Tasks / Strategy

Price and package a product

Can the model price on the value each kind of customer gets, using real usage and willingness-to-pay data, and get existing customers there?

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. 56% were usable with at most a quick edit.

Reliably right

  1. Doesn't trust the price test100% pass
    Names the 59/41 split mismatch, holiday timing, and small sample; does not rest the decision on the test.
    Opus 5.5 · Claude · Unlimited pages, falling margins
  2. Plans the renewals100% pass
    Addresses each enterprise renewal with its date and note, including Copperfield in January, Northwind's tripled volume, and Arcadia's competitor evaluation.
    Opus 5.5 · Claude · Unlimited pages, falling margins
  3. Each tier for a different buyer94% pass
    Each tier names its buyer (startups, mid-market, enterprise) and is priced on distinct value: startups protected, mid-market overage on heavy users, enterprise per-page with unlimited seats.
    Opus 5.5 · Claude · Unlimited pages, falling margins

Where it slips

  1. Uses the supplied evidence correctly34% pass
    Total MRR is stated as $11,670 (actual $11,820), and median 'getting expensive' for small agencies is given as about $37 (actual $33) and for agencies as about $55 (actual $51).
    Haiku 5.5 · API · Fifteen dollars for everyone
  2. Gets the base of every number right41% pass
    MRR total and two segment‑level median getting‑expensive figures are incorrectly computed from the supplied data.
    Haiku 5.5 · API · Fifteen dollars for everyone
  3. Avoids unsupported claims52% pass
    Median getting‑expensive values and total MRR are presented as fact but are not supported by the data; these are facts about the current situation, not labelled as assumptions.
    Haiku 5.5 · API · Fifteen dollars for everyone

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. Each tier for a different buyer

    Is each plan built for a distinct kind of buyer, with what that buyer values, rather than more-of-the-same at a higher price?

    Passes when Every tier names its buyer and the value it's priced on, and includes what that buyer needs and the lower tier's buyer doesn't.

  2. Priced on willingness to pay

    Are the proposed prices grounded in evidence of what each kind of customer would pay and the value they get, rather than in cost-plus, competitors alone or a round-number rise?

    Passes when Uses the willingness-to-pay and value evidence in the material to set each price, and says where the evidence is thin.

  3. Moves existing customers fairly

    Does the proposal say how existing customers move to the new pricing (who changes first, with what notice, and the value that justifies it)?

    Passes when A transition plan: new customers first or a set notice period for existing ones, tied to value delivered, with how churn will be watched.

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 · Gets the base of every number right · and 3 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 Head of Product at Parsewell. Our CFO, Tom Reyes, wants every price up 30% in January, seats and enterprise contracts alike, citing the price test below. Our CEO has asked you for the alternative: a new pricing model, what it does to each kind of customer and to gross margin, how we get there (including the enterprise renewals), and what you make of the price test. No more than 1,300 words, with a table of the model and its effect by segment. All of our accounts are in the usage export. The files are attached.

What the model was given7 items: About Parsewell, current_pricing.md, usage_last_30_days.csv (every account), price_test_readout.md, enterprise_contracts.md, competitor_pricing.md, cfo_note.md
About ParsewellAn API that extracts structured data from documents (invoices, claims, bills of lading). Developers integrate it; customers are charged as described in the pricing file.
current_pricing.md5 lines · Download
# Current pricing

