Worked examples
45 real-world scenarios with cited benchmark data. Load one into a calculator, see how the math behaves, then swap in your own numbers. Example data never touches your saved work until you adopt it.
Is this business healthy?
SaaS Economics · 15 worked examples
Series A SaaS
B2B SMB SaaS at ~$3M ARR. ARPU $185, 78% gross margin, 3.2% monthly churn.
Consumer subscription app
Mobile fitness/wellness app on a monthly plan. ARPU $9.40, 68% gross margin, 8.5% monthly churn.
Struggling early-stage tool
Pre-PMF tool for freelancers. ARPU $52, 72% gross margin, 7.5% monthly churn — the cautionary tale.
PLG SaaS
Self-serve B2B tool, mostly content + community + product virality. Quarterly: $185K spend, 820 new customers.
Sales-led enterprise SaaS
Six-figure ACV product with AEs, SDRs, SEs. Quarterly: $2.4M spend, 18 new customers.
DTC consumer brand
Shopify-based skincare/apparel, mostly Meta + TikTok ads. Monthly: $84K spend, 1,650 new customers.
Early-stage B2B SaaS
1,000 customers at period start, 65 cancel during the month — 6.5% monthly churn.
6.5% monthly churn compounds to ~55% annually and reads as poor against the blended B2B benchmark — early-stage churn this high caps growth before acquisition can outrun it.
Consumer subscription app
50,000 subscribers at period start, 4,500 cancel during the month — 9% monthly churn.
9% monthly churn is normal for consumer subscriptions but limits average customer lifetime to ~11 months — LTV math, not retention heroics, has to carry the business.
Enterprise SaaS
200 enterprise accounts at period start, 2 churn during the month — 1% monthly churn.
1% monthly churn means a 100-month average customer lifetime — this is why enterprise businesses can justify CAC that would sink an SMB product.
Fast-growing SaaS
$500K starting MRR. +$80K new, +$30K expansion, −$10K contraction, −$25K churn → +15% net new MRR.
+15% in a month is a pace very few SaaS companies sustain — and even it can hide an installed base that is quietly shrinking: NRR lands just below 100%, so all the growth is new logos.
Mature plateau
$2M starting MRR. +$100K new, +$50K expansion, −$30K contraction, −$120K churn → flat net new MRR.
Quick Ratio of exactly 1.0 means every new dollar only replaces a lost one — the business runs hard to stand still.
Net negative
$300K starting MRR. +$20K new, +$5K expansion, −$15K contraction, −$45K churn → contracting.
With a Quick Ratio of 0.42 the business loses about $2.40 for every $1 it adds — acquisition cannot outrun churn like this; fix retention first.
Quick-win feature
$40K engineering cost, $15K/month gain — 2.7-month payback, 350% ROI in year 1.
Sub-3-month payback with 350% first-year ROI is the no-brainer quadrant — when you find one of these, fast-track it past the roadmap queue.
Platform investment
$400K cost, $20K/month gain — 20-month payback, 80% ROI over 3 years.
Platform bets pay back slowly — a 20-month payback only clears the bar if the option value it unlocks is real, so name that value explicitly in the business case.
Marketing experiment
$25K cost, $8K/month gain for 6 months only — break-even in ~3 months, 92% ROI net.
Time-boxed benefits change the math: a campaign that stops paying after 6 months still clears 92% ROI, but only because the payback landed inside the benefit window.
What should we build first?
Prioritization · 12 worked examples
Growth team backlog
Seven ideas mixing high-confidence quick wins with speculative big bets.
The 'transformational' AI-pages idea (impact 9) scores 108 — far below a humble checkout fix at 512 — because ICE multiplies: confidence 3 cuts any idea by 70% on its own.
Onboarding ideas
Six ideas that all target the same new-user audience.
When every idea reaches the same users, ICE ranks as well as RICE without reach data — the 162-336 spread here comes mostly from ease and confidence.
Marketing channel tests
Six channel bets where confidence varies wildly.
Confidence is the honesty dial: channels you've already run (Google Ads at 432, email at 405) outrank shinier untested ones — run cheap probes to earn TikTok a higher confidence score, not a bigger budget.
Onboarding optimization
Ten onboarding ideas spread across all four quadrants.
Three tooltip-sized quick wins can ship this sprint while the flow redesign earns a planned project — and per-vertical customization lands in the time-sink quadrant where most custom work belongs.
Growth experiments
Ten growth ideas, from a referral CTA to a new pricing tier.
The referral CTA (quick win) and the pricing tier (big bet) both deserve investment — the webinar series is the classic time sink: real recurring effort, diffuse impact.
Tech debt vs features
Ten items mixing debt paydown with feature work.
Debt that unblocks speed — query caching, flaky CI — scores like feature work; ground-up rewrites and blanket coverage mandates are where debt projects go to die.
B2B SaaS feature audit
Six features across all five Kano categories for a B2B SaaS roadmap review.
Basics like SSO and audit logs take the top priority scores despite zero delight upside — missing must-bes drive churn faster than delighters drive growth.
