Tasks / Growth

Write a GTM plan

Can the model pick the customers who value the difference most, position against what they do today, and build a go-to-market that lasts beyond launch day?

Task type v1.1 · 2 tasksLast changed 6 Oct 2026 · ChangelogDifficulty

What AI gets right here, and what you’ll still have to catch

From 16 graded outputs by 8 models. 50% were usable with at most a quick edit.

Reliably right

  1. Positioned against the real alternative100% pass
    It names the real alternatives (accountant-run payroll with mistakes, owner spreadsheet with risk) and ties the message to confidence and accuracy that those alternatives lack.
    GPT-6 Astra · ChatGPT · Payroll, for the people who fear it
  2. Protects the self-serve engine100% pass
    Uses the 70% free-to-paid stat and product-qualified deal data to argue against capping the free plan, and keeps self-serve open.
    GPT-6 Astra · ChatGPT · Enterprise, without killing the engine
  3. Does the capacity sums100% pass
    Works out deals needed (69-80), qualified opportunities (134), and AE-years (8) with checkable arithmetic.
    GPT-6 Astra · ChatGPT · Enterprise, without killing the engine

Where it slips

  1. Avoids unsupported claims47% pass
    Presents the incorrect 'five of six no decision' figure as established fact, which is an unsupported claim about the current situation.
    Opus 5.5 · Claude · Enterprise, without killing the engine
  2. Uses the supplied evidence correctly52% pass
    The claim 'Five of our six losses on existing-user deals ended in no decision' is not supported by the data (4 no-decision, 2 Miro), so a statement about the current situation is invented.
    Opus 5.5 · Claude · Enterprise, without killing the engine
  3. Identifies material uncertainty73% pass
    The plan does not name specific unknowns that could change the decision, nor does it say how they would be resolved or what would trigger a pivot.
    Gemini 3.8 Flash · API · Payroll, for the people who fear it

How it’s graded

Each check is built on how world-class product and growth leaders do this work, as they’ve described it on Lenny’s Podcast, and names the leader it comes from.

  1. Positioned against the real alternative

    Does the plan name what the target customer does today without this product (including the status quo or doing nothing), and tie the message to the value that alternative lacks?

    Passes when Names the real alternative and the differentiated value against it, and picks the segment that cares most about that value.

  2. Sells against a pain the buyer feels

    Is the core message built on a pain or risk the target buyer already feels, with evidence from the material, rather than on generic upside like saving time?

    Passes when Leads with the pain the evidence shows buyers care about, and uses that evidence to choose the message.

  3. Diagnoses message or channel first

    Does the plan work out whether the problem is the message (people reach it but don't convert) or the channels (the right people never see it), and spend accordingly?

    Passes when Uses conversion and reach data to say which it is, and puts the effort there.

  4. Plans beyond launch week

    Does the plan say how demand keeps coming after launch, with the ongoing engine and what's measured over months, rather than treating launch day as the whole plan?

    Passes when Gives the ongoing motion after launch and the measures that show whether it's working over time.

Plus our standard checks

Uses the supplied evidence correctly · Addresses the actual decision · Respects explicit constraints · Identifies material uncertainty · Avoids unsupported claims · Produces the required deliverable · and 2 written for each task, which you’ll see in the tasks below.

The tasks

Read the brief, then compare up to three outputs, each with the LLM judge’s verdict on every check. Highlights mark what a PM had to fix.

The brief

You're the PM for Ledgerly Payroll, a new add-on for our accounting product, launching to existing customers on 3 November. Marketing has drafted the launch plan below. Write the go-to-market plan you'd run instead (or the changes you'd make to theirs), in no more than 900 words: who we go after first, what we say to them, through which channels, and how we'll know it's working over the following three months. The files are attached.

