Build a Waitlist (1,000 Signups)

Proof required

Submit your channel scorecard with actual signup numbers and conversion rates from each experiment, plus the acquisition artifacts from each channel (post screenshots, outreach templates, or content pieces used).

What gets checked

• Each channel experiment ran for the full 2 weeks at a consistent cadence — a single post doesn't constitute a channel test.
• Quality signal is measured by interview conversion rate, not just signup count — volume without engagement doesn't scale.
• Scalability assessment for each channel is specific: 'scales to ~500 more if we post 3x/week' is useful; 'has potential' is not.

Common mistakes

• Running the same outreach message across different channels and concluding the channel doesn't work — different channels require different messaging.
• Measuring only cost-per-signup in money when the real cost is founder time at this stage.
• Treating channel quality as equal — a referral signup who converts to a paying customer is 10x more valuable than a passive signup.

Resources

What a verifier looks for

• Ask what the best-performing channel was and what the worst was — if they can't rank them with numbers, attribution wasn't tracked.
• Ask what they'd double down on with a $500 budget and why — reveals whether the scorecard is being used as a decision tool.
• Check that all three channels are genuinely distinct — 'Twitter and LinkedIn' is one social media channel with two platforms.

Proof required

Submit your referral page or mechanism (screenshot with referral link visible), a summary of referral signups generated in 3 weeks, your referral coefficient calculation, and one screenshot from the referral tool's analytics showing referral activity.

What gets checked

• Referral coefficient is calculated from actual data, not estimated — show the formula: total referral signups ÷ total referred-in new members.
• Referral mechanism has a clear incentive that doesn't require the product to exist yet (position in queue, early access tier, etc.).
• Referral analytics show at least 10 referral signups in 3 weeks — if fewer, the mechanic isn't working yet and the milestone notes why.

Common mistakes

• Building a referral mechanic but not emailing existing waitlist members about it — most referral programs fail because they're never announced.
• Referral coefficient calculation excludes members who shared but got zero referrals — the denominator must include all who shared, not just the successful ones.
• Incentive is too vague ('better access') — specific incentives (position 1-100 on launch day) convert better.

Resources

What a verifier looks for

• Ask what the referral coefficient was and what they consider a 'good' number for their category — vague answers mean they didn't interpret the metric.
• Ask what email they sent to existing waitlist members when they launched the referral program — if they didn't send one, the program was never activated.
• Ask what they'd change about the incentive based on what they observed.

Proof required

Submit your email list export showing 1,000+ signups, your three-tier segmentation criteria and segment sizes, the pre-launch teaser email you sent to high-intent subscribers, and a report showing open rate, click rate, and (if applicable) how many expressed purchase intent in response.

What gets checked

• Segmentation is based on observable engagement data (open/click history, referral activity), not the founder's intuition about who's most interested.
• Pre-launch teaser asks for a signal of purchase intent — not just 'are you excited?' but 'would you pay $X if we launched tomorrow?'
• Open rate on the teaser email is reported accurately — not estimated, pulled from the email tool's analytics.

Common mistakes

• Reaching 1,000 but not segmenting before launch — sending a generic email to all 1,000 underperforms a segmented sequence by a large margin.
• High-intent segment defined by founder memory ('I remember that person seemed excited') rather than data.
• Pre-launch teaser that doesn't ask about price or purchase intent — it's a feel-good email, not a validation tool.

Resources

What a verifier looks for

• Ask what percentage of the list is high-intent and what criteria defined that segment — the criteria should be data-based, not estimated.
• Ask what the purchase intent signal from the teaser email told them about pricing or launch timing.
• Check that the 1,000+ export doesn't include team members, seed accounts, or test signups — the list should represent real external signups only.