saas-revenue-growth-metrics▌
deanpeters/product-manager-skills · updated Apr 8, 2026
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Calculate and interpret core SaaS revenue, retention, and growth metrics to diagnose business momentum and product-market fit.
- ›Covers 10+ essential metrics: MRR/ARR, ARPU/ARPA, churn rate, NRR, expansion revenue, and Quick Ratio, with formulas and quality checks for each
- ›Includes cohort analysis and revenue mix frameworks to reveal hidden trends that blended metrics obscure (e.g., cohort degradation, concentration risk)
- ›Provides benchmarks for each metric (e.g., <2% monthly chur
Purpose
Master revenue and retention metrics to understand SaaS business momentum, evaluate product-market fit, and make data-driven decisions about growth investments. Use this to calculate key metrics, interpret trends, identify problems early, and communicate business health to stakeholders.
This is not a business intelligence tool—it's a framework for PMs to understand which metrics matter, how to calculate them correctly, and what actions to take based on the numbers.
Key Concepts
Revenue Metrics Family
The "top-line" metrics that measure how much money the business generates.
Revenue — Total money earned from selling products/services before expenses. The "top line" of the income statement.
- Why PMs care: Every feature should connect to revenue (direct or indirect). If you can't articulate revenue impact, prioritization becomes impossible.
- Formula: Sum of all customer payments in a period
- Benchmark: Growth rate matters more than absolute number (context-dependent by stage)
ARPU (Average Revenue Per User) — Average revenue generated per individual user.
- Why PMs care: Measures per-seat monetization effectiveness. Critical for seat-based pricing models.
- Formula:
Total Revenue / Total Users - Benchmark: Varies by model; track trend more than absolute value
- B2C SaaS: $5-50/month typical; B2B: $50-500+/month
ARPA (Average Revenue Per Account) — Average revenue generated per customer account.
- Why PMs care: Measures account-level deal size. Critical for account-based pricing models.
- Formula:
MRR / Active Accounts - Benchmark: SMB SaaS: $100-$1K/month; Mid-market: $1K-$10K; Enterprise: $10K+
ARPA/ARPU Analysis — Using both metrics together to understand monetization.
- Why PMs care: Prevents packaging mistakes. High ARPA + low ARPU = undermonetized per seat. Low ARPA + high ARPU = small deal sizes.
- Example: $10K ARPA with 100 seats = $100 ARPU (reasonable). $10K ARPA with 1,000 seats = $10 ARPU (leaving money on table).
ACV (Annual Contract Value) — Annualized recurring revenue per contract (excludes one-time fees).
- Why PMs care: Compares economics across different contract structures. Enables sales compensation design and segment analysis.
- Formula:
Annual Recurring Revenue per Contract(don't include setup fees, professional services) - Benchmark: SMB: $5K-$25K; Mid-market: $25K-$100K; Enterprise: $100K+
MRR/ARR (Monthly/Annual Recurring Revenue) — Predictable recurring revenue normalized to monthly or annual.
- Why PMs care: The heartbeat of subscription businesses. Valued at 5-10x+ multiples. Track components (new, expansion, churn).
- Formula:
MRR = Sum of all recurring subscription revenue per month;ARR = MRR × 12 - Benchmark: Growth rate and quality matter; track new MRR, expansion MRR, churned MRR, contracted MRR
Gross vs. Net Revenue — Gross revenue before vs. net revenue after discounts, refunds, credits.
- Why PMs care: Discounts and refunds can hide bad acquisition quality or product problems.
- Formula:
Net Revenue = Gross Revenue - Discounts - Refunds - Credits - Benchmark: Refunds >10% is a red flag; track by acquisition channel
Retention & Expansion Metrics Family
Metrics that measure how well you keep and grow existing customers.
Churn Rate — Percentage of customers who cancel in a period.
- Why PMs care: Silent killer of SaaS. Undermines all acquisition efforts. 5% monthly churn = 46% annual churn (compounding).
