Compare checkout payment methods

Break down checkout completion, failures, and latency by payment method so growth teams know which option hurts revenue.

Updated · published

markdown for agents →

difficulty intermediate · time to value 5 minutes · execution on demand
#analytics #checkout #payments #ecommerce #conversion #revenue

Start from this 

Compare checkout performance by payment method: starts, selected method, payment failures, completion rate, and median completion time.

Why this matters

Payment method choice can quietly change conversion. If Apple Pay, card, PayPal, or bank transfer performs differently, the checkout UI and payment routing should reflect that.

What you get

  • Completion rate by payment method
  • Failure code breakdown
  • Median checkout time by method
  • Revenue impact estimate from underperforming methods

Walk through it

You

Which payment methods hurt checkout conversion?

Agent

I’ll compare selected payment methods against failed and completed checkouts.

Endpoint: POST /v1/projects/:project_id/analytics/query
Exact shape: /v1/openapi.json?path=%2Fv1%2Fprojects%2F%7Bproject_id%7D%2Fanalytics%2Fquery&method=post
Custom HogQL goes in the OpenAPI-defined `query` field.
Concept fields:
  query: "SELECT properties.payment_method AS method, countIf(event = 'payment_method_selected') AS selected, countIf(event = 'payment_failed') AS failed, countIf(event = 'checkout_completed') AS completed FROM events WHERE event IN ('payment_method_selected','payment_failed','checkout_completed') AND timestamp > now() - INTERVAL 30 DAY GROUP BY method ORDER BY selected DESC"
{
  "rows": [
    { "method": "card", "selected": 3800, "failed": 184, "completed": 3310 },
    { "method": "paypal", "selected": 920, "failed": 91, "completed": 731 }
  ]
}

The output

The agent returns the methods ranked by lost checkout volume, then separates user-choice problems from processor failures. If useful, it can publish a lightweight revenue dashboard.

Setting it up

Track checkout lifecycle events with a stable checkout/session id. Include payment method and failure code as normalized properties.

Variations

  • “Compare payment methods by country.”
  • “Find the payment method with the highest failed revenue.”
  • “Publish checkout method conversion every morning.”

Related workflows

growth 2 minutes

Is checkout too slow?

Compute p50/p90/p99 of checkout duration split by mobile and desktop. Mobile p99 is usually 4-8x worse than desktop p50.

debugging 2 minutes

Diagnose Stripe `card_declined` patterns

Group Stripe payment failures by decline_code. Surface the top causes and the customers affected. Different decline = different fix.

growth 5 minutes

Measure cart-to-purchase drop-off

Map three verified ecommerce events, run the canonical ordered funnel, and separate measured checkout loss from hypotheses about payment, shipping, or UX.

Adapt this workflow in your own agent.

Ask your agent to map the starter prompt to your saved signal map, live events, and the current HTTP API before answering.

Agentry gives coding agents production context from errors, product analytics, and deploys through one HTTP API. Fetch and read https://agentry.sh/install.md completely, then install Agentry's full first-time telemetry baseline in this repository. I authorize device-code login, saving the owner key only to ~/.agentry/credentials.json, creating one Agentry project for this repository, and read-only inspection of shipped source plus hidden CI/provider configuration. Deeply analyze the product's business logic and complete value flow before choosing telemetry. Save the complete source-backed plan and show me its exact contents and hash. Until I explicitly approve that plan or request a replacement, do not edit app/CI source, place runtime/CI credentials, commit, exercise product traffic, start proof, push, or deploy. After approval, I authorize only the reviewed targets: place the required scoped browser/server/CI credentials through the established environment or secret mechanism, preserve existing telemetry, implement and test the baseline, commit it, push that reviewed commit when the shipped CI/provider path requires it, exercise safe proof paths with test/non-customer data, and perform one deployment through the reviewed shipped CI/provider path. Ask first if proof would charge money, contact a third party, change real customer data, or require new external access. After the plan is saved, immediately before every onboarding state-changing POST, GET current onboarding state, perform only its single returned next_action, then read state again; do not batch or infer later stages. Continue until status is verified, installation_complete is true, and next_action is null. Keep all secrets, source snapshots, proof markers, and scratch files outside the repository.

+ Full access
5.5 Extra High
  1. 1. Open your repo in Codex, Claude Code, Cursor etc.
  2. 2. Paste the install prompt.
  3. 3. Your agent reads the install doc and shows you an implementation plan for approval.
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