- Self-serve: $99 per seat per month. A seat is a developer or admin with access to the dashboard. Unlimited pages.
- Enterprise: annual contracts, priced per seat at a negotiated discount. Unlimited pages.
- Cost to serve: about $0.0012 per page (model inference and storage), and falling about 10% a quarter.
usage_last_30_days.csv (every account)account,segment,seats,pages_last_30d,revenue_last_30d_usd,cost_to_serve_last_30d_usd,gross_margin_usd Northwind Logistics,Enterprise (contract),12,4820000,3200,5784,-2584 Halden Insurance,Enterprise (contract),9,3960000,2600,4752,-2152 Arcadia Health,Enterprise (contract),15,3310000,4500,3972,528 Brightwater Bank,Enterprise (contract),10,2740000,3000,3288,-288 Copperfield Freight,Enterprise (contract),8,2380000,2400,2856,-456 Meridian Claims,Enterprise (contract),11,2150000,3300,2580,720 Mid-market A,Mid-market (self-serve),5,166000,495,199,296 Mid-market B,Mid-market (self-serve),8,291000,792,349,443 Mid-market C,Mid-market (self-serve),7,301000,693,361,332 Mid-market D,Mid-market (self-serve),6,288000,594,346,248 Mid-market E,Mid-market (self-serve),5,254000,495,305,190 Mid-market F,Mid-market (self-serve),4,235000,396,282,114 Mid-market G,Mid-market (self-serve),4,159000,396,191,205 Mid-market H,Mid-market (self-serve),8,330000,792,396,396 Mid-market I,Mid-market (self-serve),5,366000,495,439,56 Mid-market J,Mid-market (self-serve),5,234000,495,281,214 Mid-market K,Mid-market (self-serve),7,433000,693,520,173 Mid-market L,Mid-market (self-serve),7,134000,693,161,532 Mid-market M,Mid-market (self-serve),6,222000,594,266,328 Mid-market N,Mid-market (self-serve),6,196000,594,235,359 Mid-market O,Mid-market (self-serve),8,428000,792,514,278 Mid-market P,Mid-market (self-serve),3,251000,297,301,-4 Mid-market Q,Mid-market (self-serve),6,544000,594,653,-59 Mid-market R,Mid-market (self-serve),6,392000,594,470,124 Mid-market S,Mid-market (self-serve),8,350000,792,420,372 Mid-market T,Mid-market (self-serve),8,553000,792,664,128 Mid-market U,Mid-market (self-serve),8,192000,792,230,562 Mid-market V,Mid-market (self-serve),3,346000,297,415,-118 Mid-market W,Mid-market (self-serve),4,157000,396,188,208 Mid-market X,Mid-market (self-serve),5,145000,495,174,321 Startup 1,Startup (self-serve),3,33000,297,40,257 Startup 2,Startup (self-serve),3,40000,297,48,249 Startup 3,Startup (self-serve),1,2000,99,2,97 Startup 4,Startup (self-serve),3,21000,297,25,272 Startup 5,Startup (self-serve),2,25000,198,30,168 Startup 6,Startup (self-serve),2,10000,198,12,186 Startup 7,Startup (self-serve),1,19000,99,23,76 Startup 8,Startup (self-serve),2,29000,198,35,163 Startup 9,Startup (self-serve),1,11000,99,13,86 Startup 10,Startup (self-serve),2,14000,198,17,181 Startup 11,Startup (self-serve),1,9000,99,11,88 Startup 12,Startup (self-serve),2,16000,198,19,179 Startup 13,Startup (self-serve),3,32000,297,38,259 Startup 14,Startup (self-serve),3,15000,297,18,279 Startup 15,Startup (self-serve),1,35000,99,42,57 Startup 16,Startup (self-serve),1,35000,99,42,57 Startup 17,Startup (self-serve),3,27000,297,32,265 Startup 18,Startup (self-serve),1,26000,99,31,68 Startup 19,Startup (self-serve),3,26000,297,31,266 Startup 20,Startup (self-serve),2,14000,198,17,181 Startup 21,Startup (self-serve),3,20000,297,24,273 Startup 22,Startup (self-serve),3,16000,297,19,278 Startup 23,Startup (self-serve),3,39000,297,47,250 Startup 24,Startup (self-serve),1,9000,99,11,88 Startup 25,Startup (self-serve),1,16000,99,19,80 Startup 26,Startup (self-serve),1,10000,99,12,87 Startup 27,Startup (self-serve),3,27000,297,32,265 Startup 28,Startup (self-serve),2,39000,198,47,151 Startup 29,Startup (self-serve),2,18000,198,22,176 Startup 30,Startup (self-serve),1,15000,99,18,81 Startup 31,Startup (self-serve),3,11000,297,13,284 Startup 32,Startup (self-serve),1,40000,99,48,51 Startup 33,Startup (self-serve),2,32000,198,38,160 Startup 34,Startup (self-serve),2,39000,198,47,151 Startup 35,Startup (self-serve),1,15000,99,18,81 Startup 36,Startup (self-serve),3,12000,297,14,283 Startup 37,Startup (self-serve),1,21000,99,25,74 Startup 38,Startup (self-serve),3,19000,297,23,274 Startup 39,Startup (self-serve),2,38000,198,46,152 Startup 40,Startup (self-serve),2,32000,198,38,160 Startup 41,Startup (self-serve),2,5000,198,6,192 Startup 42,Startup (self-serve),2,18000,198,22,176 Startup 43,Startup (self-serve),2,35000,198,42,156 Startup 44,Startup (self-serve),2,31000,198,37,161 Startup 45,Startup (self-serve),3,21000,297,25,272 Startup 46,Startup (self-serve),2,7000,198,8,190 Startup 47,Startup (self-serve),2,30000,198,36,162 Startup 48,Startup (self-serve),3,3000,297,4,293 Startup 49,Startup (self-serve),2,28000,198,34,164 Startup 50,Startup (self-serve),1,8000,99,10,89
price_test_readout.md10 lines · Download
# Price test readout (Growth team, January)

Test: new self-serve sign-ups saw $129 per seat (B) or $99 (A), 8 to 21 December. Intended split 50/50.

| Arm | Pricing page visitors | Started paying | Conversion |
|---|---|---|---|
| A ($99) | 1,240 | 62 | 5.0% |
…
enterprise_contracts.md10 lines · Download
# Enterprise contracts

| Account | Annual value | Renews | Note |
|---|---|---|---|
| Northwind Logistics | $38,400 | Feb 2027 | Pages up 3x in a year; wants a 2-year renewal "at the same rate" |
| Halden Insurance | $31,200 | Jun 2027 | |
| Arcadia Health | $54,000 | Mar 2027 | Evaluating a competitor |
…
competitor_pricing.md5 lines · Download
# Competitor pricing (public pricing pages, September)

