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Trial-Then-Service Offer

Start buyers on a self-serve trial, then convert the ones who hit real limits into a hands-on engagement.

Pro moderate Special Offer Structures

What it adds

The AI builder uses your trial configuration, usage-limit definitions, and service scope documents to build a sequenced offer where the trial qualifies the buyer for a larger engagement. It converts because the trial produces evidence of need that no sales argument could establish, and the service pitch arrives exactly when the buyer feels the constraint. The goal is a self-selecting pipeline into higher-value work.

What your builder is told to do

8

The actual instructions, in order.
  1. 1

    Read the supplied trial and usage files and identify the specific limits or friction points that indicate a user actually needs hands-on service rather than more product.

  2. 2

    Define the trial honestly on the page: what is included, what is limited, how long it lasts, and what happens to data at the end, all from the configuration files.

  3. 3

    Design the trial experience to reach a real first result within its window; a trial that expires before value is delivered produces no qualified escalation.

  4. 4

    Build the escalation trigger around the documented usage signals, not elapsed days, and describe on the page what conditions lead to a service conversation.

  5. 5

    Present the service offer as an answer to the specific constraint the user hit, referencing the observed signal, with scope taken from the service documents.

  6. 6

    Keep a continue-self-serve path fully available; forcing escalation converts fewer users and damages the trial's credibility.

  7. 7

    Set breakpoints: on mobile trial status and limit indicators live in a compact persistent header with escalation prompts as dismissible cards; on tablet a sidebar shows trial progress alongside the main workspace; on desktop trial status, usage against limits, and the service pathway render together in a dashboard region without navigation.

  8. 8

    State clearly what carries over from trial to paid engagement — data, configuration, and any work performed.

Edge cases it handles

5

The things an agent skips when you only say "build a trial-then-service offer".
  • A user hits limits within hours; escalate immediately rather than waiting for the trial window to close.
  • A user never reaches a first result; trigger a documented assistance path rather than a service pitch.
  • The trial ends with data retention obligations; state the retention period and deletion behavior explicitly.
  • Users on the trial are not the buying authority; provide a share-with-stakeholder path in the escalation flow.
  • Service capacity is exhausted; queue the escalation transparently rather than hiding the offer.

Definition of done

7

Your builder is required to check every one of these before reporting the work finished.
  • Trial inclusions, limits, duration, and end-of-trial data handling are stated from configuration files.
  • The escalation trigger is based on documented usage signals rather than elapsed time alone.
  • The service offer references the specific constraint encountered and uses documented scope.
  • A continue-self-serve path remains fully available throughout.
  • Carry-over of data, configuration, and work is explicitly stated.
  • Mobile, tablet, and desktop each surface trial status and limits without obstructing the workspace.
  • The builder reports which trial and service files it used and which usage thresholds are assumed.

Related offer files

How it works

  1. 1

    Copy the link

    Grab the Markdown blueprint URL for this offer type.

  2. 2

    Give it to your builder

    Paste it into Claude Code, Cursor, Codex, or whatever AI builder is already working in your app.

  3. 3

    It maps, then builds

    Your agent reads the blueprint first, then builds the offer into your app around the product, audience, and stack.

Works with your stack

These blueprints are written to adapt. They tell the agent to detect your framework, match your existing design system, and use your source files instead of guessing the offer.

Need it tighter than that? Customize the offer file and tell it exactly which source docs and stack to use.