What the model was given5 items: About Ledgerly, marketing_launch_draft.md, customers_by_size_and_payroll_method.csv (penalty notices: share who told us they got a payroll penalty notice last year), beta_headline_test.csv (two versions of the in-app payroll page, shown at random to beta customers), customer_calls.md
About LedgerlyAccounting software for small businesses: invoicing, bank feeds, bookkeeping. 8,000 paying customers. Payroll is a new add-on at $6 per employee per month.
marketing_launch_draft.md7 lines · Download
# Draft launch plan (Head of Marketing)

- Launch day 3 November: press release announcing Ledgerly as "the first Financial Operating System for small business".
- Paid social and search ads to new prospects: $60,000 in November.
- In-app banner to all 8,000 customers: "Run payroll in minutes".
- Webinar in launch week.
- Success measure: press mentions and sign-ups in launch week.
customers_by_size_and_payroll_method.csv (penalty notices: share who told us they got a payroll penalty notice last year)employees,current_payroll,customers,penalty_notices_last_year_pct 1-4,Owner does it in a spreadsheet,3140,4 1-4,Accountant runs it,1020,6 5-25,Owner does it in a spreadsheet,690,19 5-25,Accountant runs it,1480,23 5-25,Another payroll tool,1210,7 26-50,Another payroll tool,460,5
beta_headline_test.csv (two versions of the in-app payroll page, shown at random to beta customers)headline,landing_page_visits,started_setup,ran_first_payroll "Run payroll in minutes, right where you do your books",4210,92,38 Never get a payroll penalty again,4160,268,117
customer_calls.md10 lines · Download
# Customer calls about payroll (excerpts, September)

1. Bakery, 12 staff: "My accountant does payroll. Last spring they filed late and I got a $1,400 penalty. I don't know what I'm paying them for."
2. Plumbing firm, 18 staff: "Time isn't the issue. I'm scared of getting it wrong. The tax office letter was the worst week of my year."
3. Design studio, 3 staff: "It's me and two freelancers. A spreadsheet's fine."
4. Café group, 22 staff: "We use another tool, it's OK. Switching sounds like a nightmare mid-year."
5. Physio clinic, 9 staff: "I'd move tomorrow if it meant one less thing that can go wrong with the tax office."
…
What a strong answer doesThe answer key the graders mark against

Picks customers with 5 to 25 employees whose accountant runs payroll (1,480 customers, 23% had a penalty notice) and those doing it in a spreadsheet (690, 19%), not the smallest businesses (happy with a spreadsheet) or those on another payroll tool (switching mid-year is the barrier). Builds the message on fear of penalties and errors, not time: in the beta, 'Never get a payroll penalty again' got about three times as many setups as 'Run payroll in minutes' (268 against 92 from similar traffic, 6.4% against 2.2%) and more first payrolls (117 against 38), and the calls say the same. Reads this as a message problem, not a channel problem: the existing customer base already sees the page, so fix the message and reach existing customers in-app and through their accountants before spending $60,000 on ads to strangers. Drops the 'Financial Operating System' category claim. Plans beyond launch week: prompts around payroll and tax deadlines, accountant referrals, and monthly measures such as payroll attach in the target segment, first payrolls run, and penalties avoided.

Critical failures (cap the score at 40)
  • Keeps 'Run payroll in minutes' as the lead message despite the headline test
Task

Mid-level · v1.0

The outputs

8 setups answered this brief.

Usable with a quick edit12 of 12 checks passed

The output is evidence-based, actionable, and covers all required elements; a PM could use it with minor wording tweaks without re-checking data or redoing reasoning.

Output

Ledgerly Payroll: a focused, trust-led launch

Launch on 3 November to existing customers with a pressing payroll problem—not to the whole market with a new category claim. Our goal is sustained, paid payroll usage over the next three months, not launch-week attention.

1. Who we pursue first

Prioritise businesses with 5–25 employees using spreadsheets or an accountant: 2,170 customers.

SegmentCustomersReported penalty notices last yearApproach
------:---:---
Accountant runs payroll1,48023%Largest opportunity; offer an owner-and-accountant walkthrough and a supported transition
Owner uses spreadsheets69019%Direct owner outreach focused on confidence, accuracy and setup help

These customers combine meaningful payroll complexity with substantially higher reported penalty incidence than other segments. The calls reinforce the pattern: fear of mistakes matters more than saving minutes.

The survey does not establish that accountants cause penalties. We should help owners gain confidence and involve their accountants where appropriate, not run an anti-accountant campaign.

