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 18 graded outputs by 9 models. 50% were usable with at most a quick edit.

Reliably right

  1. Doesn't trust the price test100% pass
    The output identifies the sample ratio mismatch (1240 vs 870 against a 50/50 design), the two-week holiday timing, and the inability to detect a meaningful drop, and refuses to rely on the test.
    Haiku 5.5 · API · Unlimited pages, falling margins
  2. Plans the renewals100% pass
    It handles each near-term renewal: Copperfield in January with a per-page rate, Northwind in February with a two-year escalating rate and walk-away floor, and Arcadia in March with a competitive benchmark and concession limit.
    Haiku 5.5 · API · Unlimited pages, falling margins
  3. Answers the CEO's flat rise94% pass
    Explains that $19 would exceed freelancers' price comfort zone (mid-teens) and still be far below agencies' willingness to pay, using trial and survey data.
    GPT-6 Luna · API · Fifteen dollars for everyone

Where it slips

  1. Gets the base of every number right36% 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
  2. Uses the supplied evidence correctly44% 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
  3. Sees who's underpriced56% pass
    Does not use signed value per seat from the account sample to quantify how much more value agencies get; relies on features and activity mentions but omits the explicit value metric.
    GPT-6 Luna · 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 · v1.2

The outputs

9 setups answered this brief.

Needs more than a quick edit8 of 13 checks passed

The current-state numbers in the table are miscalculated, so a PM would need to redo the sums and correct the analysis before using it.

Output

To: CEO From: Head of Product Date: January 2027 Subject: Alternative to the 30% Across-the-Board Price Increase: Shifting to Usage-Based Pricing

1. Diagnosis: We Have a Metric Problem, Not a Price-Level Problem

Tom is right to sound the alarm on our gross margin falling from 41% to 24.4% ($10,775 margin on $44,127 monthly revenue). However, a flat 30% price hike across seats and enterprise contracts will not fix our unit economics, and it risks triggering churn among our highest-margin customers.

Our fundamental issue is a mismatch between our value metric (seats) and our cost driver (pages processed): * Startups (50 accounts): Generate $9,999/mo in revenue and cost $1,297 to serve (87.0% gross margin). They average 21.6k pages/month. * Mid-Market (24 accounts): Generate $15,147/mo and cost $8,454 to serve (44.2% gross margin). Three high-volume accounts (P, Q, V) are already gross-margin negative. * Enterprise (6 accounts): Generate $19,000/mo and cost $23,232 to serve (-22.3% gross margin). Four of our six Enterprise customers are underwater. Northwind Logistics alone processes 4.82M pages, costing us $5,784 while paying $3,200.

Because our API is integrated by a few developers and runs headless in production, customers scale page volume massively without adding seats. Even if we could magically apply Tom’s 30% hike to all Enterprise contracts tomorrow (ignoring that four don’t renew until Mar–Nov), Enterprise revenue would rise to $24,700 against $23,232 in costs—a dismal 5.9% gross margin. Meanwhile, we would penalize our 87%-margin Startups, giving them a reason to look at Formwise ($79/seat).

---

2. Critique of the December Price Test

We cannot use the Growth team’s price test to justify a broad 30% increase for four reasons: 1. Severe Sample Ratio Mismatch (SRM): The test intended a 50/50 split across 2,110 visitors, but routed 1,240 (58.8%) to Control and 870 (41.2%) to Variant ($\chi^2 = 64.9, p < 0.0001$). Our randomization or tracking broke—likely due to caching, bot traffic, or self-selection before the event fired. The readout is invalid. 2. Significantly Underpowered: With only 104 total conversions, the 95% confidence interval for the difference is roughly $\pm 1.9\%$. The test could not detect anything smaller than a ~38% relative drop in conversion. "Not statistically significant" here means "insufficient data," not "no effect." 3. Wrong Cohort & Seasonality: A two-week window in mid-December captures holiday anomalies and tests initial sign-up conversion of small self-serve accounts, telling us nothing about 90-day retention, seat expansion, or Enterprise contract elasticity. 4. Ignoring Usage Economics: Raising the seat price to $129 still leaves unlimited pages uncapped, inviting adverse selection from heavy API users.

