Voice, facts, boundaries, commercial rules, and handoff conditions.
Existing prompts and scripts are audited before new rules are layered on top.
One-model pilot
Prove the operating model before you scale the automation.
Start with one model, one primary channel, and real workflows. FanLTV maps the current operation, configures the model, begins under human control, and measures what should automate next.
Pilot scope
A working implementation, not a detached chatbot demo.
The exact schedule and commercial scope are agreed after the initial workflow review.
One production connection with history, events, send permissions, and recovery checks.
The readiness check covers the provider plan and account-specific limitations.
One priority route: chat, PPV, customs, reactivation, or FYP.
Start where the agency has a measurable bottleneck rather than enabling everything at once.
Rollout path
Control first. Automation after evidence.
- 01 / AuditMap the current operationReview conversations, content, commercial rules, channel access, exceptions, and baseline economics.
- 02 / ConfigureBuild the model contextSet voice, memory, states, conditions, pricing, content routes, safety, and agency permissions.
- 03 / ValidateRun manual or assistedInspect decisions and replies on real traffic while delivery and provider behavior are verified.
- 04 / ExpandAutomate proven routinesMove only stable workflows to auto and keep valuable uncertainty with people.
Real workspace, supervised rollout
Review the relationship and the decision in the same place.
The pilot uses actual channel behavior while preserving manual control, visible delivery state, and an accountable history of what the system did.
Review production evidencePilot report
Know what changed, what stayed human, and what to do next.
A useful pilot closes with operational and commercial evidence, not only a list of generated messages.
Work handled and recovered
Inbound coverage, unanswered recovery, proactive eligibility, delivery success, duplicate prevention, and human exceptions.
Conversation behavior
State progression, memory use, language consistency, repetition, offer timing, safety handoffs, and operator corrections.
Revenue and workload
Payment outcomes, repeat purchases, reactivation, operator hours, provider/AI costs, and expected LTV impact where the data supports it.
Commercial structure
Scope before price.
Pilot pricing depends on the channel, message volume, content workflow, model configuration, and the amount of supervised setup required. FanLTV does not hide those variables inside a generic seat price.
The proposal separates FanLTV implementation and usage from third-party provider, platform, payment, and model/API charges. The initial review defines what is included, what remains optional, and what success will be measured against.
Request the pilot
Bring one model and the workflow that matters most.
We will contact you to confirm the channel, access method, baseline, and safest starting mode.
- No password handoff required for the initial audit
- Manual or assisted validation before full auto
- Scope, external costs, and success metrics agreed before connection