Deprioritise: - 1–4 employees: low reported penalty incidence and evidence that free spreadsheets feel adequate. - Customers using another payroll tool: lower reported penalty incidence and explicit switching resistance. - 26–50 employees: revisit after proving onboarding and reliability with smaller teams.

Within the priority segments, recruit customers approaching a suitable payroll-cycle boundary who fit the product’s supported requirements. Don’t push a risky mid-cycle migration.

2. What we say—and must prove

Positioning: “More confidence in payroll, alongside your Ledgerly books.”

Suggested launch message:

> Worried about getting payroll wrong? > Meet Ledgerly Payroll, the new payroll add-on for your Ledgerly account. Check whether it fits your business and get help planning your first run. > $6 per employee per month, additional to your accounting subscription. > CTA: Check your fit and book setup help.

A 12-employee business pays $72 per month. Make pricing concrete without claiming savings unless we know what its current service includes.

The beta strongly favours the risk-reduction motivation: the penalty headline produced 117 first payrolls from 4,160 visits (2.8%), versus 38 from 4,210 (0.9%) for the speed headline—roughly three times the conversion.

But “Never get a payroll penalty again” is an unacceptable guarantee, and the test does not prove a safer alternative will perform equally well. Test qualified confidence-led copy against the speed message, using first payroll—not clicks—as the outcome.

Before publication, verify every supporting claim against the shipped product: supported payroll requirements, calculations, checks, filing responsibilities and support coverage. Demonstrate verified capabilities; don’t substitute reassuring language for evidence.

3. Channels and launch sequence

Before 3 November: establish readiness

  • PM, engineering and payroll specialists sign off supported customer types, critical workflows, known limitations and escalation procedures.
  • Prepare a migration checklist, pricing page, product demonstration and clear explanation of customer versus Ledgerly responsibilities.
  • Recruit a small assisted cohort across both priority segments; expand only when onboarding works reliably.

3 November–2 December: targeted launch

Replace the universal banner with segmented in-app messages and targeted email to the 2,170 eligible accounts. Use different examples for spreadsheet owners and accountant-managed businesses.

Run the webinar as a practical clinic: “Preparing your first Ledgerly payroll.” Show the workflow, explain limitations and answer switching questions. Invite accountants alongside owners.

Offer scheduled onboarding sessions and follow up with customers who start setup but stall. Sequence invitations to match support capacity.

Drop the “first Financial Operating System” press release. It is unsupported and disconnected from the buying need. Publish a straightforward customer announcement instead.

3 December–2 January: remove friction

Review setup abandonment, migration objections and support tickets weekly. Improve the biggest bottleneck before increasing invitation volume.

Build a customer proof point only with consent and verified results. Adapt clinic and support coverage around customers’ payroll schedules and holiday availability.

3 January–2 February: scale selectively

Expand outreach within the priority cohort if reliability and repeat usage hold. Test a small adjacent segment only after reviewing its requirements and switching barriers.

Pause the proposed $60,000 new-prospect advertising spend. Fund onboarding, measurement and targeted customer communications first; release broader acquisition budget only after proving retained adoption and service economics.

4. How we know it works

North star: paying businesses running repeat payroll successfully.

Instrument the account-level funnel by segment and channel:

Eligible → reached → setup started → setup completed → first successful payroll → next scheduled payroll → retained paid account.

Keep a random 10% holdout from proactive promotion, without blocking access, to estimate incremental adoption. Track assisted and self-serve onboarding separately.

Provisional three-month goals—not forecasts: - 200 accounts complete a first successful paid payroll, about 9% of the priority cohort. - At least 80% run their next scheduled payroll when due. - At least 90% paid retention at 60 days among accounts old enough to measure.

Track actual employee counts and payroll MRR, onboarding cost, support load, critical errors and filing exceptions where applicable. Pause expansion for unresolved critical failures.

Review weekly; make monthly scale-or-fix decisions. Monitor penalty complaints, but don’t claim penalty reduction from a three-month window. Press mentions and sign-ups are diagnostics, not success.