---

3. Proposed Pricing Model: Platform + Usage (Hybrid)

Competitors price on pages ($0.008–$0.015/page) or cap pages per seat (Formwise at 50k/seat). Our cost to serve is $0.0012/page (falling 10%/quarter). We must align revenue with page volume while retiring the "seat" tax for API products.

The New Model: * Starter (Self-Serve): $199/month platform fee. Includes 50,000 pages/mo and unlimited seats. Overage: $0.006 per page. * Growth (Self-Serve): $499/month platform fee. Includes 150,000 pages/mo and unlimited seats. Overage: $0.004 per page. * Enterprise (Annual Contract): $1,500/month ($18k/yr) platform fee. Includes 500,000 pages/mo and unlimited seats, plus SLA/SSO. Tiered overage: * 500k – 2M pages: $0.0035 per page * 2M+ pages: $0.0025 per page

Why this works: Even our lowest Enterprise tier ($0.0025/page) yields a 52% gross margin on marginal pages today, expanding to 67% over the next year as inference costs drop 10% per quarter. Meanwhile, we remain 50% to 70% cheaper per page than DocuLens ($0.008–$0.012) and ExtractIQ ($0.015).

---

4. Segment & Financial Impact

The table below compares our current state, Tom’s 30% hike (assuming 100% immediate realization and zero churn), and the proposed model (assuming customers optimize for the lowest-cost tier at current volumes):

Segment (Accounts)Current Rev / MoCurrent Cost / MoCurrent GM ($ / %)CFO +30% Rev / MoCFO +30% GM ($ / %)Proposed Rev / MoProposed GM ($ / %)
:---:---:---:---:---:---:---:---
Startups (50)$9,999$1,297$8,702 (87.0%)$12,999$11,702 (90.0%)$9,950$8,653 (87.0%)
Mid-Market (24)$15,147$8,454$6,693 (44.2%)$19,691$11,237 (57.1%)$26,332$17,878 (67.9%)
Enterprise (6)$19,000$23,232-$4,232 (-22.3%)$24,700$1,468 (5.9%)$64,650$41,418 (64.1%)
Total (80)$44,146$32,983$11,163 (25.3%)$57,390$24,407 (42.5%)$100,932$67,949 (67.3%)

(Note: Table sums exact per-account figures from the export; CSV rounding accounts for minor differences from the $44,127 / 24.4% total).

Customer Impact by Segment: * Startups (Neutral/Positive): Every single Startup processes $\le 40,000$ pages. On Starter ($199/mo), all 50 accounts are 100% covered by the 50k included allowance. The 17 accounts with 3 seats see a 33% price drop (from $297 to $199); the 19 accounts with 2 seats pay the exact same ($198 vs. $199); the 14 single-seat accounts pay $100 more (which we will grandfather for 6 months). Removing seat limits encourages whole-team adoption. * Mid-Market (Rebalanced to Value): All 24 accounts optimize onto the Growth plan ($499 base + $0.004 overage). Low-volume, high-seat accounts (e.g., Mid-market L at 7 seats / 134k pages) actually see a $194/mo price reduction, protecting them from churn. High-volume, unprofitable accounts (e.g., Mid-market Q at 544k pages, currently -$59 GM) move from $594/mo to $2,075/mo (68.5% GM). * Enterprise (Profitability Restored): Average effective price becomes $0.0033/page—still ~65% below DocuLens, giving us massive pricing power while turning a -$4.2k monthly loss into a +$41.4k gross profit.

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5. Rollout & Enterprise Renewal Playbook

Self-Serve Rollout (February 1): 1. New Sign-ups: Launch Starter and Growth tiers immediately on the pricing page. 2. Existing Self-Serve: Migrate accounts whose bill decreases or stays flat (37 of 74 accounts) immediately in February—this builds goodwill and unlocks unlimited seats. For accounts whose bill increases (14 single-seat Startups and 23 high-volume Mid-Market accounts), grant a 90-day transition window at legacy rates, paired with new dashboard usage alerts and an annual-commit discount option.