- Formula:
Customers Lost in Period / Starting Customers - Benchmark (Monthly): <2% great, 2-5% acceptable, >5% crisis
- Benchmark (Annual): <10% great, 10-30% acceptable, >30% crisis
- Note: Logo churn (customer count) differs from revenue churn (dollar amount)
NRR (Net Revenue Retention) — Revenue retention from existing customers including expansion and contraction.
- Why PMs care: The holy grail metric. NRR >100% means you grow without new logos. Highly valued by investors.
- Formula:
(Starting ARR + Expansion - Churn - Contraction) / Starting ARR × 100 - Benchmark: >120% excellent, 100-120% good, 90-100% acceptable, <90% problem
- Example: Start with $1M ARR, add $300K expansion, lose $100K to churn = $1.2M / $1M = 120% NRR
Expansion Revenue — Additional revenue from existing customers (upsells, cross-sells, usage growth).
- Why PMs care: Most capital-efficient revenue (no CAC). Should drive NRR >100%.
- Formula:
Sum of upsells + cross-sells + usage increases from existing customers - Benchmark: Should represent 20-30% of total revenue; drives NRR >100%
Quick Ratio (SaaS) — Revenue gains vs. revenue losses.
- Why PMs care: Shows if you're building on solid ground or running on a treadmill.
- Formula:
(New MRR + Expansion MRR) / (Churned MRR + Contraction MRR) - Benchmark: >4 excellent, 2-4 healthy, <2 leaky bucket
Analysis Frameworks
Revenue Mix Analysis — Breakdown of revenue by product, segment, or channel.
- Why PMs care: Identifies which products fund the business and where to invest. Reveals concentration risk.
- Formula:
Product/Segment Revenue / Total Revenue × 100 - Benchmark: No single product >60% ideal; diversification reduces risk
Cohort Analysis — Group customers by join date and track behavior over time.
- Why PMs care: Blended metrics hide critical trends. Shows whether business is improving or degrading.
- Method: Track retention, expansion, and LTV by cohort (e.g., "Jan 2024 cohort")
- Benchmark: Recent cohorts should perform same or better than old cohorts
Anti-Patterns (What This Is NOT)
- Not profit metrics: Revenue is top-line, not bottom-line. High revenue with negative margins is a disaster.
- Not vanity metrics: Total revenue growth means nothing if driven by unsustainable discounting or margin-destroying deals.
- Not blended averages: ARPU that averages $10 SMB and $1,000 enterprise customers hides segment economics.
- Not isolated numbers: Churn rate alone doesn't tell the story—need to see cohort trends and NRR.
When to Use These Metrics
Use these when:
- Evaluating overall business health and product-market fit
- Comparing performance across time periods or cohorts
- Prioritizing features with direct monetization paths (ARPU impact, expansion enablers)
- Communicating with leadership, board, or investors
- Assessing retention problems (churn analysis, cohort degradation)
- Measuring pricing or packaging changes (ARPU/ARPA shifts)
Don't use these when:
- Evaluating profitability (use margin metrics instead)
- Assessing capital efficiency (use LTV:CAC, payback period)
- Making product investment decisions without cost context (revenue alone isn't ROI)
- Comparing across wildly different business models without normalization
Application
Step 1: Calculate Revenue Metrics
Use the templates in template.md to calculate your core revenue metrics.
Revenue
Revenue = Sum of all customer payments in period
Example:
- Month 1 payments: $100,000
- Revenue = $100,000
Quality checks:
- Is this gross or net revenue? (Clarify if discounts/refunds are included)
- Is revenue growing cohort-over-cohort, or just from new customer adds?
- What's the revenue growth rate vs. headcount/cost growth rate?
ARPU (Average Revenue Per User)
ARPU = Total Revenue / Total Users
Example:
- Total Revenue: $100,000/month
- Total Users: 2,000
- ARPU = $100,000 / 2,000 = $50/user/month
Quality checks:
- Is ARPU growing or shrinking over time?
- Is ARPU growth from price increases or mix shift (losing small customers)?
- How does ARPU vary by cohort? (Are new customers less valuable?)
