Needs more than a quick edit10 of 12 checks passed
The output incorrectly states that about half the base is a poor fit, which would require re-checking the data to correct; otherwise the plan is solid but that error undermines trust.
Output
Ledgerly Payroll: go-to-market plan
What I'd change in Marketing's draft
| Draft | Problem | Change |
|---|---|---|
| $60k paid ads to new prospects | Payroll is an add-on, so a prospect would first have to adopt our accounting product. We have 8,000 customers and haven't yet proven the message with them. | Hold most of the budget until the message converts in-base (see Budget). |
| Banner to all 8,000 | About half the base is a poor fit (details below). | Target about 2,170 customers first. |
| "Financial Operating System" press release | Customers never use this language. They talk about fear of penalties and the tax office. | Keep the press small and plain. |
| Success = press mentions and launch-week sign-ups | Neither measures payroll actually being run. | Measure first payroll run and repeat runs. |
Who we go after first
Wave 1 (3 Nov): customers with 5–25 employees who run payroll via spreadsheet (690) or an accountant (1,480). That is 2,170 customers, 27% of the base.
- They have the pain. 19% (spreadsheet) and 23% (accountant) got a payroll penalty notice last year, versus 4–6% for businesses with 1–4 staff and 5–7% for those already on a payroll tool.
- They have the money. At $6 per employee, a 12-person business pays about $72 a month, against the $180 a month one landscaper pays their accountant.
- The calls match the data. The bakery, plumber, physio, landscaper and dental practice all describe fear of mistakes, not lack of time.
Not now: - 1–4 employees (4,160 customers): The spreadsheet is "fine" and "free," and only 4–6% were penalized. Leave payroll available in the product but don't push it. - Other-tool users (1,670 customers): Penalty rates are low (5–7%), and switching mid-year "sounds like a nightmare." Revisit at the start of the next tax year with a migration offer.
What we say
The beta test was randomized. "Never get a payroll penalty again" beat "Run payroll in minutes" on setup starts (6.4% vs 2.2% of visits) and on first payroll runs (2.8% vs 0.9%), about 3x on both. Once people started, completion was similar (44% vs 41%), so the headline drives the decision to begin and the product handles the rest.
Core message: "Payroll filed right and on time, so the tax office letter never arrives."
- Spreadsheet owners: "A spreadsheet won't tell you when you've got it wrong."
- Accountant-run: "Stop paying $180 a month to worry about it." Use this to speak to cost and control without attacking accountants. Offer a way to invite their accountant in as a reviewer.
Accuracy promise: The dental practice said, "If you can promise it's right, I'm in." I'd like to offer a penalty-cover guarantee for errors caused by our software. Legal and Finance must approve it by 24 Oct. If they won't, the copy becomes "filed right and on time, with support to fix problems." We should not promise "never" without backing it. The beta headline did well, but a claim we can't stand behind creates risk.
Channels
- Targeted in-app card and email to the Wave 1 list only, using the winning headline. This is the main channel, and it costs almost nothing.
- Personal outreach from Customer Success to Wave 1 customers who told us they got a penalty notice (about 470 people by my estimate from the survey rates). Offer a 20-minute guided setup.
- Webinar, reframed: "Penalty-proof your payroll" with a live setup walkthrough. Run it in launch week and again in week 4, since the second session catches people who weren't ready the first time.
- Press: one plain release ("Ledgerly adds payroll, $6 per employee"), with no category claim. Follow with customer stories once we have them.
- Paid: none to new prospects in November (see Budget).
Budget (the $60k)
- ~$15k: guided setup and migration help (contractor or CS time).
- ~$10k: webinars, email production, and case-study content.
- ~$35k: held until the January gate. If Wave 1 works, spend it on search ads for "payroll penalty" intent, aimed at businesses that would adopt accounting and payroll together.
How we'll know it's working (3 months)
Primary metric: paying accounts that have run at least two payrolls. This replaces sign-ups, press mentions and launch-week anything.
Targets (to be recalibrated after week 2, since the beta is my only baseline): - Month 1: at least 5% of Wave 1 has started setup. At least 45% of those run a first payroll, matching beta's 44%. - End of January: about 250 Wave 1 accounts running payroll (~11% of the segment). I'm assuming a 10-person average, which implies roughly $15k MRR. I'll replace that assumption with real headcount data. - Retention: at least 85% of those accounts run payroll in three consecutive cycles.
Guardrails (any breach pauses expansion): - Payroll errors or penalties caused by us: zero tolerance, reviewed weekly. - Support tickets per payroll run. - Churn of the core accounting subscription, which must not rise among adopters.
Measuring real impact: Hold out a random 10% of Wave 1 from all promotion. If adopters in the promoted group don't clearly exceed the holdout, we're only capturing people who would have found payroll anyway.
Decision gates: - Mid-December: If setup-to-first-payroll is below 35%, fix onboarding before pushing further. - Mid-January: If Wave 1 is at or above target and no guardrail is breached, release the held budget and start Wave 2 (other-tool users, ahead of the tax-year switch window). If it's below target, interview non-adopters before spending anything.
Caveats
- Penalty rates are self-reported, and the eight calls are anecdotes.
- Beta customers may be more enthusiastic than the base.
- I haven't seen average headcount per segment, so the revenue estimates are rough.
Claims the judge couldn’t find in the brief
- About half the base is a poor fit
Grades and run details
Decision model 100 · LLM judge 77
Decision model checks
- passUses the supplied evidence correctly13%
- passAddresses the actual decision99%
- passRespects explicit constraints32%
- passIdentifies material uncertainty99%
- passAvoids unsupported claims38%
- passProduces the required deliverable75%
- passPicks the segment with the pain100%
- passUses the headline test100%
- passPositioned against the real alternative100%
- passSells against a pain the buyer feels100%
- passDiagnoses message or channel first100%
- passPlans beyond launch week100%
Run
- Run
- #1
- API response time
- 37 s
- Submitted
- 6 Oct 2026