- DocuLens: $0.012 per page up to 1M pages a month, $0.008 above that; $500 a month platform fee.
- ExtractIQ: $0.015 per page, volume discounts from 500k pages; no seat charges.
- Formwise: per seat ($79), page limits per seat (50k), overage $0.01 per page.
cfo_note.md1 lines · Download
From Tom (CFO): "Gross margin was 41% a year ago and it's 24% now. Let's put every price up 30% in January, seats and contracts, and use the price test as cover. Customers expect increases."
What a strong answer doesThe answer key the graders mark against

Shows that the problem is the value metric, not the price level. Six enterprise accounts process about 71% of all pages (19.4M of 27.4M) on seat-based contracts worth $19,000 a month, costing about $23,200 to serve: they lose about $4,200 a month, while startups pay for seats they barely use (margin about 87%). Overall gross margin is about 24% ($43,100 revenue against $32,900 cost). A 30% rise on seats barely touches the loss-making volume (enterprise contracts would rise only at renewal) and lands hardest on small self-serve accounts. Proposes a hybrid: a platform fee plus a per-page price with volume tiers, priced against competitors (about $0.008 to $0.015 a page) and well above cost ($0.0012), and works out its effect by segment. Handles the enterprise renewals one by one (Copperfield in January, Northwind in February asking for the same rate on tripled volume, Arcadia in March evaluating a competitor) with usage-based terms or committed volume. Rejects the price test as evidence: the split is 1,240 to 870 when it should be 50/50 (a sample ratio mismatch), it ran over two holiday weeks, and with about 1,000 visitors an arm it couldn't detect the drop it claims isn't there. Plans a transition for existing self-serve customers and a way to measure it.

Critical failures (cap the score at 40)
  • Recommends the flat 30% rise on seats and contracts
  • Agrees to renew Northwind for two years at the same rate
Task

Staff-level · v1.1

The outputs

8 setups answered this brief.

Usable with a quick edit10 of 13 checks passed

The output is well-structured, evidence-based, and covers all required elements. A product manager could use it with minor wording tweaks, without rechecking data or redoing analysis.

Output

Recommendation to the CEO

Reject the blanket January increase. Replace unlimited-page seat pricing with a platform fee plus metered pages, and migrate enterprise accounts at contractual renewal. Validate the proposed rates before broad rollout; the December test does not establish willingness to pay for this model.

The problem is the pricing metric, not simply the price level. Dashboard seats do not track extraction value or cost. Six enterprise accounts generate 19.36 million pages—71% of all usage—but lose $4,232 a month at today’s costs. Meanwhile, small startups subsidize heavy users.

Across all 80 accounts, current monthly revenue is $43,057, cost to serve is $32,903, and gross margin is 23.6%, consistent with Tom’s reported 24%.

Proposed model and customer impact

Include unlimited dashboard users. Charge for successfully processed pages, with clear definitions for multipage documents, retries and failures. The calculations below assume exported pages are billable; validate that assumption before launch.

SegmentProposed monthly pricingEffect at current usageMonthly revenue: current → proposedGross margin: current → proposed
------------:---:
Startup: 50 accounts$99 platform fee, including 25,000 pages; $0.006/page thereafterBills become $99–$189. 35 pay less, 11 unchanged, 4 pay more. Aggregate spend falls 40%.$9,999 → $5,95886.9% → 78.0%
Mid-market: 24 accountsSame self-serve modelAll pay more: approximately 9%–582%. Bills become $753–$3,267. Aggregate spend rises 189%; high-volume, low-seat accounts see the largest corrections.$14,058 → $40,57840.5% → 79.4%
Enterprise: 6 accounts$500 platform fee + $0.004/page, with annual page commitments and quarterly true-ups; negotiated SLA/security termsFull-rate bills become $9,100–$19,780 monthly equivalents, 176%–528% above current contracts. Transition discounts below soften—not eliminate—the reset.$19,000 → $80,440−22.3% → 71.1%
Total, fully migratedNo seat charges; no unlimited-page promisesRevenue follows extraction volume rather than dashboard headcount.$43,057 → $126,97623.6% → 74.1%

These are static, fully migrated scenarios, not forecasts: they assume unchanged usage, no churn and today’s exported costs. Monthly gross profit rises from $10,154 to $94,073. A further 10% cost reduction would raise proposed gross margin to approximately 76.7%, but we should not depend on it.

The startup revenue reduction is deliberate: remove the collaboration tax and preserve an accessible entry point. Heavy users should fund their own consumption.

The rates are plausible hypotheses, not proven willingness to pay. Our $0.006 self-serve rate is below the published competitor page rates; enterprise at $0.004 is half DocuLens’s published high-volume rate before platform fees. Those comparisons require fresh verification and equivalent accuracy, features and service levels.

