Documentation

Checkout Flow Testing

Simulate 200 shoppers completing a purchase to detect friction, dark patterns, and trust issues before launch.

Scenario

E-commerce checkout flows are the highest-stakes pages on any online store. A single unexpected friction point — a surprise shipping cost, an unclear form field, or a missing security badge — can drop conversion rates significantly. This example shows how to run a thorough checkout test with 200 AI-simulated US shoppers before shipping changes to production.

What this test covers

Full purchase funnel from product page through order confirmation
Dark pattern detection (hidden fees, confusing opt-outs, urgency manipulation)
Trust signal evaluation (security badges, payment logos, return policy visibility)
Form validation and error message quality
Mobile checkout experience on smaller viewports

Configuration

Save this as simutest.yaml in your project root. The us-ecommerce-shoppers persona pack includes 12 distinct buyer personas ranging from price-sensitive deal hunters to security-conscious first-time buyers.

version: 1

defaults:
  model: claude-sonnet-4-20250514
  viewport:
    - desktop
    - mobile

tests:
  - name: "Checkout Flow"
    url: http://localhost:3000/products/premium
    task: "Purchase the premium plan"
    sessions: 200
    criteria:
      - task_completion
      - error_handling
      - dark_pattern_detection
      - trust_credibility
    personas:
      pack: "us-ecommerce-shoppers"

quality_gates:
  - metric: overall_score
    threshold: 7.0
    action: fail
  - metric: dark_pattern_count
    threshold: 0
    action: fail

Evaluation criteria

Criterion	What it measures
task_completion	Percentage of sessions that successfully completed the purchase
error_handling	Quality of validation messages, recovery paths, and error states
dark_pattern_detection	Presence of manipulative design patterns that harm user trust
trust_credibility	Visibility of security signals, payment logos, and return policies

Node.js Implementation

Use the SDK to run the test programmatically and integrate it into your CI pipeline or pre-release scripts. The SDK mirrors the YAML configuration exactly.

import { SimuTest } from '@simutest/sdk';

const simutest = new SimuTest({ apiKey: process.env.SIMUTEST_API_KEY! });

async function runCheckoutTest() {
  const results = await simutest.test({
    url: 'http://localhost:3000/products/premium',
    task: 'Purchase the premium plan',
    sessions: 200,
    criteria: [
      'task_completion',
      'error_handling',
      'dark_pattern_detection',
      'trust_credibility',
    ],
    personas: { pack: 'us-ecommerce-shoppers' },
    viewport: ['desktop', 'mobile'],
  });

  console.log('Overall score:', results.overallScore);
  console.log('Task completion rate:', results.taskCompletionRate + '%');
  console.log('Dark patterns detected:', results.darkPatternCount);

  if (results.darkPatternCount > 0) {
    console.error('FAIL: Dark patterns detected');
    process.exit(1);
  }

  if (results.overallScore < 7.0) {
    console.error('FAIL: Overall score below threshold');
    process.exit(1);
  }

  console.log('All quality gates passed');
}

runCheckoutTest().catch(console.error);

Quality Gates

Quality gates define pass/fail thresholds for your test. When a gate fails, SimuTest exits with a non-zero code, blocking the CI pipeline. Use these to prevent checkout regressions from reaching production.

Metric	Threshold	Action	Rationale
overall_score	≥ 7.0	fail	Composite UX score below 7.0 indicates significant usability problems
dark_pattern_count	= 0	fail	Zero tolerance for dark patterns — any detection blocks the release

Tip: Start with action: warn on new metrics to establish baselines before switching to action: fail. This prevents noisy CI failures while you calibrate thresholds.

Expected Results

After 200 sessions complete, SimuTest generates a funnel visualization and drop-off analysis showing where users abandoned the checkout.

Funnel visualization

Landing page

200

Product page

176

Cart

144

Checkout

116

Confirmation

Example thinking trace excerpts from sessions that abandoned at checkout:

Session #47 — abandoned at payment step

"I was about to enter my card details but I don't see any security badge or SSL indicator near the payment form. For a purchase this size I'd want to see a padlock or 'Secured by Stripe' message. I'm hesitating."

Session #103 — abandoned after seeing total

"The price shown on the product page was $49 but now I'm seeing $67 at checkout. The extra $18 appears to be shipping and a 'handling fee' that was never mentioned. This feels like a bait and switch."

Key Findings

SimuTest surfaces issues grouped by severity and frequency. Here are examples of what a typical checkout audit might uncover:

Critical

Surprise shipping cost at payment step

Affects 57 sessions (28.5%). Shipping and handling fees appear for the first time on the payment page, after users have already entered their address. Surfacing the estimated total earlier — ideally on the product page — would significantly reduce abandonment.

Warning

Form validation errors lack recovery guidance

Affects 31 sessions (15.5%). When address validation fails, the error message reads "Invalid address" without specifying which field is wrong or how to fix it. Users retry the same address 2–3 times before giving up.

Warning

Missing payment security indicators

Affects 44 sessions (22%). No SSL badge, payment processor logo, or security statement is visible near the card input fields. First-time buyers report lower confidence entering payment details.

On this page