Hi @RJBu,
The short answer regarding out-of-the-box features is no. Adobe Target has not released a native, visual "Audience Splitter" tool inside the Audience Library to create mutually exclusive random cohorts (e.g., a 50/50 split of a specific audience to use across completely different activities).
For disjoint A/B testing assignment where you want to partition users before they hit an activity, you still have to rely on architectural design patterns.
Aside from the classic random integer math in profile scripts (Math.floor(Math.random() * 100)), here are the modern industry patterns used to handle this.
1. The "Experience Cloud ID (ECID) Hashing" Pattern
Instead of generating a completely random number on every session or evaluation, you can use the visitor's permanent ECID (MCID) to generate a stable, deterministic hash.
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How it works: You grab the ECID via a profile script or your data layer, extract the last few digits, or run a simple hash function (like a modulo operation) against it to assign a bucket number from 0 to 9.
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Why it's better than standard random math: It is completely stateless and deterministic. A user will fall into the exact same bucket across devices or platforms as long as their ECID is stitched, ensuring perfect long-term disjoint groups.
2. The "AEP / Real-Time CDP Segment Splitting" Pattern
If you are using the Adobe Experience Platform (AEP) Web SDK, the split should be moved upstream out of Target entirely.
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How it works: Within the AEP segment builder, you can use the Percentile Split function to create distinct audiences. For example, you can build Audience A (Top 50% of ECID Hash) and Audience B (Bottom 50% of ECID Hash).
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Why it's better: These flow into the Target Audience Library as separate, fully formed, mutually exclusive audiences. Target doesn't have to execute any logic; it just reads the evaluation state from the edge cluster.