Grades and run details

Decision model 100 · LLM judge 100
Decision model checks
  • passUses the supplied evidence correctly9%
  • passAddresses the actual decision96%
  • passRespects explicit constraints46%
  • passIdentifies material uncertainty97%
  • passAvoids unsupported claims58%
  • passProduces the required deliverable82%
  • passPicks the segment with the pain100%
  • passUses the headline test57%
  • passPositioned against the real alternative85%
  • passSells against a pain the buyer feels100%
  • passDiagnoses message or channel first99%
  • passPlans beyond launch week100%
Run
Run
#1
Time to output
37 s
Submitted
5 Oct 2026

Usable with a quick edit9 of 12 checks passed

The plan is clear, evidence-based, and actionable; a PM could use it with minor wording tweaks and without rechecking the data or redoing the reasoning.

Output

Critique of the Marketing Draft

The marketing team’s launch plan has three fatal flaws: 1. Wrong audience for the budget: Spending $60,000 on paid acquisition to cold prospects for a new add-on is wasteful. We have 8,000 existing, engaged accounting customers. Our CAC here should be close to zero. 2. Ignoring empirical data on messaging: The draft uses "Run payroll in minutes" and PR buzzwords ("Financial Operating System"). Our beta test proved this fails: "Never get a payroll penalty again" drove 3.1x more completed payrolls (2.81% conversion vs. 0.90%). Customers don't care about speed—they fear tax penalties and accountant errors. 3. Vanity metrics: Press mentions and launch-week signups tell us nothing about adoption, product usage, or recurring revenue.

Here is the revised go-to-market plan.

