To tackle our goals, we focused on the following:
{{stats-component}}
The strategy began with targeting a broad audience and refining actions based on gathered insights. Additional factors like offline and online behavior were considered, focusing on a mid to high affluence demographic in Jakarta and Java. Customized creatives were produced to align with specific audience segments, and programmatic affiliate channels were utilized to build look-a-like audiences. Predictive analysis models, behavior-based targeting, and device-based targeting were employed for optimization.
reduction in CAC against benchmark
growth in Monthly Active Users
growth in funnel conversion rates
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