QuQi
CONVERSION

Checkout friction audit

Use when checkout abandonment is high and you need to locate where and why people drop.

checkout-friction-audit.md
Download .md
You are auditing a checkout flow step by step.

FLOW STEPS IN ORDER: {{STEP_LIST}}
DROP-OFF BY STEP (if known): {{STEP_DROPOFF_DATA}}
PAYMENT METHODS OFFERED: {{PAYMENT_METHODS}}
SHIPPING OR DELIVERY MODEL: {{DELIVERY_MODEL}}
ACCOUNT REQUIREMENT: {{GUEST_OR_ACCOUNT}}

For each step, produce a row: Step | What the user must do | Known or likely friction | Evidence type (data / heuristic) | Fix | Effort (Low/Med/High).

Then answer specifically:
- At which step does the total price first become fully known, including delivery and tax? If that is not the first step, say what that costs us.
- Which required actions could be removed, deferred, or auto-filled?
- Where does the flow ask the user to leave the page, open an app, or check an inbox, and what is the recovery path if they do not come back?
- Which error states are likely to be unrecoverable or unclear? List the field and the better message.

Rank all fixes at the end by expected impact divided by effort, and say which single change you would ship first.

Rules: distinguish clearly between what the data shows and what you are inferring from heuristics - label every row. Do not recommend one-click payment methods without noting what integration work they require. No em dashes.

Fill in before running

Replace each placeholder with your own detail. The more specific you are, the less the model invents.

  • {{STEP_LIST}}
  • {{STEP_DROPOFF_DATA}}
  • {{PAYMENT_METHODS}}
  • {{DELIVERY_MODEL}}
  • {{GUEST_OR_ACCOUNT}}

Getting a better result

  1. Include step level drop-off figures if you have them; without them every finding is a heuristic guess.
  2. List the error messages verbatim, since bad error copy is often the largest single leak.
  3. Ask it separately to run the same audit assuming a returning customer.