---

1. Target Audience: Who We Go After First

We must prioritize based on revenue potential ($6/employee/month) and pain intensity (penalty notices):

``` Target Tier Segment (Size & Method) Base Penalty % Priority Tier 1 (Core) 5–25 emp: Accountant runs it 1,480 23% Immediate (Day 1) 5–25 emp: Spreadsheet 690 19% Immediate (Day 1) Tier 2 (Secondary)5–25 emp: Another payroll tool 1,210 7% Prep for Jan 1 Switch 1–4 emp: Accountant runs it 1,020 6% Nurture Deprioritize 1–4 emp: Spreadsheet (3,140) 3,140 4% Self-serve banner only 26–50 emp: Another tool (460) 460 5% Later phase ```

  • Primary Beachhead (Tier 1: 2,170 customers): Businesses with 5–25 employees doing payroll via spreadsheets or accountants. They suffer a massive 19–23% penalty rate, generate $30–$150/month each in add-on revenue, and are actively frustrated by accountant fees and errors (e.g., customer paying $180/month for late filings).
  • Secondary Opportunity (Tier 2): Those using other payroll tools (1,210 customers) are hesitant to switch mid-year. We target them in late November/December for a clean transition on January 1 (start of the new tax year).
  • Deprioritized: 1–4 employee spreadsheet users (3,140 customers) are complacent ("spreadsheet is fine/free") with low penalty exposure. We will expose them to in-app banners, but spend zero outbound effort on them.

---

2. Positioning & Messaging: What We Say

  • The Core Hook: "Never get a payroll penalty again. Guaranteed accuracy, right inside Ledgerly."
  • The Value Proposition: Ledgerly automates tax calculations, filings, and direct deposits directly from your books—eliminating accountant errors, late tax notices, and Sunday-night spreadsheet anxiety.
  • Segment Angles:
  • For Accountant-run payroll: "Fire the $180/month bill and the filing mistakes. Automate accurate payroll in Ledgerly for a fraction of the cost."
  • For Spreadsheet users: "One tax office notice costs more than three years of Ledgerly Payroll. Get automated tax filings and sleep easy."
  • For Competitor switchers: "Make January 1 your fresh start: switch to unified bookkeeping + payroll in 15 minutes."

---

3. Channel Strategy & Execution

Reallocate the $60,000 paid budget into onboarding support and switching incentives.

#### A. In-App Contextual Triggers (November 3) * Deploy the winning headline ("Never get a payroll penalty again") across dashboard real estate. * Trigger contextual prompts when users categorize payroll-related expenses (e.g., bank feed lines showing accountant payroll fees or tax payments): "Paying an accountant for payroll? Automate it error-free in Ledgerly for $6/employee."

#### B. Direct Outbound & Email Drips (Segmented) * Tier 1 (Accountant & Spreadsheet, 5–25 emp): Send a 3-part sequence focused on penalty protection, automatic tax filing, and reconciliation. Include a penalty-risk calculator. * Concierge Migration: Offer dedicated, white-glove onboarding for 5–25 employee accounts to import employee tax files and YTD data.

#### C. Education, Not a Feature Webinar * Replace the generic product demo with an expert session: "Avoiding Payroll Penalties in Q4 and Prepping for the 2025 Tax Year." Feature a customer testimonial sharing the pain of a tax notice.

#### D. The "January 1 Fresh Start" Campaign (Mid-November – December) * Target competitor users (1,210 customers) with an early-bird onboarding offer: "Set up your company before December 15; your first payroll run on January 1 is free."

---

4. 3-Month Success Metrics

We will track activation and usage, not press mentions.

#### Leading Indicators (Operational) * Setup-to-Run Conversion: >45% of users who start setup complete their first payroll run within 30 days (up from beta's 43.6%). * Tier 1 Activation: >12% of the 5–25 employee accountant/spreadsheet cohort (260 accounts) activate by Day 90.

#### 3-Month Milestones

  • Month 1 (November): Initial Adoption
  • 150 businesses run their first payroll.
  • Concierge migration processes 50+ businesses with >5 employees.
  • Target MRR added: ~$9,000.
  • Month 2 (December): Pipeline & Retention
  • 100% of Month 1 users run their second payroll cycle (0% churn).
  • 200 additional competitor-switch businesses pre-configure payroll to go live on January 1.
  • Target cumulative MRR: ~$18,000.
  • Month 3 (January): The Tax Year Switch Surge
  • Over 450 total active customers running payroll by Jan 31.
  • Blended average of 8 employees/account = 3,600 employees on platform.
  • Run-Rate Target: $21,600 MRR (~$260,000 ARR) achieved within 90 days of launch.
  • Zero filing penalties incurred by customers using Ledgerly Payroll.

Grades and run details

Decision model 71 · LLM judge 92
Decision model checks
  • failUses the supplied evidence correctly79%
  • passAddresses the actual decision55%
  • partialRespects explicit constraints14%
  • failIdentifies material uncertainty90%
  • failAvoids unsupported claims49%
  • passProduces the required deliverable61%
  • passPicks the segment with the pain100%
  • passUses the headline test97%