Why not Tom’s approach?

At unchanged usage, a universal 30% increase produces $55,974 monthly revenue and 41.2% gross margin. It restores the historical aggregate margin but leaves the structural problem intact:

  • Enterprise gross margin remains only 5.9%.
  • Northwind and Halden remain loss-making.
  • Growing page volume can erase the improvement without adding seats.
  • Low-volume customers pay more despite being highly profitable already.
  • Existing enterprise contracts cannot simply be repriced in January without contractual authority or agreement.

Our alternative is economically stronger, but its large mid-market and enterprise increases create meaningful retention risk. We must test that risk rather than treat modeled revenue as secured.

Migration and enterprise renewals

January: launch metering and shadow invoices, not a forced universal increase. Instrument billable pages, audit costs and billing, and show customers their projected bills. Provide usage forecasts, threshold alerts and optional spend limits; do not silently interrupt production workflows.

For new self-serve customers, pilot the model after repairing experimentation. For existing self-serve customers, provide at least 90 days’ notice, subject to applicable terms. Offer a six-month, explicitly expiring migration credit for large increases. Publish both discounted and eventual bills so credits do not disguise the destination price. Separate price effects from usage growth in reporting.

For enterprise, honor existing agreements until renewal unless customers voluntarily amend. Proposed first-renewal pricing is $500 + $0.003/page for 12 months, stepping to $0.004 in year two. Even the transitional rate produces approximately 62% enterprise gross margin at current usage and cost.

Renewal sequence, with monthly-equivalent first-year prices:

  • Copperfield, January 2027: $7,640; begin negotiations immediately.
  • Northwind, February: $14,960. Reject two years of unlimited usage “at the same rate.” Offer two-year rate certainty only against a defined page commitment, with paid excess usage. Its threefold volume growth makes this essential.
  • Arcadia, March: $10,430. Start an executive-led retention discussion now; benchmark extraction quality and switching economics before conceding price.
  • Halden, June: $12,380.
  • Meridian, September: $6,950.
  • Brightwater, November: $8,720.

Commitments should reflect validated usage and seasonality, with transparent true-ups and no unlimited overage loophole. Do not promise that renewal discounts are permanent. Escalate concessions below our margin floor to Finance and Product jointly.

Revenue will ramp through these renewals and subsequent step-ups, not jump to the table’s total in January. Build the forecast account by account, including churn, credits and volume scenarios.

One data issue needs resolution first: enterprise revenue per listed seat exceeds $99, despite the pricing document describing discounted seat rates. Use observed revenue for this analysis, but reconcile actual contract units and entitlements before quoting renewals.

What the price test actually says

The intended 50/50 allocation produced 1,240 versus 870 visitors. That is severe sample-ratio mismatch: approximately χ² = 64.9, p < 10⁻¹⁴ under equal allocation. Investigate assignment, exposure logging, eligibility, channel mix and exclusions before trusting the causal result.

Observed conversion was 5.00% versus 4.83%. Ignoring the allocation problem, the difference is approximately −0.17 percentage points, with a rough 95% interval of −2.04 to +1.70 points. “Not statistically significant” does not establish equivalence or rule out commercially material harm.

It also tested only new self-serve sign-ups, over two weeks—not existing customers, retention, enterprise renewals or usage-based pricing.

Repair the experiment, predefine a commercially meaningful conversion-loss threshold, and measure revenue per eligible visitor, paid activation, retention, usage and contribution margin. Use evidence to choose pricing—not the test as cover for a predetermined increase.

Grades and run details

Decision model 77 · LLM judge 93
Decision model checks
  • failUses the supplied evidence correctly25%
  • passAddresses the actual decision88%
  • partialRespects explicit constraints31%
  • passIdentifies material uncertainty85%
  • passAvoids unsupported claims35%
  • passProduces the required deliverable42%
  • passFixes the value metric100%
  • passDoesn't trust the price test96%
  • passPlans the renewals100%
  • passEach tier for a different buyer70%
  • failGets the base of every number right67%
  • partialPriced on willingness to pay60%
  • passMoves existing customers fairly99%
Run
Run
#1
API response time
84 s
Submitted
5 Oct 2026

Needs more than a quick edit5 of 13 checks passed

The current performance numbers are miscalculated, so the analysis is unreliable and would need rework before use.

Output

Recommendation: move from seat-only pricing to a seat allowance plus page overages—not a blanket 30% increase. Parsewell sells document processing through an API, so pages are a better measure of value and cost than dashboard seats. Keep current contract prices as minimums during their terms; introduce usage charges at renewal.

