DEJAN's Content Optimizer uses a Bayesian acquisition policy (such as Thompson Sampling or UCB) to iteratively test hypothesis claims, where an ideator crafts targeted content variants and a re-ranker model evaluates the draft against competitor pages across multiple samples to discover what features improve AI ranking.
flowchart LR
A[Seeder: Hypotheses Claims] --> B[Acquisition: Thompson Sampling]
B --> C[Ideator: Craft Variant]
C --> D[Ranker: N-Sample Evaluation]
D --> E{Reward: Improved?}
E -- Yes --> F[Update Posterior: Alpha + 1]
E -- No --> G[Update Posterior: Beta + 1]
F --> B
G --> BReferenced by