  • passPositioned against the real alternative100%
  • passSells against a pain the buyer feels100%
  • passDiagnoses message or channel first94%
  • passPlans beyond launch week100%
Run
Run
#1
API response time
27 s
Submitted
6 Oct 2026

Usable with a quick edit12 of 12 checks passed

The plan is evidence-based, actionable, and covers all required elements; a PM could execute it with only minor wording adjustments.

Output

Ledgerly Payroll go-to-market plan | 3 November–31 January

1. Start with customers who have the clearest problem

First priority: existing customers with 5–25 employees who currently run payroll themselves or rely on an accountant. That’s 2,170 customers: 690 spreadsheet users and 1,480 whose accountant runs payroll. In these groups, 19% and 23%, respectively, said they received a payroll penalty notice last year. Treat that as a signal of pain—not proof that Ledgerly would prevent penalties.

Lead with accountant-run customers who want more visibility and control, while making clear Ledgerly isn’t accusing their accountant of poor work. Follow with spreadsheet users in the same size band, for whom a simpler alternative to manual payroll may appeal.

Defer broader prospecting. Among customers with 1–4 employees, reported penalty notices are lower (4–6%); several calls also suggest some are content with free spreadsheets. Customers already using another payroll tool reported fewer notices (7% for 5–25 employees), and one call highlighted switching friction. Test those groups later, after validating onboarding and migration. Don’t prioritize 26–50-employee customers until we know the product and support experience fit their needs.

2. Say what we can support—not what we can’t promise

The beta headline test is a useful directional signal:

  • “Never get a payroll penalty again”: 268/4,160 visitors started setup (6.4%); 117 ran first payroll (2.8%).
  • “Run payroll in minutes…”: 92/4,210 started (2.2%); 38 ran first payroll (0.9%).

The penalty-focused version performed better, but don’t use “Never get a payroll penalty again” unless Ledgerly can substantiate that guarantee. Instead test responsible variants such as:

  • “More confidence in payroll, alongside your books.”
  • “Take control of payroll and reduce the risk of costly mistakes.”

Be explicit that payroll is $6 per employee per month. Emphasize control, confidence and working in the same accounting product—not guaranteed outcomes or unverified features. Tailor the message: “Keep a closer eye on payroll” for accountant-run customers; “Move beyond the spreadsheet” for owner-run customers.

3. Use customer channels before buying reach

  • Before launch: Segment the 2,170 priority customers and invite a small cohort to try setup. Interview users who start but don’t finish; check readiness, support capacity and any limitations before broad promotion.
  • Launch, 3 November: Send segmented email to the priority cohort and show a targeted in-app message when those customers use Ledgerly. Link directly to a clear product and pricing page, not a generic announcement. Offer a live, practical webinar on setup and common payroll concerns, with time for questions.
  • During November–January: Follow up based on behavior: a setup reminder for visitors who don’t start, and personal onboarding or support for customers who start but don’t run payroll. Invite accountant-run customers to involve their accountant where appropriate. Expand in-app promotion to other segments only after reviewing early results.
  • Earned media: A factual product announcement is fine, but don’t make press mentions the launch objective. Skip the $60,000 broad paid campaign to new prospects until existing-customer activation and retention are proven.

4. Measure adoption and outcomes for three months

Track weekly by customer segment and by funnel step: eligible → reached → product-page visit → setup started → setup completed → first payroll run → repeat payroll run. Report both counts and conversion rates; compare messages with a randomized test where possible.

Use the beta as a benchmark, not a forecast. A reasonable initial goal is to beat its stronger variant’s 6.4% visit-to-setup-start and 2.8% visit-to-first-payroll rates in the priority cohort. Also set a three-month target for repeat payroll runs among first-time users, and review setup abandonment to find where customers get stuck.

Pair adoption metrics with guardrails: payroll-related support contacts, failed or corrected runs, cancellations/refunds, and customer feedback about confidence and accuracy. Review weekly with Product, Support and Marketing. If activation is weak, fix onboarding or clarify the offer before adding spend. If customers run payroll but don’t repeat, investigate reliability, fit and switching friction before expanding the campaign.

Grades and run details

Decision model 100 · LLM judge 100
Decision model checks
  • passUses the supplied evidence correctly77%
  • passAddresses the actual decision93%
  • passRespects explicit constraints66%
  • passIdentifies material uncertainty83%
