Hire an AI store profit test planner

Everything it can hand back

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

• Corrected revenue and gross profit per visitor, a split of cold and warm traffic, and a trust score out of 100 for the numbers
• A friction list ranked by page and money at stake, a test idea for each item and a friction score out of 100
• A list of repairs to make now that need no test
• A leaderboard of test ideas, the one or two to run first and the reasons the rest wait

How it does the job well

• Work from the real catalogue, prices, stock and policies. Check variants and currencies.
• Judge changes by contribution margin, not revenue alone.
• Change one thing at a time on a live store and keep a way to roll back.
• Keep product claims consistent with supplier data and labels.

Mistakes it avoids

• Editing live products, prices or themes without approval or a backup.
• Ignoring shipping, returns and fees when judging profit.
• Copying competitor listings.

What a good result looks like

An example, not your task: You have traffic but no clear idea what to test on your store next.

• Step 1 file: Profit baseline. Your numbers fixed for tax, shipping and bots, revenue and gross profit per visitor, and a trust score.
• Step 2 file: Friction list. Friction ranked by page and money at stake, with evidence, a test idea for each and a friction score.
• Step 3 file: Test ranking. A fix list, a leaderboard of test ideas, the one or two to run first and the ideas parked.
• 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 Peep Laja would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Set the profit baseline. Fixes the dashboard numbers for tax, shipping and bots, works out revenue and gross profit per visitor, and shows how cold traffic pulls blended conversion down. It scores how far to trust the numbers.
• Watch the shoppers. A pause. You watch about 20 recordings each on the product page and cart, save heatmap screenshots and note any survey answers.
• Read the heatmaps and recordings. Matches screenshots to what shoppers saw, reads clicks and scroll depth and weights each friction by money, not raw clicks. Every item gets a test idea.
• Rank the test ideas. Splits repairs from tests, writes each idea as a hypothesis, counts the evidence and sizes the gain with your baseline. It names the one or two to run first.

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 find-the-store-change-most-worth-testing 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/find-the-store-change-most-worth-testing/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

• A store report with orders, sessions, revenue, tax, shipping and costs for a date range
• After the pause, heatmap and scroll map screenshots, notes from about 20 recordings each on the product page and cart, and any survey answers
• Customer reviews or survey comments (optional)

Tools and access

• Shopify: A paid plan. Net sales, shipping collected, tax, discounts and orders come from its reports.
• GA4: Sessions with fewer bots, and traffic split by source.
• Microsoft Clarity: Free heatmaps, area maps and recordings with the rage and dead click insights this skill reads.
• GA4: Free funnels in the Explore tab, and sessions you can compare with your platform dashboards.
• A store survey app: Gives you the 'why' behind what the heatmap shows, tied to order data.
• Any good chat AI: It writes hypotheses and does the profit sums from your pasted findings.
• A spreadsheet: Keep the leaderboard there so you can re-sort it when new proof comes in.

Functions and deliverables

• Store profit test planner: Calculate profit per visitor. Review real shopper behaviour and rank the page changes most worth testing.
  • Corrected revenue and gross profit per visitor, a split of cold and warm traffic, and a trust score out of 100 for the numbers
  • A friction list ranked by page and money at stake, a test idea for each item and a friction score out of 100
  • A list of repairs to make now that need no test
  • A leaderboard of test ideas, the one or two to run first and the reasons the rest wait
• Store profit per visitor calculator: Paste your Shopify and analytics numbers. Get corrected revenue and gross profit per visitor, and a trust score.
  • Revenue per visitor and gross profit per visitor, as given and corrected
  • A blended conversion check showing the effect of your cold traffic share
  • The link between conversion and the cost of getting a customer
  • What to track weekly, and a trust score out of 100 with the sum shown
• Heatmap and session recording analyst: Share heatmaps, page data and recording notes. Get possible shopping problems, evidence gaps, repair ideas and a plan for what to watch next.
  • A friction list ranked by page and money at stake
  • A hypothesis and a test idea for each problem, and a fix list for repairs
  • A watch plan for recordings: which, how many and when to stop
  • A friction score out of 100, now and after the fixes, with the sum shown
• Test idea ranker: Paste your research findings. Get each test written as a hypothesis and ranked by evidence and profit.
  • Each idea written as a hypothesis with a main metric and a smallest lift worth shipping
  • A ranked leaderboard with evidence points and a profit estimate
  • The one or two tests to run first, and the rest parked with a reason
  • A fix list for anything broken
• 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
• Peep Laja: Review page messaging or an A/B test using Peep Laja’s recorded approach. Start with buyer evidence, clarity and a sound comparison plan.
  • Your problem worked on the way Peep Laja would: their questions, their method, their push-back
  • The answer or the work, in Peep Laja'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 have traffic but no clear idea what to test on your store next.
• Your team keeps suggesting changes and you need a fair way to choose.
• Your conversion rate moved and you want to know whether it affected profit.

Limits to check before starting

• Your store gets only a few orders a week. Fix the obvious problems first, such as slow pages or unclear shipping costs, instead of running tests.
• You already have a test running and want to know if it worked. Use the A/B test traffic checker to see if you have enough visitors.
• Your sales dropped and you want to know why. Use the Ad sales drop analyst to find the cause first.

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 and every skill file this workflow uses.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Give it a store report for a recent range, with sessions, orders, tax and shipping.
• When it pauses, watch about 20 recordings each on the product page and cart. Save heatmap screenshots and write down what you saw.
• Make the repairs list first. Run only the tests it names, one at a time.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/find-the-store-change-most-worth-testing 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.