Research Script Templates

These UserTold.ai study templates cover common acquisition and product-learning use cases: onboarding, activation, churn, pricing, and feature validation.

Treat them as starting points. The best script names the workflow, expected behavior, common failure points, and the exact evidence you need before creating a work item.

Onboarding template

Use when a new user is trying to understand setup, account creation, or first configuration.

{
  "version": 2,
  "goals": [
    { "id": "first-setup", "description": "Identify where new users hesitate before completing initial setup." }
  ],
  "segments": [
    {
      "id": "intro",
      "mode": "speak",
      "title": "Intro",
      "speak_text": "Please complete setup as you normally would. I will stay quiet while you work."
    },
    {
      "id": "onboarding-observe",
      "mode": "observe",
      "title": "Complete onboarding",
      "instruction": "Create your account and reach the first usable project screen.",
      "conductor_context": "Expected flow: account details -> provider connection -> project creation -> confirmation. Watch for repeated navigation, docs visits, and uncertainty around required credentials.",
      "max_duration_s": 420
    },
    {
      "id": "onboarding-debrief",
      "mode": "talk",
      "title": "Debrief",
      "talk": {
        "goals": ["first-setup"],
        "system_prompt": "Ask about the moments where the participant paused, backtracked, or used docs. Ask what they expected and what happened instead."
      }
    }
  ]
}

Activation template

Use when the team needs to know whether users reach first value.

  • Start with one speak instruction that defines the goal.
  • Use observe for the actual activation task.
  • Debrief the first moment the user believed the product became useful.

Good activation prompt:

Complete the workflow until you have something you would be willing to use or share with your team.

Good evidence:

  • first value reached or not reached
  • page where the participant stalled
  • workaround used to continue
  • quote explaining what value they expected

Churn-risk template

Use with users who stopped using a workflow or downgraded usage.

Recommended sequence:

  1. talk: capture the last concrete time they tried the workflow.
  2. observe: ask them to repeat or reconstruct the workflow if possible.
  3. talk: ask what they did instead and what would have changed the outcome.

The key evidence is the substitute behavior. Churn is often explained by the workaround the user adopted after the product failed them.

Pricing template

Use when buyers hesitate, misunderstand limits, or cannot map plan details to their use case.

Recommended observe instruction:

Choose the plan you would recommend for your team and explain out loud what you are considering.

Recommended conductor_context:

Watch for plan comparison loops, repeated FAQ visits, uncertainty around credits, BYOK costs, team limits, or whether a usage pattern fits a plan.

Follow with a talk debrief that asks what information was missing at the decision point.

Feature validation template

Use before or after shipping a feature to learn whether the workflow solves the intended job.

Recommended sequence:

  1. talk: ask about the recent job or trigger.
  2. observe: have the participant use the feature for that job.
  3. talk: ask whether the result would replace their current workaround.

Strong validation evidence includes:

  • the user's existing workaround
  • where the feature fit or failed
  • the final output they expected
  • whether they would use it again without prompting

Turning templates into work items

After interviews complete, review evidence by workflow area and create work items only when there is enough evidence to act. A single confusing quote can be useful context; repeated struggling moments in the same workflow are a stronger delivery candidate.

Qualified next step

Pick the template that matches the product risk you are investigating, then adapt it with the field-level guidance in the study design guide. If the study produces repeated evidence, use from interviews to issues to move the work into Linear or GitHub.