Reinforcement Learning (Contextual Bandits)

Reinforcement Learning (Contextual Bandits)

Dynamic pricing that balances exploration (learning) and exploitation (profit) in real-time.

Live Report Preview

Interact with the mock decision board below.

Reward Learning Curve
Price Point Selection Frequency
Context vs Price Map
Price Waterfall (Global)
Counterfactual Policy Replay

Methodology & Governance

Transparent assumptions for CFO auditability.

Core Assumptions

  • Stationarity (reward function stable over short term)
  • Full feedback (we see conversion immediately)

Data Requirements

  • Episodes500k
  • Context Dim24 Features

Key Features

Device TypeReferrerTime of DayUser SegmentInventory Depth

Watchlist (Failure Modes)

  • Feedback loop delays (delayed conversions)
  • Non-stationarity (sudden market shift)

Ready to see your own data?

Upload your CSV and generate this Reinforcement Learning (Contextual Bandits) model in seconds.

Ask about ROAS, Attribution, or Budget...