saas-revenue-growth-metrics

name	saas-revenue-growth-metrics
description	Calculate SaaS revenue, retention, and growth metrics. Use when diagnosing momentum, churn, expansion, or product-market-fit signals.
intent	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.
type	component
theme	finance-metrics
best_for	["Understanding your key revenue and retention metrics","Calculating MRR, ARR, churn, and NRR correctly","Building a metrics dashboard for your SaaS product"]
scenarios	["I need to calculate and interpret our MRR, churn rate, and NRR for a board deck","Help me understand the difference between gross and net revenue retention and how to improve it"]
estimated_time	10-15 min

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

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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

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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

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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.

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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

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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?

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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?)

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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)

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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)?

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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?

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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)

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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?

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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

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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?)

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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?

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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)

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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?

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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

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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

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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.

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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?

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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.

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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.

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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.

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Pitfall 3: Ignoring Cohort Degradation

Symptom: "Blended churn is stable at 3%"

Consequence: Blended metrics can hide that new cohorts churn at 6% while old cohorts churn at 1%. Product-market fit is degrading.

Fix: Always analyze retention by cohort. If newer cohorts perform worse, stop scaling and fix the product.

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Pitfall 4: Logo Churn vs. Revenue Churn Confusion

Symptom: "Logo churn is only 2%, we're great!"

Consequence: You might be losing 2% of customers but 10% of revenue if you're churning large customers.

Fix: Track both logo churn AND revenue churn. If revenue churn > logo churn, you're losing high-value customers.

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Pitfall 5: Treating All Churn Equally

Symptom: "We lost 50 customers this month" (no context on who)

Consequence: Losing 50 small customers ($10/month) is different from losing 50 enterprise customers ($10K/month).

Fix: Segment churn analysis by customer size, cohort, and reason. Weight by revenue impact, not just logo count.

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Pitfall 6: Forgetting Compounding Churn

Symptom: "3% monthly churn is fine, that's only 36% annually"

Consequence: Churn compounds. 3% monthly = 31% annual churn, not 36%. Math: 1 - (1 - 0.03)^12 = 31%.

Fix: Use the correct formula when converting monthly to annual churn. Don't just multiply by 12.

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Pitfall 7: Celebrating Gross Revenue While Net Contracts

Symptom: "Gross revenue is up 20%!" (but discounts/refunds doubled)

Consequence: Net revenue might be flat or shrinking. Discounts hide pricing power problems; refunds hide product quality issues.

Fix: Always track gross AND net revenue. If discounts >20% or refunds >10%, investigate why.

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Pitfall 8: NRR >100% from Low Churn, Not Expansion

Symptom: "NRR is 105%, we're expanding!"

Consequence: NRR can be >100% just from very low churn, without meaningful expansion. True expansion-driven NRR is >120%.

Fix: Break down NRR into components: expansion MRR vs. churned/contracted MRR. Aim for expansion-driven NRR, not just low churn.

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Pitfall 9: Revenue Concentration Risk

Symptom: "We're at $10M ARR!" (but $5M is from one customer)

Consequence: Losing that one customer cuts revenue in half. Roadmap becomes hostage to one customer's requests.

Fix: Track revenue concentration. Ideal: Top customer <10% of revenue, Top 10 customers <40%. Diversify early.

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Pitfall 10: Averaging ARPU/ARPA Across Segments

Symptom: "Our ARPU is $100" (average of $10 SMB and $1,000 enterprise)

Consequence: Blended ARPU hides segment economics. Can't make smart acquisition or product decisions.

Fix: Calculate ARPU/ARPA by segment (SMB, mid-market, enterprise). Optimize each segment independently.

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References

Related Skills

• saas-economics-efficiency-metrics — Unit economics (CAC, LTV, margins, burn rate)
• finance-metrics-quickref — Fast lookup for all metrics
• feature-investment-advisor — Uses revenue metrics to evaluate feature ROI
• finance-based-pricing-advisor — Uses ARPU/ARPA to evaluate pricing changes
• business-health-diagnostic — Uses revenue/retention metrics to diagnose business health

External Frameworks

• Bessemer Venture Partners: "SaaS Metrics 2.0" — Definitive guide to SaaS metrics
• David Skok (Matrix Partners): "SaaS Metrics" blog series — Deep dive on unit economics
• Tomasz Tunguz (Redpoint): SaaS benchmarking research
• Tien Tzuo: Subscribed — Subscription business model fundamentals
• ChartMogul, Baremetrics, ProfitWell: SaaS analytics platforms with metric definitions

Provenance

• Adapted from research/finance/Finance for Product Managers.md
• Consolidated from research/finance/Finance_QuickRef.md
• Common mistakes from research/finance/Finance_Metrics_Additions_Reference.md