Skip to main contentSPLICE
Splice doesn’t just track who joins — it scores user actions, filters noise, and maps the dyanmics of loyalty across ecosystems. It does this through five interconnected systems that analyse user behaviour across games, quests, referrals, and social platforms, transforming scattered signals into a unified measure of loyalty and growth using state of the art machine learning algorithms.
The interpretation engine, responsible for coalating, converting, and condensing actions captured by the sub-systems — allowing teams to better understand users and take actions based on predictive insights.
An adaptive scoring framework used to interpret user actions. Every quest, match, or referral contributes to a weighted profile that reflects consistency, engagement, and impact.
A real-time activity monitoring system responsible for filtering out bots, repetitive claims, and synthetic activity to preserve accuracy and ensure authenticity.
A predictive analysis layer that interprets historical data to reveal emerging patterns. It enables teams to forecast retention, identify risks, and uncover the strategies that drive sustainable growth.
The aggregation system designed to consolidate data from multiple chains, applications, and platforms, providing a single, verifiable view of user retention. 
