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.

Needs more than a quick edit6 of 13 checks passed

The output contains a factual error (test duration) and omits key elements like uncertainty, churn monitoring, and WTP evidence gaps, requiring rework before use.

Output

MEMORANDUM

TO: Chief Executive Officer FROM: Head of Product DATE: January 5, 2027 SUBJECT: Comprehensive Pricing Strategy: Transitioning from Seat-Based to Hybrid Usage-Based Model

---

1. Executive Summary: The Root Cause of Our Margin Compression

Tom is right that our gross margin collapse—from 41% a year ago to 23.6% today—is unsustainable. However, his proposed solution—a flat 30% across-the-board hike on seats and enterprise contracts—is the wrong remedy for a structural disease.

Parsewell is an API document infrastructure business selling variable compute (model inference and storage at $0.0012/page) under a flat, unmetered developer-seat model. This misaligns cost with value: * Enterprise is underwater: 4 of our 6 enterprise accounts generate negative gross margins. Northwind Logistics costs us $5,784/month to serve while paying only $3,200/month (-$2,584 GM). * Enterprise drives 70.6% of page volume (19.36M pages) and 70.6% of COGS, but yields -22.3% gross margin. * Startups are overpaying relative to cost: Startups generate an 87.3% gross margin. Tom’s 30% seat hike taxes the low-volume developer funnel that feeds our pipeline while leaving our heaviest enterprise consumers deeply unprofitable (even at +30%, Northwind would still lose $1,624 every month). * Enterprise contracts cannot simply be hiked in January: Enterprise customers are on annual agreements that renew throughout 2027.

We must shift immediately to a Hybrid Base + Metered Usage Model. This protects developer adoption, eliminates negative-margin accounts, positions us at a 50–70% discount to competitors, and restores company-wide gross margins from 23.6% to 60.3% ($10.2k to $50.0k monthly gross profit).

---

2. Critique of the Growth Team’s Price Test

The recommendation to raise self-serve seats from $99 to $129 based on the December test is flawed and should not be used as executive cover:

  1. Fatal Sample Ratio Mismatch (SRM): The test intended a 50/50 traffic split, but logged 1,240 visitors in Arm A ($99) and only 870 in Arm B ($129)—a 58.8% to 41.2% skew. A chi-square goodness-of-fit test yields $\chi^2 = 64.9$ ($p < 10^{-14}$). This severe deviation indicates a critical bug in traffic routing, ad tracking, or bot filtering. The data is compromised and scientifically invalid.
  2. Cohort & Volume Blindness: The test ran for just 13 days during the mid-December holiday slowdown and evaluated only top-of-funnel self-serve sign-ups. It provides zero data on willingness to pay for mid-market teams or enterprise renewals, which represent 76% of our revenue and 96% of compute costs.
  3. Optimizing the Wrong Value Metric: The test treated Parsewell as a collaboration tool (charging for humans viewing dashboards) rather than an API processing workloads. A developer seat price hike penalizes low-volume accounts while letting high-volume API users exploit unlimited processing for $99.