ARPA (Average Revenue Per Account)
ARPA = MRR / Active Accounts
Example:
- MRR: $100,000
- Active Accounts: 200
- ARPA = $100,000 / 200 = $500/account/month
Quality checks:
- Is ARPA growing from expansion or just larger new deals?
- How does ARPA compare across customer segments?
- Is ARPA high but ARPU low? (Undermonetized per seat)
ARPA/ARPU Combined Analysis
ARPA = MRR / Active Accounts
ARPU = MRR / Total Users
Average Seats per Account = ARPA / ARPU
Example:
- ARPA: $500/month
- ARPU: $50/month
- Average Seats: $500 / $50 = 10 seats/account
Quality checks:
- Are you monetizing per seat effectively?
- Could you charge more per seat (raise ARPU)?
- Could you expand seat count per account (raise ARPA)?
ACV (Annual Contract Value)
ACV = Annual Recurring Revenue per Contract
(Exclude one-time fees like setup, professional services)
Example:
- Customer signs 3-year contract for $300K total
- ACV = $300K / 3 years = $100K/year
Quality checks:
- How does ACV vary by segment (SMB vs. Enterprise)?
- Is ACV growing over time (moving upmarket)?
- Does ACV justify sales team cost structure?
MRR/ARR (Monthly/Annual Recurring Revenue)
MRR = Sum of all recurring monthly subscriptions
ARR = MRR × 12
Track components:
- New MRR (from new customers)
- Expansion MRR (from upsells/cross-sells)
- Churned MRR (from lost customers)
- Contraction MRR (from downgrades)
Example:
- Starting MRR: $500K
- New MRR: +$50K
- Expansion MRR: +$20K
- Churned MRR: -$15K
- Contraction MRR: -$5K
- Ending MRR: $550K
- ARR = $550K × 12 = $6.6M
Quality checks:
- Is MRR growth from new customers or expansion?
- Is churn/contraction increasing as you grow?
- What's the ratio of new:expansion:churn MRR? (Best: expansion > new)
Gross vs. Net Revenue
Net Revenue = Gross Revenue - Discounts - Refunds - Credits
Example:
- Gross Revenue: $100K
- Discounts: -$10K
- Refunds: -$2K
- Net Revenue: $88K
Quality checks:
- Are discounts >20%? (Pricing power problem)
- Are refunds >10%? (Product quality problem)
- Do certain channels have higher discount/refund rates?
Step 2: Calculate Retention & Expansion Metrics
Churn Rate
Logo Churn Rate = Customers Lost / Starting Customers × 100
Revenue Churn Rate = MRR Lost / Starting MRR × 100
Example (Logo Churn):
- Starting Customers: 1,000
- Customers Lost: 30
- Logo Churn = 30 / 1,000 = 3% monthly
Example (Revenue Churn):
- Starting MRR: $500K
- MRR Lost: $15K
- Revenue Churn = $15K / $500K = 3% monthly
Quality checks:
- Is churn rate accelerating or decelerating over time?
- Are newer cohorts churning faster than older ones? (PMF degradation)
- Is revenue churn higher than logo churn? (Losing big customers)
Convert monthly to annual:
- Monthly churn compounds: 3% monthly ≠ 36% annual
- Formula:
Annual Churn = 1 - (1 - Monthly Churn)^12 - 3% monthly = ~31% annual churn
NRR (Net Revenue Retention)
NRR = (Starting ARR + Expansion - Churn - Contraction) / Starting ARR × 100
Example:
- Starting ARR: $5M
- Expansion: +$800K
- Churn: -$300K
- Contraction: -$100K
- Ending ARR from cohort: $5.4M
- NRR = $5.4M / $5M = 108%
Quality checks:
- Is NRR >100%? (You grow without new logos)
- Is NRR improving or degrading cohort-over-cohort?
- What's driving NRR? (Expansion or low churn?)
