Case Studies
Real results from real creative teams
See how performance and creative teams use Segwise to back every creative decision with data, and improve their ROAS with data-backed creative generations.
Digital Ad AgencyHow Medialicious scaled AI creatives to 30% of ad spend across its portfolio
Learn how Medialicious, a digital advertising agency running paid user acquisition across a large multi-brand portfolio, made Segwise the engine of its creative pipeline, to the point where AI-made ads now carry nearly a third of the budget.
Read case studyResults~30%of total ad spend~150assets / week#1static in the flagship app
Rewards AppInfluence Mobile improved D7 ROAS by 10% immediately with Segwise
Influence Mobile runs paid user acquisition for Rewarded Play. By moving its creative testing into Segwise, the team started backing every call with data, and the ads they built off it pulled in better early ROAS.
Read case studyResults↑10%D7 ROAS↑9%D1 ROAS~30%spend share
Consumer AppsHow Mode Mobile's UA team catches breakout creatives and fatigue early with Segwise
Mode acquires consumer apps for their engaged customer bases. Its portfolio includes the Mode Earn App, NGL, Trimbox, and Applock Pro. At this scale, the UA team can't afford to sit on a creative decision for even a week.
Read case studyResultsEarlier detection
Breakout creatives spotted early
Automated reporting
Reporting fully automated
Faster iteration
Faster creative iteration
Ride-HailingHow Namma Yatri finds its winning ad themes across cities with Segwise
Namma Yatri, a ride-hailing app in India, uses Segwise, an AI creative analytics and generation platform, to identify winning ad creative themes across cities. The team queries performance data through AI chat instead of dashboards, gets weekly alerts on campaign health, and works from a region-split account for clean city-level insights.
Read case studyResultsData-backed briefs
Design briefs built from patterns spotted across campaigns, objectives, and cities
Clean city-level data
Account split by region, so each city's data and insights stay separate and clean
Early warnings
Weekly alerts flag campaign issues before they get expensive