---

3. The Proposed Pricing Model

Document extraction value scales with document volume, not dashboard seats. Competitors recognize this: DocuLens charges $0.008–$0.012/page plus platform fees, and ExtractIQ charges $0.015/page. We can price at a substantial discount to both while capturing healthy margins.

``` ┌──────────────────────────────────────────────────────────────────────────────┐ │ PROPOSED PRICING MODEL │ ├───────────────────┬──────────────────────────────────────────────────────────┤ │ Plan │ Structure & Inclusions │ ├───────────────────┼──────────────────────────────────────────────────────────┤ │ Self-Serve │ • $99 / seat / month │ │ (Startup & │ • Includes 25,000 pages per seat / month │ │ Mid-Market) │ • Overage: $0.0040 / page ($4.00 per 1,000 pages) │ ├───────────────────┼──────────────────────────────────────────────────────────┤ │ Enterprise │ • $1,000 / month ($12,000 / yr) Platform Fee │ │ (Custom Contract) │ (includes 10 seats, custom models, 99.9% SLA, SOC 2) │ │ │ • Committed Volume: $0.0020 / page ($2.00 / 1,000 pages) │ │ │ • Uncommitted Overage: $0.0035 / page │ └───────────────────┴──────────────────────────────────────────────────────────┘ ```

#### Why this structure works: * Startups (<50k pages/mo): 46 of our 50 startups fit entirely within their 25,000 pages/seat allowance. Their pricing remains unchanged at $99–$297/month, maintaining top-of-funnel conversion. * Mid-Market (100k–550k pages/mo): Accounts with heavy API integration contribute overage revenue reflecting their compute load. Mid-market Q (544k pages, 6 seats) will pay $2,170/month instead of $594/month. Under DocuLens, Q would pay $7,028/month. We remain 69% cheaper than the market while turning a -$59 margin into +$1,517. * Enterprise (>2M pages/mo): Shifting to $0.0020/page gives enterprise clients predictable, volume-discounted rates that are 75% lower than DocuLens ($0.0080), while guaranteeing Parsewell a 40%+ gross margin against our $0.0012 cost to serve (widening as inference costs drop 10% QoQ).

---

4. Segment-by-Segment Financial & Gross Margin Impact

The table below contrasts the 30-day baseline against Tom’s 30% flat increase and the proposed model:

SegmentMetricCurrent BaselineTom's +30% Hike (Hypothetical)*Proposed Model (Fully Transitioned)
:---:---:---:---:---
Startup<br>(50 accounts, 101 seats, 1.06M pages)Revenue<br>Cost to Serve<br>Gross Margin ($)<br>Gross Margin (%)$9,999<br>$1,273<br>$8,726<br>87.3%$12,999<br>$1,273<br>$11,726<br>90.2%$10,143<br>$1,273<br>$8,870<br>87.4%
Mid-Market<br>(24 accounts, 142 seats, 6.99M pages)Revenue<br>Cost to Serve<br>Gross Margin ($)<br>Gross Margin (%)$14,058<br>$8,380<br>$5,678<br>40.4%$18,275<br>$8,380<br>$9,895<br>54.1%$28,002<br>$8,380<br>$19,622<br>70.1%
Enterprise<br>(6 accounts, 65 seats, 19.36M pages)Revenue<br>Cost to Serve<br>Gross Margin ($)<br>Gross Margin (%)$19,000<br>$23,232<br>-$4,232<br>-22.3%$24,700<br>$23,232<br>$1,468<br>5.9%$44,720<br>$23,232<br>$21,488<br>48.0%
Total Company<br>(80 accounts, 27.41M pages)Total Revenue<br>Total COGS<br>Gross Margin ($)<br>Gross Margin (%)$43,057<br>$32,885<br>$10,172<br>23.6%$55,974<br>$32,885<br>$23,089<br>41.2%$82,865<br>$32,885<br>$49,980<br>60.3%

\Note: Tom’s enterprise numbers assume annual contracts could be unilaterally raised mid-term without churn, which is legally impossible.*

---

5. Implementation Roadmap & Enterprise Renewal Strategy

#### Phase 1: Self-Serve Rollout (January–February 2027) * Grandfathering Window: Announce the hybrid model on January 15, taking effect March 1. Give existing self-serve accounts a 45-day grace period. * In-App Usage Analytics: Ship a real-time usage dashboard by February 1 showing page counts, projected monthly spend, and threshold alerts. Transparency prevents billing shock. * Top-of-Funnel Conversion: Keep new customer acquisition frictionless at $99/seat with 25k pages included.

#### Phase 2: Enterprise Renewal Playbook Enterprise accounts renew on contract dates throughout 2027. We must address each strategically:

1. Copperfield Freight (Renews Jan 2027 — Immediate Action): * Status: 2.38M pages, currently paying $2,400/mo ($28.8k/yr) against $2,856 cost. * Play: Propose a renewed contract at $5,760/mo ($69.1k ARR) ($1k base + 2.38M pages @ $0.0020). Highlight that Formwise would charge over $23k/mo for this volume. 2. Northwind Logistics (Renews Feb 2027 — High Risk/Priority): * Status: 4.82M pages (up 3x in 12 months); paying $3,200/mo ($38.4k/yr) against $5,784 cost. Requested a 2-year lock-in at the current rate. * Play: Flatly decline the 2-year rate freeze. Present their 3x volume growth and offer an enterprise tier at $10,640/mo ($127.7k ARR) ($1k base + 4.82M pages @ $0.0020). Demonstrate that DocuLens would charge them $43,060/mo ($516k ARR). Our proposal saves them $388k annually versus competitors. 