Expansion Revenue
Expansion Revenue = Upsells + Cross-sells + Usage Growth (from existing customers)
Example:
- Upsells to higher tier: $50K/month
- Cross-sells of add-ons: $20K/month
- Usage growth: $10K/month
- Total Expansion Revenue: $80K/month
Quality checks:
- Is expansion revenue growing as % of total revenue?
- What % of customers expand each year? (Expansion rate)
- Are certain cohorts/segments more likely to expand?
Quick Ratio (SaaS)
Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
Example:
- New MRR: $50K
- Expansion MRR: $20K
- Churned MRR: $15K
- Contraction MRR: $5K
- Quick Ratio = ($50K + $20K) / ($15K + $5K) = $70K / $20K = 3.5
Quality checks:
- Quick Ratio >4 = excellent (gains far exceed losses)
- Quick Ratio 2-4 = healthy (sustainable growth)
- Quick Ratio <2 = leaky bucket (fix retention before scaling)
Step 3: Analyze Trends with Frameworks
Revenue Mix Analysis
Product/Segment % = Product/Segment Revenue / Total Revenue × 100
Example:
- Product A Revenue: $300K
- Product B Revenue: $500K
- Product C Revenue: $200K
- Total Revenue: $1M
- Product A: 30%, Product B: 50%, Product C: 20%
Quality checks:
- Is revenue concentration increasing? (Risk: over-reliance on one product)
- Which products are growing/shrinking?
- Does revenue mix match your strategic priorities?
Cohort Analysis
Group customers by when they joined and track metrics over time.
Example:
| Cohort | Month 0 | Month 1 | Month 2 | Month 3 | Month 6 |
|---|---|---|---|---|---|
| Jan 2024 | 100% | 95% | 92% | 90% | 85% |
| Feb 2024 | 100% | 94% | 90% | 87% | 80% |
| Mar 2024 | 100% | 92% | 86% | 82% | - |
Quality checks:
- Are recent cohorts retaining better or worse than older cohorts?
- If worse: Product-market fit is degrading (fix before scaling)
- If better: Improvements are working (safe to scale)
- Track revenue retention by cohort, not just logo retention
Step 4: Quality Checks & Benchmarks
Before reporting metrics, validate:
Revenue metrics:
- ✅ Gross vs. net revenue clearly labeled
- ✅ Revenue growth rate > cost growth rate
- ✅ ARPU/ARPA trends analyzed by cohort (not just blended)
Retention metrics:
- ✅ Logo churn and revenue churn both tracked
- ✅ Cohort-over-cohort trends analyzed (not just blended churn)
- ✅ NRR tracked with components (expansion, churn, contraction)
Analysis:
- ✅ Cohort analysis shows retention trends
- ✅ Revenue mix shows concentration risk
- ✅ Quick ratio shows growth sustainability
Examples
See examples/ folder for detailed scenarios. Mini examples below:
Example 1: Healthy SaaS Metrics
Company: Mid-market project management SaaS
Revenue Metrics:
- MRR: $2M (growing 10% month-over-month)
- ARR: $24M
- ARPA: $1,200/month (200 accounts)
- ARPU: $120/month (20,000 users)
- Average seats: 100 per account
Retention Metrics:
- Monthly logo churn: 2%
- Revenue churn: 1.5% (losing smaller customers)
- NRR: 115% (strong expansion)
- Expansion revenue: $200K/month (10% of MRR)
- Quick Ratio: 5.0
Analysis:
- ✅ Strong growth (10% MoM MRR)
- ✅ Excellent retention (2% logo churn, 115% NRR)
- ✅ Healthy expansion (NRR >100%)
- ✅ Sustainable (Quick Ratio 5.0)
- ✅ Revenue churn < logo churn (losing smaller customers, good signal)
Action: Scale acquisition. Unit economics are strong.