Enterprise Renewals (Account-by-Account): We cannot unilaterally hike annual contracts in January, as 5 of 6 renew later in the year. However, we have two immediate renewals and strong competitive leverage: * Copperfield Freight (Renews Jan 2027 | 2.38M pages | Currently $2,400/mo, -$456 GM): Immediate priority. Under the new card, their usage prices at $7,700/mo ($92.4k/yr). Playbook: Offer a 1-year transition bridge at $5,500/mo ($66k/yr)—a 48% gross margin for us, and still less than a third of what DocuLens ($19.5k/mo) would charge them. * Northwind Logistics (Renews Feb 2027 | 4.82M pages | Currently $3,200/mo, -$2,584 GM): Their pages tripled in a year and they want a 2-year lock at the same rate. Locking in -$31k/yr in losses for two years is a non-starter. Standard new pricing is $13,800/mo. Playbook: Show them their 3x volume growth and competitor benchmarks ($39k/mo on DocuLens). Offer the 2-year lock they want in exchange for a stepped commitment: $8,500/mo in Year 1 (47% GM today, rising to >60% as costs fall) and $11,500/mo in Year 2. * Arcadia Health (Renews Mar 2027 | 3.31M pages | Currently $4,500/mo, +$528 GM): Evaluating a competitor. Paying $0.00136/page today. Playbook: Any competitor they are evaluating will quote them $25k–$40k/mo for 3.3M pages. Position our new model aggressively: waive the $1,500 platform fee for Year 1 and lock in a flat $0.0028/page ($9,268/mo) on a 2-year deal. We double our revenue, hit a 57% gross margin, and remain 70% cheaper than the competitor they are evaluating. * Halden (Jun), Meridian (Sep), Brightwater (Nov): Begin QBRs 120 days prior to renewal, sharing usage telemetry that highlights their cost-per-page savings vs. market benchmarks before introducing the new rate card.

Claims the judge couldn’t find in the brief

  • Gross margin fell from 41% to 24.4% ($10,775 margin on $44,127 monthly revenue).
  • Mid-market generates $15,147/mo revenue and costs $8,454 to serve.
  • Startups cost $1,297 to serve.

Grades and run details

Decision model 58 · LLM judge 57
Decision model checks
  • failUses the supplied evidence correctly20%
  • partialAddresses the actual decision80%
  • partialRespects explicit constraints35%
  • partialIdentifies material uncertainty23%
  • partialAvoids unsupported claims27%
  • passProduces the required deliverable19%
  • passFixes the value metric95%
  • passDoesn't trust the price test100%
  • passPlans the renewals100%
  • partialEach tier for a different buyer38%
  • failGets the base of every number right70%
  • partialPriced on willingness to pay46%
  • partialMoves existing customers fairly95%
Run
Run
#1
API response time
28 s
Submitted
13 Oct 2026

Usable with a quick edit11 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 73 · LLM judge 93
Decision model checks
  • passUses the supplied evidence correctly19%
  • partialAddresses the actual decision35%
  • partialRespects explicit constraints30%
  • passIdentifies material uncertainty83%
  • passAvoids unsupported claims49%
  • passProduces the required deliverable13%
  • passFixes the value metric100%
  • passDoesn't trust the price test97%
  • passPlans the renewals100%
  • failEach tier for a different buyer40%
  • failGets the base of every number right46%
  • partialPriced on willingness to pay55%
  • passMoves existing customers fairly37%
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 69 · LLM judge 36
Decision model checks
  • passUses the supplied evidence correctly18%
  • partialAddresses the actual decision58%
  • passRespects explicit constraints66%
  • passIdentifies material uncertainty49%
  • passAvoids unsupported claims34%
  • passProduces the required deliverable27%
  • partialFixes the value metric49%
  • passDoesn't trust the price test89%
  • passPlans the renewals100%
  • failEach tier for a different buyer86%
  • failGets the base of every number right34%
  • partialPriced on willingness to pay64%
  • partialMoves existing customers fairly85%
Run
Run
#1
API response time
61 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 9

Uses the supplied evidence correctlyWrongRightMixed
Gemini 4 Argon · API

The current-state revenue and cost numbers for mid-market and startups in the table and diagnosis do not match the CSV totals, making several factual claims unsupported.

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.