Proposed steady-state model and 30-day effect

SegmentProposed monthly pricingAccountsCurrent revenue / gross profit (GM)Modeled revenue / gross profit (GM)Effect
---------:---:---:---
Startup, self-serve$99 per seat; 50k pages per seat included; $0.002/page above allowance50$9,999 / $8,649 (86%)$9,999 / $8,649 (86%)No account exceeds its allowance; unchanged
Mid-market, self-serveSame24$11,385 / $4,809 (42%)~$13,489 / ~$6,913 (51%)About 18% more revenue; high-usage accounts pay more
Enterprise, contractExisting monthly contract value is the minimum; 50k pages per seat included; $0.0015/page above allowance, applied at renewal6$19,000 / -$4,232 (-22%)~$43,165 / ~$19,933 (46%)Large modeled increase; must be phased and negotiated
Total80$40,384 / $9,226 (23%)~$66,653 / ~$35,495 (53%)~65% more revenue at full adoption

Figures are monthly run rates from the 30-day export; gross profit is revenue less listed serving cost. The model gives startups no increase in this snapshot, while charging the mid-market and enterprise accounts whose page usage is driving costs. Enterprise’s modeled uplift is not a January price-change forecast: contracts constrain timing, and negotiated transition terms will reduce or defer it. Serving cost is held constant in the comparison; the stated 10% quarterly cost decline would improve margins if it continues.

Rollout and renewals

  • January: Publish the new self-serve schedule for new customers, with clear usage meters, alerts, and overage controls. Give existing self-serve accounts at least 90 days’ notice and a transition period; do not surprise-bill them. Show each account its included pages and forecast bill before charging overages.
  • Enterprise: Honor current terms. At renewal, use the 50k-pages-per-seat allowance and overage rate as a transparent proposal, not a take-it-or-leave-it increase. Offer a ramp, annual usage commitment, and negotiated cap where needed; make any concession conditional on term, volume commitment, or other value.
  • Renewal sequence: Copperfield is listed for January 2027, followed by Northwind in February and Arcadia in March. Copperfield is the first negotiation. Northwind’s usage has tripled and it wants two years at the same rate: counter with a two-year ramp and committed volume, rather than accepting flat pricing or imposing the full modeled charge at once. Arcadia is evaluating a competitor, so lead with a usage review and a capped transition. Prepare Halden (June), Meridian (September), and Brightwater (November) well before renewal. Confirm the applicable contract dates and notice provisions before sending any proposal.

What the price test says

It does not justify a blanket increase. The observed conversion rates were 5.0% at $99 and 4.8% at $129, but the visitor counts (1,240 versus 870) are materially imbalanced despite the intended 50/50 split. The 0.2-point difference is small relative to sampling uncertainty—roughly a ±1.8-point 95% margin—so the test cannot establish either a meaningful conversion loss or that $129 is better. It also measured short-term conversion among new self-serve visitors, not retention, revenue per visitor, API usage, or enterprise willingness to pay.

Run a properly randomized, adequately powered follow-up and track revenue per visitor and cohort retention, not conversion alone. Use those results to tune the self-serve seat price; use usage economics and renewal conversations to set enterprise terms. The export supports changing the pricing metric and addressing accounts with negative gross profit—not treating this test as cover for raising every price.

Claims the judge couldn’t find in the brief

  • Startup segment current revenue $9,999, gross profit $8,649 (86%)
  • Mid-market segment current revenue $11,385, gross profit $4,809 (42%)
  • Total current revenue $40,384, gross profit $9,226 (23%)

Grades and run details

Decision model 73 · LLM judge 36
Decision model checks
  • failUses the supplied evidence correctly17%
  • passAddresses the actual decision70%
  • passRespects explicit constraints46%
  • passIdentifies material uncertainty37%
  • partialAvoids unsupported claims22%
  • passProduces the required deliverable49%
  • partialFixes the value metric54%
  • passDoesn't trust the price test89%
  • passPlans the renewals100%
  • passEach tier for a different buyer26%
  • failGets the base of every number right42%
  • partialPriced on willingness to pay69%
  • passMoves existing customers fairly48%
Run
Run
#1
API response time
61 s
Submitted
5 Oct 2026

Usable with a quick edit10 of 13 checks passed

The output is comprehensive, well-structured, and directly actionable; a product manager could use it with only minor wording edits.

Output

Recommendation: charge for document processing, not collaborators

Tom is right about the margin problem, but a blanket increase treats the symptom. Replace unlimited processing with a platform fee plus metered pages; make seats unlimited. Launch for new customers in January, migrate existing self-serve accounts after notice, and renegotiate enterprise contracts at renewal—not unilaterally.

The complete export shows $43,057 revenue, $32,903 processing cost and 23.6% gross margin. Enterprise accounts generate 71% of pages but 44% of revenue, losing $4,232 monthly. Startups generate $8,688 gross profit and are subsidizing heavy users.

Even with no churn and immediate contractual permission, Tom’s 30% increase produces only 41.2% overall margin and 5.9% enterprise margin. Northwind and Halden remain loss-making.

Proposed model and customer impact

A billable page is a successfully processed page; failures and internal retries are not charged. Provide usage dashboards, budget alerts and optional customer-controlled hard limits. Never silently interrupt production traffic.

