Segwise is a tool designed to help maximize Return on Ad Spend (ROAS), and optimize in-app purchases, ad revenue, and user retention for mobile games. The tool is developed to aid gaming studios in reducing their cost per installation (CPI) and enhance the integration process by eliminating the need for coding.
Segwise uses AI agents to identify and exploit hidden opportunities across campaigns, in-game events, and app performance data. One of the key features of the tool, MELRON, serves as an always-on ROAS analyst.
It uses Causal inference models on terabytes of player data to detect player demographics and in-app behaviors which affect ROAS. The tool also hyper-segments player data across millions of user dimensions and values, running anomaly detection models to provide insights on metric movement.
Additionally, Segwise offers the capability to ask any questions about ROAS metrics for instant answers tailored to specific data. Finally, Segwise provides a seamless, no-code integration with all data sources and warehouses.
<img src="https://static.wixstatic.com/media/0ad3c7_ee1c424967824936af003a05dd992fa1~mv2.png" alt="Featured on Hey It's AI" style="width: 250px; height: 50px;" width="250" height="50">
Get to know the latest AI tools
Join 2300+ other AI enthusiasts, developers and founders.
Ratings
Help other people by letting them know if this AI was useful. All tools start with a default rating of 3.
- Share Your ThoughtsBe the first to write a comment.
Pros & Cons
Maximizes ROAS
Optimizes in-app purchases
Boosts ad revenue
Aid in user retention
Reduces CPI
No-code integration
Targets mobile games
Assists gaming studios
MELRON feature
Always-on ROAS analyst
Causal inference models usage
Terabytes of player data
Detects player demographics
Identifies influencing in-app behaviors
Hyper-segments player data
Anomaly detection for insights
Ability to query ROAS
Integration with all data sources
Integration with data warehouses
Built by industry expert creators
Spot hidden ROAS opportunities
Root cause ROAS inputs
Capable of data hyper-segmentation
Fine-tuned LLMs
Boosts D7 ROAS & Retention
Saves weekly operational hours
No MAU based pricing
Transforms data analysis
Limited to mobile gaming
Focused on ROAS only
No-code may limit customizations
Dependent on data warehouses
May miss non-digital metrics
Bias towards in-app revenue
Options for anomaly detection unclear
MELRON -- usage complexity
Specific data sources integration
Depends on large user dimensions
Alternatives
Featured
%20(1).webp)
.webp)
.webp)
Sponsored listings. More info here: https://www.heyitsai.com/sponsorships