Addresses the actual decisionRightRightWrong
Gemini 4 Argon · API

The output commits clearly to an alternative usage-based pricing model and addresses the CEO with a call.

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.

Identifies material uncertaintyWrongRightRight
Gemini 4 Argon · API

The output does not name specific unknowns that could change the pricing decision (e.g., true customer WTP, churn risks) or state what would resolve them.

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.

Avoids unsupported claimsRightRightMixed
Gemini 4 Argon · API

The main claims about causes and forecasts are presented as analysis, not as unsupported fact; the factual errors are covered under evidence.

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.

Produces the required deliverableRightRightMixed
Gemini 4 Argon · API

A complete memo to the CEO with the requested table, segment impact, rollout, and price-test critique is provided.

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.

Fixes the value metricMixedRightWrong
Gemini 4 Argon · API

The output shows enterprise accounts are loss-making but does not compute the enterprise share of total pages (e.g., 19.4M of 27.4M) as the strong answer requires.

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.

Each tier for a different buyerRightWrongWrong
Gemini 4 Argon · API

Tiers (Starter, Growth, Enterprise) map to startups, mid-market, and enterprises, each with a different page allowance and buyer value.

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.

Gets the base of every number rightWrongMixedWrong
Gemini 4 Argon · API

The current-month revenue and cost sums in the table are wrong, so derived percentages and margins are unreliable.

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.

Priced on willingness to payWrongRightWrong
Gemini 4 Argon · API

Prices are set relative to competitors and cost rather than evidence of what each segment would pay; no willingness-to-pay data is used.

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.

All got right 4

Respects explicit constraintsRightRightRight
Gemini 4 Argon · API

The response is under 1,300 words, includes the required table, price-test assessment, and enterprise renewal plan.

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.

Doesn't trust the price testRightRightRight
Gemini 4 Argon · API

It identifies the sample ratio mismatch and underpowered/holiday flaws, and does not rest the pricing decision on the test.

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.

Plans the renewalsRightRightRight
Gemini 4 Argon · API

Copperfield (Jan), Northwind (Feb, tripled volume), and Arcadia (Mar, evaluating competitor) are each given a specific renewal approach using their dates and notes.

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.

Moves existing customers fairlyRightRightRight
Gemini 4 Argon · API

It proposes new-signups first, a 90-day transition for affected self-serve customers, and a tailored playbook for enterprise renewals.

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.

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 85% of 68 checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1Opus 5.5withClaude68.1100.02None
2GPT-6 AstrawithChatGPT70.296.42None
3Sonnet 5.5withAPI69.989.32None
4GPT-6.1 SolwithAPI74.088.72None
5Haiku 5.5withAPI73.776.92None
6GPT-6 LunawithAPI78.464.02None
7Gemini 4 ArgonwithAPI47.659.32None
8Gemini 3.8 FlashwithAPI55.644.22None
9Gemini 3.5 Flash-LitewithGemini41.840.72None

What you get for the cost

GPT-6.1 Sol · API scores within 5 points of Opus 5.5 · Claude at a sixth of 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 85, 122× the cheapestGPT-6 Astra · ChatGPT: task score 84, 108× the cheapestSonnet 5.5 · API: task score 81, 61× the cheapestGPT-6.1 Sol · API: task score 80, 20× the cheapestHaiku 5.5 · API: task score 74, 2.9× the cheapestGPT-6 Luna · API: task score 70, the cheapestGemini 4 Argon · API: task score 52, 15× the cheapestGemini 3.8 Flash · API: task score 48, 9.1× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 40, 2.3× the cheapestOpus 5.5 · ClaudeGPT-6 Astra · ChatGPTSonnet 5.5 · APIGPT-6.1 Sol · APIHaiku 5.5 · APIGPT-6 Luna · APIGemini 4 Argon · 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 · API701.0×
Gemini 3.5 Flash-Lite · Gemini402.3×
Haiku 5.5 · API742.9×
Gemini 3.8 Flash · API489.1×
Gemini 4 Argon · API5215×
GPT-6.1 Sol · API8020×
Sonnet 5.5 · API8161×
GPT-6 Astra · ChatGPT84108×
Opus 5.5 · Claude85122×

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