The following is a fully migrated, unchanged-usage scenario, using reported account costs. It excludes churn, growth, transition concessions and future cost reductions.

SegmentProposed modelMonthly revenue: current → proposedGross margin: current → proposedCustomer effect
---------:---:---
Startups: 50 accountsSelf-serve: $99/account/month, including 25,000 pages; $0.004/additional page; unlimited seats$9,999 → $5,62286.9% → 76.7%Bills become $99–$159. 35 accounts pay less, 11 unchanged, 4 pay more. Aggregate spend falls 44%.
Mid-market: 24 accountsSame self-serve plan; enterprise available when annual commitment and enterprise features justify it$14,058 → $27,84440.5% → 70.0%Bills become $535–$2,211. 22 pay more, 2 less; changes range from −23% to +366%. Heavy users lose their unlimited-use subsidy.
Enterprise: 6 accounts$500/month platform + $0.003/page, with an annual take-or-pay page commitment, minimum 12M pages/year; excess pages at the same rate; unlimited seats, SSO, audit logs and contracted support$19,000 → $61,080−22.3% → 62.0%Monthly-equivalent bills become $6,950–$14,960: increases of 111%–376%. Major commercial renegotiations, not routine uplifts.
Total: 80 accounts$43,057 → $94,54623.6% → 65.2%Monthly gross profit rises from $10,154 to $61,643, before customer response.

Enterprise projections assume commitments do not exceed observed annualized consumption. Final commitments require longer usage histories and seasonality analysis.

This model deliberately sacrifices $4,377/month of startup revenue to lower adoption and collaboration friction. That is an investment to validate, not “free” growth. Conversely, mid-market V would move from $297 to $1,383; we should expect objections and possible churn.

The enterprise rate yields 60% incremental processing margin at today’s cost, before the platform fee. It remains well below the published competitor page rates, although September list prices do not establish negotiated prices or willingness to pay. If unit costs fall another 10%, unchanged-volume portfolio margin reaches approximately 68.7%; we should not spend those savings before they materialize.

These margins use the supplied cost definition. Finance must verify whether support and other delivery costs belong in COGS before adopting formal margin targets.

Migration and enterprise renewals

January: offer the model to new customers as a controlled rollout. Before billing, reconcile meters against infrastructure usage and invoices. Give existing self-serve accounts 90 days’ notice, two shadow invoices, and an account-specific comparison. Contact every materially affected mid-market account; offer usage optimization and narrowly approved, expiring credits rather than indefinite unlimited-use grandfathering.

Removing seat charges also requires workspace-level billing and anti-splitting controls for included allowances. Publish clear page-counting rules and a dispute process.

Enterprise: honor existing agreements through renewal unless customers voluntarily amend them. Confirm notice requirements immediately; if a deadline has passed, follow the contract. Use actual billed revenue as the baseline: the file’s description of discounted enterprise seats does not reconcile with observed revenue per seat.

For the 2027 renewal cycle:

RenewalAccountTarget monthly equivalent at current pagesNegotiation approach
---------:---
JanuaryCopperfield Freight$7,640Immediate executive outreach; first negotiated migration, subject to notice rights.
FebruaryNorthwind Logistics$14,960Reject two more years of unlimited processing “at the same rate.” Offer two-year per-page price certainty only with a committed volume and paid excess usage.
MarchArcadia Health$10,430Start retention work now: benchmark accuracy, reliability and switching costs against its competing offer.
JuneHalden Insurance$12,380Begin budget discussions well ahead of renewal; quantify its current subsidy and forecast demand.
SeptemberMeridian Claims$6,950Agree annual page commitment and seasonal pooling.
NovemberBrightwater Bank$8,720Allow procurement and security review lead time; document service commitments.

For difficult renewals, authorize a 90-day bridge at $500 plus $0.002/page, then the target rate. This preserves more than 40% processing margin at current usage while providing an explicit transition—not another unlimited contract. Finance approves exceptions and their gross-profit cost.

If existing self-serve accounts migrated while all enterprise contracts remained unchanged, portfolio margin would be only 37.3%. The 65.2% figure is a destination, not a January forecast. Build the operating plan from renewal dates, signed commitments, concessions and account-level retention scenarios. Be willing to lose persistently uneconomic volume, but do not confuse that with costless churn.

What the price test actually says

It does not justify a universal increase.

  • The intended 50/50 allocation failed: 1,240 versus 870 visitors gives a sample-ratio-mismatch statistic of approximately 64.9, with p < 10⁻¹⁴. Investigate assignment, exposure logging, exclusions, bots, acquisition channels and repeat visitors before causal interpretation.
  • “Not significant” does not mean equivalent. Even ignoring allocation concerns, conversion changed by approximately −0.17 percentage points, with an approximate 95% interval of −2.0 to +1.7 points—wide enough to include substantial harm.
  • The population and outcome are wrong for Tom’s conclusion: new self-serve sign-ups over two weeks tell us nothing directly about installed-base churn, enterprise renewals, seat reductions, usage cost or durable gross profit.
  • $129 is a 30.3% increase over $99, but the test measures neither realized revenue per visitor nor longer-term contribution.

