Spot the Deliverability Trap: Tearing Down a Broken Opt-In Flow
Objective: Given 3 synthetic opt-in and welcome-sequence specimens, identify which ones violate the lesson's permission and deliverability rules.
You're auditing Warby Parker's regional email vendor's opt-in setup after a spike in spam complaints.
Review 3 short specimens describing opt-in flows and flag the real defects versus the plausible-but-fine choices.
Before you start
What you'll need
Free path (everything below is enough to finish)
Free, no signup friction
Paid upgrades (optional, faster/deeper)
A real ESP shows the exact settings each specimen is describing
No access? Google Sheets alone is enough to complete the exercise
The process
Specimens to review
Is this opt-in flow safe to run at scale?
Paid Instagram ad -> single opt-in form (no confirmation email) -> straight into the main promotional list, no tag applied.
Specimen: synthetic, realistic
Flag the defect.
Marketing team buys a 20,000-address 'eyewear shoppers' list from a data broker and merges it into the main send.
Specimen: synthetic, realistic
Flag the defect.
New confirmed subscriber gets their welcome email 48 hours later, batched with the weekly newsletter send.
Specimen: synthetic, realistic
Final deliverable
A defect log across all 3 specimens with severity and lesson-referenced fixes.
See a reference example
Lenskart welcome-flow teardown (excerpt) SPECIMEN 2: purchased list merge DEFECT: critical, list purchased from broker FIX: delete the purchased addresses, rebuild via opt-in only
Success criteria
You're done when you can:
- Correctly identifies all 3 real defects
- Does not flag the distractors as defects
- Assigns lesson-referenced severity to each defect