Consumer mobile app
Six features for a consumer app, including a fully-built Reverse feature.
The forced login is 90% implemented and still classifies as Reverse — implementation level measures completeness, not whether users want the feature at all.
Marketplace trust audit
Six features for a two-sided marketplace where trust is the product.
Verification and secure checkout classify as must-bes in marketplaces — chat and recommendations can only delight buyers who already feel safe.
Are users coming back?
Growth & Engagement · 12 worked examples
Healthy B2B SaaS
$100K starting MRR, +$6K expansion, −$2K contraction, −$3K churn, 200 → 196 customers.
GRR of 95% with NRR just above 100% is the plateau shape of a healthy retention curve — expansion from the surviving base covers the leak.
Strong consumer mobile
$50K starting MRR, +$1K expansion, −$1.5K contraction, −$4.5K churn, 10,000 → 9,100 customers.
Consumer products lose users fast up front — a 91% monthly logo retention is survivable only if the curve plateaus, so watch whether the same cohort keeps declining.
No PMF warning
$80K starting MRR, +$0.5K expansion, −$4K contraction, −$12K churn, 400 → 330 customers.
NRR near 80% every month compounds to losing most of the base within a year — a curve that never flattens is the clearest quantitative signal of missing product-market fit.
Consumer messaging app
8M MAU with 4.8M DAU — a 60% stickiness ratio.
60% means a typical monthly user shows up most days — social/messaging territory, well above the 40% bar this calculator rates as exceptional.
Productivity SaaS
250k MAU with 75k DAU — a 30% stickiness ratio.
30% is strong for a workday tool: a user active every working day caps out near 73% (22 of 30 days), so weekday products should never be judged against consumer-app ratios.
Weekly-cadence B2B tool
40k MAU with 6k DAU — a 15% stickiness ratio.
15% looks weak next to consumer apps, but a product every user opens exactly once a week would sit near 14% (1 in 7 days) — this tool is at its natural ceiling, not failing.
E-commerce checkout
50,000 monthly visitors, 1,200 purchases — a 2.4% conversion rate.
2.4% sits inside the typical 2-3% e-commerce band — the optimization target is the 97.6% who left, starting with the checkout steps where they dropped.
SaaS trial to paid
10,000 trial signups, 1,800 convert to paid — an 18% trial conversion rate.
18% matches First Page Sage's opt-in trial average, yet ChartMogul's broader study puts the median nearer 9% — trial benchmarks vary wildly by study and trial model, so name your source before declaring victory.
B2B demo to opportunity
800 demo requests, 96 become qualified opportunities — a 12% conversion rate.
Small funnels swing hard: at 800 demos, ten deals either way moves the rate by 1.25 points — trend B2B funnel stages quarterly, not weekly.
B2B SaaS at 50
240 responses: 60% promoters, 30% passives, 10% detractors across enterprise and SMB segments.
60% promoters minus 10% detractors nets NPS 50 — excellent territory — and the segment split shows enterprise (65) carrying SMB (43).
E-commerce at 25
400 responses: 45% promoters, 35% passives, 20% detractors — below the 40-50 average for consumer retail.
NPS 25 is below the e-commerce average of 40-50, and the 35% passives are the bigger risk: they don't subtract from the score, but they're one bad delivery away from becoming detractors.
Telecom at -10
300 responses: 30% promoters, 30% passives, 40% detractors — bottom-of-category telecom territory.
When detractors outnumber promoters, NPS goes negative — the telecom category average sits near 20, but the lowest-rated ISPs and cable brands post scores like this; benchmark against category peers, not the global 'above 50 is excellent' bar.
Is this result real?
Validation & Research · 6 worked examples
NPS survey
Survey a 50,000-customer base at 95% confidence with a ±5% margin and a 20% email response rate.
A 50k base needs only 382 completes for ±5% at 95% confidence — sample size is driven by precision, not population — but a 20% response rate means planning 1,910 invites.
High-precision launch survey
Large audience at 95% confidence with a tight ±2% margin and a 15% in-app response rate.
Precision is quadratic: tightening ±5% to ±2% multiplies the sample by (5/2)² ≈ 6x to 2,401 completes — about 16,000 invites at a 15% response rate, so budget weeks of fielding, not days.
Pricing research
2,500 eligible customers at 90% confidence with a ±7% margin, analyzed across 5 pricing segments.
131 responses meets ±7% at 90% confidence overall — but split across 5 pricing segments that is ~26 per cell, so recruit ~30 per segment (150 total) rather than trusting the topline number.
E-commerce checkout test
Checkout flow converting at 3%, testing for a 10% relative lift with 8,000 visitors a day.
Six figures of sample size sounds scary, but healthy traffic clears it in about two weeks.
Low-traffic B2B signup test
Signup page converting at 5%, testing for a 10% relative lift — but only 400 visitors a day.
At 400 visitors a day this test runs for roughly five months. Raise the MDE or skip the test.
High-traffic onboarding test
Onboarding step converting at 40%, testing for a 5% relative lift with 50,000 users a day.
Huge traffic hits significance in hours — run a full week anyway to capture weekday-weekend cycles.
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