The Consumer World Model.

Behavior Model

A model of how your members actually behave.

A compact behavioral model trained on your members' own event stream — visits, purchases, points, opens, clicks, dozens of governed event types — one model per brand, never pooled across customers. It learns each member's behavioral fingerprint and keeps a live read on what tends to come next: purchase or lapse, and when.

• ✓Member embeddings — a behavioral fingerprint per member — the engine behind lookalike audiences
• ✓Next-event prediction — purchase and churn probabilities that feed segments and the agents
• ✓Timing — each member's next-purchase window and the hour they actually engage

Honesty gate:the model only goes live for your brand after it beats a transparent baseline on your own held-out data. Until it earns that, the platform runs on glass-box math — it never fakes a model it doesn't have.

Digital Twin

A simulation of what your members would do next.

The same model, run forward. The digital twin plays a plan against your member base before reality does: a campaign versus deliberately doing nothing, a journey change versus the status quo — member by member, rolled up into an honest forecast, calibrated against held-out reality.

• ✓Counterfactual rollout — simulate the campaign and the silence, and read the difference
• ✓Held-out calibration — forecasts are checked against reality the model never saw
• ✓Research twins — de-identified member twins you can pre-test surveys and concepts onEarly access

Honest by design:a simulation is a rehearsal, not a promise. The twin reports confidence with every number and stays silent where your data can't support an answer — it will tell you “not enough signal” before it tells you a story.

Find more members like your best ones.

Pick a handful of proven members — top spenders, a winning segment, even a single VIP — and the behavior model finds the members whose behavioral fingerprint sits closest to theirs. Not “same age, same city”: same rhythm of visits, categories and responses, read from what they actually do.

See churn forming — and act while it's still cheap.

For each member the model keeps a live read: how likely their next purchase is, how likely they are to lapse, and what's at stake if they do. When the risk crosses your line, the decision goes to the agents — SoClaw picks one fitting gesture (or deliberately none) inside your guardrails, proven against an untouched control.

Play the campaign forward before you send it.

The digital twin runs your campaign against the model of your base — and runs doing nothing as the counterfactual — so you see the expected difference before a single message goes out. Forecasts are calibrated against held-out reality, and the model says so when it doesn't have enough data for an honest answer.

The right member, at their own right moment.

Each member has a purchase rhythm and an hour of day when they actually engage. The model learns both — when the next purchase is due, when this member opens and clicks — so sends land in each member's window instead of everyone's Tuesday 10am.