3. Arcadia Health (Renews Mar 2027 — Retention Risk): * Status: 3.31M pages, paying $4,500/mo ($54k ARR); currently evaluating competitors. * Play: Competitive intelligence shows Arcadia cannot leave for a lower price: ExtractIQ would charge them $49,650/mo and DocuLens $30,980/mo. Offer Arcadia a multi-year deal with a grandfathered volume tier at $7,620/mo ($91.4k ARR) ($1k base + 3.31M pages @ $0.0020). They get price predictability; we move gross margin from 11.7% to 47.9%. 4. Halden Insurance (Jun), Meridian Claims (Sep), Brightwater Bank (Nov): * Play: Conduct mid-term Quarterly Business Reviews (QBRs) 90 days before renewal. Share data on their volume growth, introduce the new enterprise volume-tier framework, and negotiate smooth transitions without surprising client procurement teams.

Summary Recommendation

Tom's flat 30% increase damages our acquisition funnel, fails to make heavy users profitable, and risks enterprise litigation or churn. By shifting to a consumption-aligned hybrid model, Parsewell protects its developer brand, doubles monthly revenue to $82.9k, and achieves a sustainable 60.3% gross margin that expands as underlying inference costs drop.

Claims the judge couldn’t find in the brief

  • The test ran for 13 days during the mid-December holiday slowdown.

Grades and run details

Decision model 62 · LLM judge 50
Decision model checks
  • failUses the supplied evidence correctly25%
  • passAddresses the actual decision47%
  • partialRespects explicit constraints39%
  • failIdentifies material uncertainty32%
  • failAvoids unsupported claims42%
  • passProduces the required deliverable64%
  • passFixes the value metric100%
  • passDoesn't trust the price test100%
  • passPlans the renewals100%
  • passEach tier for a different buyer90%
  • failGets the base of every number right52%
  • partialPriced on willingness to pay30%
  • passMoves existing customers fairly79%
Run
Run
#1
API response time
1.6 min
Submitted
6 Oct 2026

Usable with a quick edit8 of 13 checks passed

The output is comprehensive and actionable; minor omissions like churn monitoring and a decision condition can be added with a quick edit without redoing the reasoning.

Output

To: CEO From: Head of Product Re: Alternative to the across-the-board 30% increase

Summary

Margin fell from 41% to 24% because pages are free inside the seat price and our cost is per page. Six enterprise accounts use 71% of all pages and pay 44% of revenue. Their combined gross margin is −22% (−$4.2k on $19.0k last month), and four of the six lose money. Startups run at 87% margin and mid-market at 41%.

A flat 30% doesn't fix this, for three reasons: - Contracts can't be repriced in January. All six renew in 2027, and I haven't seen any reopener clauses. - Enterprise stays near zero margin. Even at +30%, enterprise would reach only about 6% margin, and it would erode again as pages grow. Northwind's pages tripled in a year. - The price test doesn't support it (below).

I recommend pricing on pages, which is what drives our cost.

Proposed model and effect by segment

Figures are monthly, at last-30-day volumes and today's $0.0012 cost per page, with no churn.

SegmentNew pricingRevenue now → newWho pays whatGross margin now → new
Startup (50)$99/seat, now including 50k pages/seat (pooled). Overage $0.005/page.$10.0k → $10.0kNo change for any account; the heaviest uses 40k on one seat87% → 87%
Mid-market (24)$99/seat including 50k pages/seat (pooled). Overage $0.005/page.$14.1k → $19.3k (+37%)14 accounts unchanged. 10 pay $20 to $980 more; the three loss-makers (P, Q, V) rise 2–4x41% → 57%
Enterprise (6)Annual commit at $0.002/page, no seat charges, overage at the same rate, multi-year price lock for committed volume$19.0k → $38.7k (+104%)+30% (Meridian) to +205% (Halden); Northwind +201%−22% → 40%
Total$43.1k → $68.0k24% → 52%

Why these rates

  • Overage at $0.005: about 76% margin on the extra pages. It is below the cheapest competitor's per-page rate ($0.008).
  • Enterprise at $0.002: 40% margin today. If cost keeps falling 10% a quarter, it reaches about $0.0008 after four quarters, which puts this rate near 60% margin. That gives room to concede on rate later without losing money.
  • Competitor comparison: at Northwind's 4.8M pages, DocuLens list price is about $43k a month. We would charge $9.6k. Arcadia is evaluating a competitor, but at its 3.3M pages DocuLens lists near $31k against our $6.6k.
  • Enterprise seats: I'm dropping seat charges. Seats don't drive cost and mostly add negotiating friction.

Gross margin comparison

ScenarioRevenueGross margin
Today$43.1k23.6%
