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Marketing Academy · Field Work●Growth Marketing
CoreTeardown· 45 minutes

Teardown: Five-Star's Reverse Trial Downgrade Flow

Five-Star Business Finance

Objective: Given a synthetic downgrade-flow specimen (in-app messaging plus an email sequence) for a branch loan-officer app's premium AI underwriting assistant, identify which parts follow reverse trial best practice and which recreate the lesson's four common mistakes.

You're auditing UX copy at Five-Star Business Finance, the Chennai-headquartered, NSE-listed MSME lender, ahead of rolling a 30-day reverse trial of 'Star AI Underwriter' out to its full branch network.

Read the specimen downgrade sequence end to end, flag every defect against the lesson's common-mistakes list, and don't get fooled by messaging that sounds reassuring but still commits a mistake.

Before you start

What you'll need

Free path (everything below is enough to finish)

FreeLog each identified defect with severity and lesson reference

Free, sufficient for a structured defect log

The process

Specimens to review

Identify every defect in this downgrade sequence, rate its severity, and explain why it undermines the reverse trial's loss-aversion mechanic.

Sample output
STAR AI UNDERWRITER — 30-DAY TRIAL DOWNGRADE SEQUENCE (synthetic, branch loan-officer app)

Day 28 in-app banner: 'Your Star AI Underwriter trial is ending soon. Upgrade to keep instant risk scoring.'

Day 30, 11:58 PM: trial access silently removed. No further notice sent.

Day 31 email: 'Your Star AI Underwriter trial has ended. Upgrade now to restore instant risk scoring.' (Underwriting notes and risk-score history created during the trial are deleted from the branch dashboard as part of the downgrade, per the engineering ticket linked in the email.)

Free-tier dashboard: no visual indicator distinguishes which loan files were scored with AI assistance versus manually, and no upgrade prompt appears anywhere in the free tier after day 31.

Specimen: synthetic, realistic

Final deliverable

A defect log rating each downgrade-flow issue by severity, mapped to the specific common-mistake it recreates.

See a reference example
Sample output
Utkarsh Small Finance Bank, downgrade flow defect log (excerpt)

CRITICAL: Trial-created customer notes deleted on downgrade
  Ref: managing-downstream-churn-and-retention

MODERATE: Single day-28 warning banner only, no day-30 notice
  Ref: common-mistakes-in-reverse-trial-design

Success criteria

You're done when you can:

  • Correctly identifies all 4 planted defects with matching severity
  • Does not flag any of the 3 distractors as defects