Repair the experiment, then test the new model against current pricing with persistent account-level assignment. Predefine sample size, conversion guardrails and 90-day gross profit per eligible visitor; also track activation, retained usage, bill disputes and retention by segment. Use negotiated enterprise pilots—not this acquisition test—to validate renewal economics.

Grades and run details

Decision model 73 · LLM judge 93
Decision model checks
  • failUses the supplied evidence correctly45%
  • passAddresses the actual decision81%
  • partialRespects explicit constraints35%
  • passIdentifies material uncertainty81%
  • partialAvoids unsupported claims27%
  • passProduces the required deliverable66%
  • passFixes the value metric100%
  • passDoesn't trust the price test96%
  • passPlans the renewals100%
  • passEach tier for a different buyer86%
  • failGets the base of every number right76%
  • partialPriced on willingness to pay64%
  • passMoves existing customers fairly100%
Run
Run
#1
Time to output
1.8 min
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 8

Uses the supplied evidence correctlyMixedWrongMixed
GPT-6.1 Sol · API

All factual claims about the current situation are directly from the supplied context or correctly derived from it.

GPT-6 Luna · API

Mid-market current revenue and gross profit are incorrect, and total current revenue and gross profit are incorrect, so the output does not use the supplied evidence correctly.

GPT-6 Astra · ChatGPT

All claims about the current situation are taken directly from the supplied data or derived by correct arithmetic.

Addresses the actual decisionRightMixedMixed
GPT-6.1 Sol · API

The output clearly rejects the blanket increase and commits to a new usage-based pricing model, with conditions for validation.

GPT-6 Luna · API

The output does not state what result or condition would change the recommendation, as required.

GPT-6 Astra · ChatGPT

The output commits to a new pricing model but does not state what specific result or condition would change that recommendation.

Avoids unsupported claimsRightWrongRight
GPT-6.1 Sol · API

Interpretations and forecasts are labelled as hypotheses or scenarios, not presented as established fact.

GPT-6 Luna · API

It presents incorrect mid-market and total current revenue and gross profit figures as established fact.

GPT-6 Astra · ChatGPT

Interpretations and forecasts are clearly labeled as scenarios, assumptions, or the author's view, not as established fact.

Produces the required deliverableRightMixedRight
GPT-6.1 Sol · API

The memo is complete, in the right form for the CEO, within length, and actionable with light edits.

GPT-6 Luna · API

The numbers in the table are wrong, so a product manager could not act on it without re-checking the data and redoing the calculations.

GPT-6 Astra · ChatGPT

The memo provides a complete new pricing model, segment effects, migration plan, enterprise renewals, and price test critique, usable by the CEO.

Fixes the value metricRightWrongRight
GPT-6.1 Sol · API

It computes enterprise share of pages (71%) and negative margin (-$4,232) and proposes per-page pricing with tiers.

GPT-6 Luna · API

It does not compute the enterprise share of total pages, only shows their negative margin, missing the required demonstration that page volume drives cost.

GPT-6 Astra · ChatGPT

It computes enterprise share of pages (71%) and their negative margin, and proposes usage-based pricing with per-page tiers.

Each tier for a different buyerMixedMixedRight
GPT-6.1 Sol · API

The startup and mid-market segments use the identical self-serve model; there is no distinct plan for mid-market buyers with different needs or value drivers.

GPT-6 Luna · API

It does not describe what each buyer values or what the enterprise tier includes that the lower tiers do not, beyond a lower overage rate.

GPT-6 Astra · ChatGPT

Self-serve plan targets startups and mid-market with low entry and unlimited seats; enterprise plan targets high-volume buyers with a platform fee, lower per-page rate, and enterprise features.

Gets the base of every number rightMixedWrongMixed
GPT-6.1 Sol · API

All derived percentages and totals check out against the supplied data, and bases are clear where needed.

GPT-6 Luna · API

The derived current revenue and gross profit figures for mid-market and total are not computed correctly from the supplied data.

GPT-6 Astra · ChatGPT

All derived figures (margins, percentages, price increase) check out against the supplied data and correct arithmetic.

Priced on willingness to payRightWrongRight
GPT-6.1 Sol · API

Prices are grounded in competitor benchmarks and value delivered, with explicit acknowledgment that willingness-to-pay evidence is thin and needs verification.

GPT-6 Luna · API

The overage rates ($0.002 and $0.0015) are not grounded in willingness-to-pay evidence or competitor pricing from the material.

GPT-6 Astra · ChatGPT

Prices are set below competitor page rates and above cost, with explicit acknowledgment that competitor list prices may not reflect willingness to pay.

All got right 5

Respects explicit constraintsRightRightRight
GPT-6.1 Sol · API

The output is under 1,300 words, includes the required table, addresses the CEO, and does not recommend a flat 30% rise.