CFO plan, what January can actually do (self-serve +30%, contracts locked)$50.3k34.5%, and falling as enterprise pages grow
CFO plan, theoretical (every contract also +30%)$56.0k41.2%
Proposed model, at full run-rate$68.0k51.6%

The CFO plan assumes zero churn. Even on that assumption, its best case only gets back to last year's 41%.

Getting there

Self-serve (mid-market and startup): - Meter and display pooled page usage in the dashboard now. - Send mid-market a 60-day notice with a personal usage preview. Launch the new plan around April 1. - Charge overage at half rate for the first quarter, which softens the three biggest increases. - Startups see only a new allowance line, with no change in price.

Enterprise: Start before the renewal dates, and have legal check the contracts first. - Northwind (Feb 2027): Decline "the same rate". At 3x page growth again, its cost would be about $17k a month against $3.2k of revenue. Offer a two-year deal instead, with a price lock, a committed volume and a modest discount above 6M pages. That gives them the certainty they want. - Halden (Jun 2027): Same structure as Northwind, with an early-renewal offer. - Arcadia (Mar 2027): It has the smallest increase of the six accounts (+47%) and a competitor in play. Lead with value, and keep the rate flat to the competitor's list. - Copperfield (Jan 2027): First to renew, so the first live test of the model. Start talks in Q2 2026. - Meridian and Brightwater: Standard offer at renewal.

Northwind and Halden together lose about $4.7k a month, so losing them would improve gross margin dollars. We can hold the line. For the two losers the loss continues until renewal unless they take an early-renewal offer, so I'd offer a glide path (a year-one rate between $0.0015 and $0.002) in exchange for committing early. That keeps even the worst case above cost.

The price test

I wouldn't use it as cover, because it doesn't show what the readout says.

  1. The split is broken. A 50/50 split of 2,110 visitors should give about 1,055 per arm. We got 1,240 and 870, which is a 59/41 split. That is far too lopsided to be chance (p well below 0.001). Something in assignment or tracking failed, so the arms aren't comparable.
  2. "Not significant" is not "no effect". The difference is −0.17 points, with a 95% interval of about −2.0 to +1.7 points. $129 pays off only if conversion stays above about 3.8% (a drop of less than 23%), and the data can't rule out falling below that.
  3. It's the wrong test. It ran two weeks in December. It covers new sign-ups only and measures starting to pay, not retention or usage. It says nothing about existing customers, enterprise, or per-page pricing. Under my plan startups don't change price at all.

To test $129 properly, we'd need working randomisation and revenue per visitor plus 90-day retention as the measures. Detecting a one-point conversion change needs about 7,500 visitors per arm. I'd run that only if we want a startup price rise later.

Risks and assumptions

  • Figures assume static volumes, no churn, and today's unit cost. Enterprise page growth raises both revenue and cost under the new model, and the per-page rate protects margin.
  • Mid-market bill shock is the main self-serve risk. The three accounts with 2–4x increases are the ones most worth a personal call. They are also the three loss-makers (P, Q and V).
  • A 2–3x enterprise increase may cost us one or two accounts. I think that is acceptable, but it is a judgment call.
  • Full enterprise run-rate arrives only after the last renewal in November 2027. Savings this year come mostly from self-serve and any early renewals.
  • Not yet checked: contract terms (fair-use or reopener clauses) and whether billing can meter pooled pages by April.

Decision requested: approve the model for planning, and let me begin the Copperfield and Northwind conversations this quarter.

Grades and run details

Decision model 77 · LLM judge 79
Decision model checks
  • failUses the supplied evidence correctly13%
  • passAddresses the actual decision70%
  • passRespects explicit constraints38%
  • passIdentifies material uncertainty71%
  • partialAvoids unsupported claims41%
  • passProduces the required deliverable77%
  • passFixes the value metric100%
  • passDoesn't trust the price test100%
  • passPlans the renewals100%
  • passEach tier for a different buyer87%
  • failGets the base of every number right45%
  • partialPriced on willingness to pay33%
  • passMoves existing customers fairly83%
Run
Run
#1
API response time
2.1 min
Submitted
6 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

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 correctlyWrongMixedWrong
Gemini 3.8 Flash · API