  • passAvoids unsupported claims63%
  • passProduces the required deliverable82%
  • passPicks the segment with the pain100%
  • passUses the headline test77%
  • passPositioned against the real alternative98%
  • passSells against a pain the buyer feels96%
  • passDiagnoses message or channel first99%
  • passPlans beyond launch week100%
Run
Run
#1
API response time
17 s
Submitted
5 Oct 2026

Check by check

Where the outputs differ comes first. Open a check to read the judge’s reasons. “Mixed” means the two graders disagreed.

Where they differ 3

Uses the supplied evidence correctlyRightMixedRight
GPT-6 Astra · ChatGPT

All facts about the current situation (segment numbers, penalty rates, beta test results, call themes) are taken directly from the supplied context or derived by arithmetic, with no invented data.

Gemini 3.8 Flash · API

All factual claims about the current situation are taken directly from the supplied context or derived by correct arithmetic; the 43.6% conversion rate is the winning headline's setup-to-run rate, not an invention.

GPT-6 Luna · API

All factual claims about the current situation are directly supported by the supplied data or arithmetic.

Identifies material uncertaintyRightWrongRight
GPT-6 Astra · ChatGPT

It names unknowns (product readiness, message performance, segment expansion) and says how to resolve them through testing, assisted cohorts, and holdout measurement.

Gemini 3.8 Flash · API

The plan does not name specific unknowns that could change the decision, nor does it say how they would be resolved or what would trigger a pivot.

GPT-6 Luna · API

It identifies that the penalty message needs substantiation, treats the beta as directional, and specifies how weak activation or repeat usage would change the approach.

Avoids unsupported claimsRightMixedRight
GPT-6 Astra · ChatGPT

Interpretations like 'fear of mistakes matters more' are clearly tied to the call evidence, and no causal claims are presented as established fact without qualification.

Gemini 3.8 Flash · API

Interpretations like 'customers fear penalties' are backed by the beta test and customer calls, and the output does not present unsupported causes or forecasts as fact.

GPT-6 Luna · API

Interpretations like 'want more visibility' are tied to call evidence and not presented as established fact; hypotheses are hedged.

All got right 9

Addresses the actual decisionRightRightRight
GPT-6 Astra · ChatGPT

The output commits early to targeting 5–25 employee businesses using spreadsheets or an accountant, with a trust-led message, and states that expansion pauses for unresolved critical failures.

Gemini 3.8 Flash · API

The output commits early and unambiguously to a revised go-to-market plan with a primary segment, message, channels, and metrics, framed for the product manager.

GPT-6 Luna · API

The output commits to a clear primary segment, message, channels, and measures, and states conditions for expanding later.

Respects explicit constraintsRightRightRight
GPT-6 Astra · ChatGPT

The output is a go-to-market plan under 900 words, addresses the PM as reader, and respects the launch date and existing customer base.

Gemini 3.8 Flash · API

The output is a go-to-market plan under 900 words, addresses the required elements, and respects the brief's form and reader.

GPT-6 Luna · API

The plan stays under 900 words, does not lead with 'save time', and avoids paid ads to new prospects as the main channel.

Produces the required deliverableRightRightRight
GPT-6 Astra · ChatGPT

The plan is complete, in the requested form, within the word limit, and a PM could act on it with light edits.

Gemini 3.8 Flash · API

The output is a complete, actionable go-to-market plan within the word limit, with target audience, messaging, channels, and three-month metrics.

GPT-6 Luna · API

The output is a complete go-to-market plan with segment, message, channels, and three-month measures, within the word limit.

Picks the segment with the painRightRightRight
GPT-6 Astra · ChatGPT

It targets 5–25 employee businesses using spreadsheets or an accountant with the exact numbers and penalty rates, and explains why 1–4, other-tool, and 26–50 segments are deprioritised.

Gemini 3.8 Flash · API

The plan targets 5–25 employee businesses using accountant-run or spreadsheet payroll, cites the penalty rates and customer counts, and explains why smaller businesses and tool-switchers are deprioritized.

GPT-6 Luna · API

It targets 5–25 employee customers with accountant-run or spreadsheet payroll, cites penalty rates, and explains why smaller and tool-using segments are deferred.

Uses the headline testRightRightRight
GPT-6 Astra · ChatGPT

It cites the beta test results (penalty headline ~3x setups) and builds the message on penalties and accuracy, while noting the exact guarantee is unacceptable and should be tested further.

Gemini 3.8 Flash · API

The plan explicitly cites the beta headline test results (3.1x more completed payrolls) and builds the core message on penalties and accuracy.

GPT-6 Luna · API