Example 2: Warning Signs
Company: SMB marketing automation SaaS
Revenue Metrics:
- MRR: $500K (growing 15% month-over-month)
- ARR: $6M
- ARPA: $250/month (2,000 accounts)
- ARPU: $50/month (10,000 users)
Retention Metrics:
- Monthly logo churn: 6% (increasing from 4% six months ago)
- Revenue churn: 7% (losing larger customers)
- NRR: 85% (contracting)
- Expansion revenue: $5K/month (1% of MRR)
- Quick Ratio: 1.2
Cohort Analysis:
| Cohort | Month 6 Retention |
|---|---|
| 6 months ago | 75% |
| 3 months ago | 65% |
| Current | 58% |
Analysis:
- ⚠️ High churn (6% monthly = ~50% annual)
- 🚨 Revenue churn > logo churn (losing bigger customers)
- 🚨 NRR <100% (contracting, not expanding)
- 🚨 Cohort degradation (newer customers churn faster)
- 🚨 Quick Ratio 1.2 (leaky bucket)
Action: STOP scaling acquisition. Fix retention first. Investigate:
- Why are newer cohorts churning faster?
- Why is expansion revenue only 1% of MRR?
- What's causing customer contraction?
Example 3: Blended Metrics Hiding Problems
Company: Multi-product SaaS platform
Blended Metrics Look Great:
- MRR: $3M (growing 20% MoM)
- Blended churn: 3%
- Blended NRR: 110%
But Revenue Mix Analysis Shows:
| Product | Revenue | % of Total | Growth | Churn | NRR |
|---|---|---|---|---|---|
| Legacy Product | $2M | 67% | -5% MoM | 8% | 75% |
| New Product | $1M | 33% | +80% MoM | 1% | 150% |
Analysis:
- 🚨 Legacy product (67% of revenue) is dying: -5% growth, 8% churn, 75% NRR
- ✅ New product is stellar: +80% growth, 1% churn, 150% NRR
- ⚠️ Blended metrics hide the fact that 2/3 of revenue is contracting
- ⚠️ High dependency on one product (67% concentration risk)
Action: Accelerate migration from legacy to new product. Plan for legacy product sunset.
Common Pitfalls
Pitfall 1: Confusing Revenue with Profit
Symptom: "We grew revenue 50% this year, we're crushing it!"
Consequence: Revenue is the top line, not bottom line. You might be growing at a loss, destroying margins, or scaling unprofitable products.
Fix: Always pair revenue metrics with margin metrics (see saas-economics-efficiency-metrics). $1M revenue at 80% margin >> $2M revenue at 20% margin.
Pitfall 2: Celebrating ARPU Growth from Mix Shift
Symptom: "ARPU increased 30%!" (but customer count dropped 40%)
Consequence: ARPU rose because you lost all your small customers, not because you improved monetization.
Fix: Analyze ARPU by cohort and segment. True ARPU improvement = same customers paying more, not losing cheap customers.
Pitfall 3: Ignoring Cohort Degradation
Symptom: "Blended churn is stable at 3%"
Consequence: Blended metrics can hide that new cohorts churn
How to use saas-revenue-growth-metrics on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add saas-revenue-growth-metrics
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches saas-revenue-growth-metrics from GitHub repository deanpeters/product-manager-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate saas-revenue-growth-metrics. Access the skill through slash commands (e.g., /saas-revenue-growth-metrics) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★50 reviews- ★★★★★Benjamin Martinez· Dec 24, 2024
We added saas-revenue-growth-metrics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Xiao Sethi· Dec 12, 2024
Registry listing for saas-revenue-growth-metrics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sophia Smith· Dec 8, 2024
saas-revenue-growth-metrics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★William Ghosh· Dec 4, 2024
Solid pick for teams standardizing on skills: saas-revenue-growth-metrics is focused, and the summary matches what you get after install.
- ★★★★★Ama Reddy· Nov 27, 2024
saas-revenue-growth-metrics has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★William Iyer· Nov 19, 2024
saas-revenue-growth-metrics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Benjamin Rahman· Nov 15, 2024
saas-revenue-growth-metrics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Maya Taylor· Nov 3, 2024
Keeps context tight: saas-revenue-growth-metrics is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Maya Haddad· Oct 22, 2024
I recommend saas-revenue-growth-metrics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ama Singh· Oct 18, 2024
saas-revenue-growth-metrics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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