The claim that the price test ran for 13 days is not supported; the source says 8 to 21 December, which is 14 days.

Sonnet 5.5 · API

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

Identifies material uncertaintyWrongMixedRight
Gemini 3.8 Flash · API

The output does not name specific unknowns that could change the decision or how they would be resolved.

Sonnet 5.5 · API

It names some unknowns (contract terms, billing capability) but does not bound them or specify what would change the decision, and does not say how churn risk would be resolved beyond a judgment call.

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 claimsWrongRightWrong
Gemini 3.8 Flash · API

Forecasts like 'doubles monthly revenue to $82.9k, and achieves a sustainable 60.3% gross margin' are presented as confident claims without being labelled as projections.

Sonnet 5.5 · API

Interpretations like the cause of margin decline are directly supported by the cost and pricing structure; no unsupported claims are presented as 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 3.8 Flash · API

The memo with table is complete, addressed to the CEO, and provides an actionable plan.

Sonnet 5.5 · API

The memo is complete, addressed to the CEO, includes the required table and all requested elements, and is actionable.

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 metricRightRightWrong
Gemini 3.8 Flash · API

The output computes enterprise share of pages and negative margin, and proposes a hybrid usage-based model with per-page tiers.

Sonnet 5.5 · API

It computes the enterprise share of pages (71%) and their negative margin, and proposes usage-based pricing with per-page 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 buyerRightRightMixed
Gemini 3.8 Flash · API

The two tiers (Self-Serve and Enterprise) name distinct buyers and include features each values (e.g., SLA, custom models for enterprise).

Sonnet 5.5 · API

Each tier (startup, mid-market, enterprise) is built for a distinct buyer with a different value metric and pricing structure.

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 rightMixedMixedWrong
Gemini 3.8 Flash · API

All derived percentages and margins check out against the supplied data; the 13-day error is a factual claim, not a computation error.

Sonnet 5.5 · API

All derived figures (margins, revenue changes, percentages) check out against the supplied data with correct denominators.

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 3.8 Flash · API

The output relies on competitor pricing as a proxy for willingness to pay but does not state where the evidence is thin or use direct WTP signals from the material.

Sonnet 5.5 · API

Prices are grounded in competitor rates and value delivered, with margin considerations, not just cost-plus or round numbers.

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.

Moves existing customers fairlyMixedMixedRight
Gemini 3.8 Flash · API

The transition plan lacks a mechanism for watching churn, which is required for moving existing customers fairly.

Sonnet 5.5 · API

The transition plan includes notice periods and value justification but does not specify how churn will be monitored or watched.

GPT-6 Luna · API

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

All mixed 1

Addresses the actual decisionMixedMixedMixed
Gemini 3.8 Flash · API

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

Sonnet 5.5 · API

The output commits to a recommendation but does not state what specific result or condition would change that call, only noting it is a judgment call.

GPT-6 Luna · API

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

All got right 3

Respects explicit constraintsRightRightRight
Gemini 3.8 Flash · API

The output is a memo to the CEO, includes the required table, and appears to be within 1,300 words.

Sonnet 5.5 · API

The output is a memo to the CEO, includes the required table, and is well within the 1,300-word limit.

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 3.8 Flash · API

The output names the sample ratio mismatch and the holiday timing, and does not rest the decision on the test.

Sonnet 5.5 · API

It identifies the uneven split (59/41), the holiday timing, and the insufficient sample size, and does not rely on the test.

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 3.8 Flash · API

The output gives specific renewal approaches for Copperfield (Jan), Northwind (Feb), and Arcadia (Mar), using their dates and notes.

Sonnet 5.5 · API

It gives a specific approach for each near-term enterprise renewal, using their dates and notes (Copperfield, Northwind, Arcadia, etc.).

GPT-6 Luna · API

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

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