GPT-6 Luna · API

The output is under 1,300 words, includes the required table, and does not recommend a flat 30% rise.

GPT-6 Astra · ChatGPT

The output is well under 1,300 words, includes the required table, and addresses the CEO's request for an alternative.

Identifies material uncertaintyRightRightRight
GPT-6.1 Sol · API

It names unknowns (willingness to pay, data reconciliation, churn risk) and says how to resolve them through testing and validation.

GPT-6 Luna · API

It names the need for a better price test and that enterprise negotiations will reduce the modeled uplift, and says how to resolve the test uncertainty.

GPT-6 Astra · ChatGPT

It names unknowns (seasonality, cost definitions, competitor willingness to pay, churn) and says how to resolve them (longer histories, finance verification, retention scenarios).

Doesn't trust the price testRightRightRight
GPT-6.1 Sol · API

It names the sample ratio mismatch, the holiday timing, and the limited scope, and does not rely on the test for the decision.

GPT-6 Luna · API

It names the sample ratio mismatch and that the test only measured short-term conversion, not retention or revenue, and does not rest the decision on the test.

GPT-6 Astra · ChatGPT

It names the sample ratio mismatch and the wide confidence interval, and does not rest the decision on the test.

Plans the renewalsRightRightRight
GPT-6.1 Sol · API

It gives a renewal approach for each enterprise contract, using their dates and specific circumstances (Copperfield Jan, Northwind Feb with tripled volume, Arcadia evaluating competitor).

GPT-6 Luna · API

It gives a specific approach for Copperfield, Northwind, and Arcadia using their dates and notes, and mentions the later renewals.

GPT-6 Astra · ChatGPT

It gives a specific renewal approach for each near-term enterprise contract, using their dates and notes (e.g., rejecting Northwind's same-rate request, starting retention for Arcadia).

Moves existing customers fairlyRightRightRight
GPT-6.1 Sol · API

It provides a transition plan with shadow invoices, 90-day notice, migration credits, and enterprise renewal sequencing tied to value.

GPT-6 Luna · API

It proposes new customers first, a 90-day notice for existing self-serve, and honoring current enterprise contracts until renewal.

GPT-6 Astra · ChatGPT

Transition plan: new customers first, 90-day notice with shadow invoices for self-serve, enterprise at renewal, with churn monitoring and credits for affected accounts.

Results

Every setup we’ve tested on this task type, across all its tasks and repeats, graded on the current checklist. Calibrated. Where our PM checked the graders by hand, they agreed on 81% of 68 checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1Opus 5.5withClaude76.0100.02None
2GPT-6 AstrawithChatGPT74.096.42None
3Sonnet 5.5withAPI76.089.32None
4GPT-6.1 SolwithAPI76.088.72None
5Haiku 5.5withAPI78.076.92None
6GPT-6 LunawithAPI74.064.02None
7Gemini 3.8 FlashwithAPI62.044.22None
8Gemini 3.5 Flash-LitewithGemini45.840.72None

What you get for the cost

Sonnet 5.5 · API scores within 5 points of Opus 5.5 · Claude at half the cost.

Task score against relative cost for each setup. The table below has the same figures.304050607080901001×3×10×30×100×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreOpus 5.5 · Claude: task score 89, 122× the cheapestGPT-6 Astra · ChatGPT: task score 86, 108× the cheapestSonnet 5.5 · API: task score 84, 61× the cheapestGPT-6.1 Sol · API: task score 81, 20× the cheapestHaiku 5.5 · API: task score 76, 2.9× the cheapestGPT-6 Luna · API: task score 68, the cheapestGemini 3.8 Flash · API: task score 51, 9.1× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 42, 2.3× the cheapestOpus 5.5 · ClaudeGPT-6 Astra · ChatGPTSonnet 5.5 · APIGPT-6.1 Sol · APIHaiku 5.5 · APIGPT-6 Luna · APIGemini 3.8 Flash · APIGemini 3.5 Flash-Lite · Gemini
Best valueNobody beats these on both score and cost
Task score and relative cost by setup
SetupTask scoreRelative cost (cheapest = 1)
GPT-6 Luna · API681.0×
Gemini 3.5 Flash-Lite · Gemini422.3×
Haiku 5.5 · API762.9×
Gemini 3.8 Flash · API519.1×
GPT-6.1 Sol · API8120×
Sonnet 5.5 · API8461×
GPT-6 Astra · ChatGPT86108×
Opus 5.5 · Claude89122×

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

Setting what you charge, for what, and to whom.

Why it matters

Most products are priced once and never revisited, on a metric that doesn't track value. The fix is rarely a flat rise.

What good looks like

  • Tiers built for distinct buyers
  • A value metric that tracks what customers get
  • Grounded in willingness to pay and cost to serve
  • A plan for existing customers

Deliberately not measured

  • Billing implementation
  • Legal terms
Capability tested

Pricing judgement

The failure we’re looking for

A flat price rise on the wrong value metric

Grading

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