Hire an AI free-sample customer acquisition reviewer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A free sample offer in words you can use, who gets it, how they claim it and a capped budget
• A small test in four or five places, what to measure, and a roll out, change or drop rule set before you start
• What a customer really costs for each ad, headline and offer, how soon sales cover it, the most you can pay for a customer and which ads to keep

How it does the job well

• Write for one named audience and one action. Each asset has a single job.
• Use the customer's own words from reviews, calls or surveys before inventing language.
• Every claim needs proof the business can show. Leave unproven claims out or mark them.
• Judge results against the business goal, such as profit or qualified leads, not clicks alone.

Mistakes it avoids

• Generic copy that could fit any brand.
• Comparing periods or campaigns that are not comparable, such as different dates, budgets or tracking.
• Calling a test winner before there is enough data.

What a good result looks like

An example, not your task: You are launching a product and want to try it on a small crowd before you spend big on ads.

• Free sample offer. The offer in words you can use, who gets it, how they claim it and a capped budget.
• Small launch test plan. One question, four or five places to try it, what to measure and a roll out, change or drop rule.
• Cost per customer. Cost by ad, headline and offer, days to pay back, the most you can pay for a customer and ads to keep.
• HAND-BACK SUMMARY. Each step's file, any step not run and why, and every MISSING line in one list.

How the work is checked

• Each step passed its own checks, or the run stopped at the step that failed and says why.
• The steps ran in order, and each one used the result of the one before.
• Nothing was invented to fill a gap. Every gap is a MISSING: line.
• Nothing was sent, published or paid for without a clear yes.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way Claude Hopkins and Alex Hormozi would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Design the sample. Picks the smallest piece a buyer can try, says who gets it and how they claim it, and caps the sample budget.
• Plan the small test. Takes the offer from the step before and sets one question, four or five places to try it and a rule for roll out, change or drop.
• Work out the cost. Takes your test numbers, counts real customers instead of replies, and shows cost per customer, how soon it pays back and which ads to keep.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id free-sample-launch only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/free-sample-launch/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• Your product facts, such as what it is, its size and what it costs to make
• Your price
• Your current offer (optional)
• A sample budget and where you could offer it, such as towns, lists, shops or channels (optional)
• Costs for ad space or spend, samples, handling and follow-up, after the test
• Replies and orders for each ad, headline or offer, after the test
• Repeat orders you can show (optional)
• Time to run the test in a few places

Tools and access

• Any good chat AI: Writing an offer and a cost check is text work any strong chat AI does with this skill.
• A form tool with unique links: Gives each source its own key so you can trace replies.
• Any good chat AI: Designing a test and a decision rule is text work any strong chat AI does with this skill.
• A spreadsheet: Holds the table and works out cost per customer.
• Any good chat AI: Adding costs and ranking ads is work any strong chat AI does with this skill, given clean numbers.
• A spreadsheet: Holds the table and lets you check each sum.

Functions and deliverables

• Free-sample customer acquisition reviewer: Plan a sample offer and small launch test, then use real replies, orders and costs to review customer acquisition.
  • A free sample offer in words you can use, who gets it, how they claim it and a capped budget
  • A small test in four or five places, what to measure, and a roll out, change or drop rule set before you start
  • What a customer really costs for each ad, headline and offer, how soon sales cover it, the most you can pay for a customer and which ads to keep
• Free sample offer planner: Plan a free sample offer that reaches buyers and stays within budget. Give your product and price. You get the offer, claim steps and a cost check.
  • A sample offer in words you can use
  • Who gets it and how they claim it
  • A sample budget with a cap and keys on every reply
  • A cost-per-customer check before you start
• Small launch test planner: Plan a small launch test for an offer you doubt will sell. Get a few test places, what to measure and a roll out, change or drop rule.
  • The one question the test answers
  • Four or five test places with a reason for each
  • What to measure and how to record it
  • A roll-out, change or drop rule set before the test
• Cost per customer calculator: Work out what a customer really costs from your ad costs, samples and orders. See payback time and which ads to keep. Give it your numbers.
  • The full cost per customer by ad, headline and offer
  • How soon sales cover the cost
  • The most you can pay for a customer
  • A data score out of 100 and which ads to keep
• Brand profile builder: Share your website. Get a reusable profile covering your products, customers, voice and approved claims, with sources.
  • A folder of eight plain files, from a start file for your AI to a claims list and a change log
  • A tag on every fact, and every claim marked approved, pending or banned
  • A two-sentence diagnosis of your biggest gap, and a list of what's missing and who can answer it
  • A short slice for your next step, if you name one
• Claude Hopkins: Write specific ads or plan a small buyer test using Claude Hopkins’s recorded approach. Replace vague praise with facts and track cost per customer.
  • Your problem worked on the way Claude Hopkins would: their questions, their method, their push-back
  • The answer or the work, in Claude Hopkins's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• Alex Hormozi: Improve an offer, price or lead plan using Alex Hormozi’s recorded frameworks. Check buyer needs, costs and honest promises before adding more leads.
  • Your problem worked on the way Alex Hormozi would: their questions, their method, their push-back
  • The answer or the work, in Alex Hormozi's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You are launching a product and want to try it on a small crowd before you spend big on ads.
• Your ads bring plenty of replies or clicks, but you cannot tell what a paying customer costs.
• You have a new offer or idea and want a clear rule for when to roll it out, change it or drop it.

Limits to check before starting

• You have no price or ad history yet: use the Ad test brief writer first to plan what to test.
• You only want the sample offer itself: use the Free sample offer planner.
• You want to check a discount against margin and ad cost: use the Discount margin and ad-cost checker.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the handoff pack. It's a zip with HANDOFF.md plus one skill file for each step.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Give it your product and price. It writes the sample offer and the test plan, then stops.
• Run the test in a few places and write down samples sent, replies and orders for each place.
• Bring the numbers back and say "carry on". Read the cost per customer last.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/free-sample-launch for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.