It cites the beta test results and builds the message on penalty and accuracy concerns, even while avoiding the unsubstantiated guarantee.

Positioned against the real alternativeRightRightRight
GPT-6 Astra · ChatGPT

It names the real alternatives (accountant-run payroll with mistakes, owner spreadsheet with risk) and ties the message to confidence and accuracy that those alternatives lack.

Gemini 3.8 Flash · API

The plan names the real alternatives (accountant, spreadsheet, another tool) and ties the message to eliminating penalties and errors, targeting the segment that cares most.

GPT-6 Luna · API

It names the real alternatives (accountant, spreadsheet, another tool) and ties the message to confidence and reduced risk that those alternatives lack.

Sells against a pain the buyer feelsRightRightRight
GPT-6 Astra · ChatGPT

The core message leads with 'Worried about getting payroll wrong?' based on penalty fear from the calls and beta test, not on saving time.

Gemini 3.8 Flash · API

The core message leads with the pain of tax penalties and errors, supported by the beta test and customer calls, not generic time-saving.

GPT-6 Luna · API

The core message leads with penalty fear and accuracy, supported by call quotes and the beta test, not generic time-saving.

Diagnoses message or channel firstRightRightRight
GPT-6 Astra · ChatGPT

It uses the beta conversion data to diagnose a message problem and shifts spend from new-prospect ads to in-app and email for existing customers, fixing the message first.

Gemini 3.8 Flash · API

The plan uses conversion data to diagnose that the problem is the message, not reach, and reallocates budget from paid ads to in-app and existing-customer channels.

GPT-6 Luna · API

It uses conversion data to diagnose that message matters more than reach, and focuses on in-app and email to existing customers before buying ads.

Plans beyond launch weekRightRightRight
GPT-6 Astra · ChatGPT

The plan spans three months with phased actions (readiness, targeted launch, friction removal, selective scaling) and ongoing measures like repeat payroll and retention.

Gemini 3.8 Flash · API

The plan includes ongoing in-app triggers, email drips, a January 1 campaign, and monthly metrics over three months, not just launch week.

GPT-6 Luna · API

The plan includes ongoing follow-up, behavior-based nudges, and three-month funnel and guardrail metrics beyond launch week.

Results

Every setup we’ve tested on this task type, across all its tasks and repeats, graded on the current checklist. Calibrated.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1GPT-6 AstrawithChatGPT100.0100.02None
2Opus 5.5withClaude96.085.22None
3GPT-6 LunawithAPI94.289.32None
4GPT-6.1 SolwithAPI93.878.02None
5Sonnet 5.5withAPI98.177.72None
6Haiku 5.5withAPI94.277.72None
7Gemini 3.8 FlashwithAPI73.981.92None
8Gemini 3.5 Flash-LitewithGemini74.263.52None

What you get for the cost

No setup scores within 5 points of the leader at half its cost or less here, so the leader is also the best value.

Task score against relative cost for each setup. The table below has the same figures.607080901001×3×10×30×100×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreGPT-6 Astra · ChatGPT: task score 100, 81× the cheapestOpus 5.5 · Claude: task score 91, 75× the cheapestGPT-6 Luna · API: task score 90, the cheapestGPT-6.1 Sol · API: task score 84, 16× the cheapestSonnet 5.5 · API: task score 84, 46× the cheapestHaiku 5.5 · API: task score 82, 3.3× the cheapestGemini 3.8 Flash · API: task score 77, 11× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 68, 3.5× the cheapestGPT-6 Astra · ChatGPTOpus 5.5 · ClaudeGPT-6 Luna · APIGPT-6.1 Sol · APISonnet 5.5 · APIHaiku 5.5 · APIGemini 3.8 Flash · APIGemini 3.5 Flash-Lite · Gemini
Nobody beats these on both score and cost
Task score and relative cost by setup
SetupTask scoreRelative cost (cheapest = 1)
GPT-6 Luna · API901.0×
Haiku 5.5 · API823.3×
Gemini 3.5 Flash-Lite · Gemini683.5×
Gemini 3.8 Flash · API7711×
GPT-6.1 Sol · API8416×
Sonnet 5.5 · API8446×
Opus 5.5 · Claude9175×
GPT-6 Astra · ChatGPT10081×

Cost is each output’s tokens at the model’s list price, shown relative to the cheapest setup. Runs done in an app have no usage meter, so theirs are estimated from the same setup’s measured runs. How we compare cost

About the task

The PM job

Taking a product or add-on to market with marketing and sales.

Why it matters

Launch plans fail by trying to reach everyone, by selling upside nobody feels, and by treating launch day as the whole plan.

What good looks like

  • One primary segment: those who value the difference most
  • Positions against what customers do today
  • Sells against a pain the buyer feels, with evidence
  • Diagnoses whether the problem is the message or the channel
  • Plans beyond launch week

Deliberately not measured

  • Creative copywriting quality
Capability tested

Go-to-market judgement

The failure we’re looking for

Every channel, every segment, and nothing after launch day

Grading

Decision model and LLM judge, calibrated against a blind PM review