6. Analyzing SaaS Performance

Learning Objectives:

• Apply Growth Accounting Formula to track inflows and outflows across time periods visualizing net changes
• Execute customer segmentation strategies grouping by industry, geography, ARR, or usage to tailor engagement
• Conduct cohort analysis tracking customer groups by shared attributes to identify retention and churn dynamics
• Perform six-type churn analysis: Customer, Revenue, Involuntary, Voluntary, Downgrade, Good churn
• Use four actionable analysis techniques: Behavioral cohort, Acquisition cohort, Subscription plan analysis, Billing interval comparison
• Implement Land-and-Expand model maximizing existing customer value through strategic upselling and cross-selling

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Introduction

Analyzing performance in SaaS companies requires structured approach to track customer behavior, measure retention, and identify opportunities for growth. This analysis is critical for driving key metrics like ARR, NRR, and churn while providing actionable insights for Customer Success, Product, and Revenue teams.

Effective performance analysis moves beyond simple metrics reporting to understanding underlying drivers: Why is churn happening? Which customer segments perform best? Where are expansion opportunities? What patterns predict success or failure? CSMs who master performance analysis can proactively address risks, optimize engagement strategies, and identify revenue opportunities before they're obvious.

The Cost of Poor Performance Analysis

Without structured analysis capabilities, CSMs may:

• React to churn after it happens rather than identifying patterns that predict and prevent it
• Miss expansion opportunities in customer segments showing strong retention and adoption signals
• Waste time on low-performing segments while underinvesting in high-value cohorts
• Fail to learn from customer behavior patterns repeating same mistakes across accounts
• Provide generic feedback to Product team without data showing which features drive retention
• Struggle to defend CS strategy decisions because can't demonstrate data-driven thinking

The Benefits of Mastering Performance Analysis

Performance analysis expertise enables you to:

• Predict churn through cohort and behavioral analysis identifying at-risk patterns before cancellation
• Identify expansion opportunities systematically through usage pattern analysis and segment comparison
• Optimize engagement strategies using data showing which approaches work best for which customer types
• Provide actionable Product feedback backed by retention and usage data across segments
• Demonstrate CS strategic value through insights driving business decisions beyond tactical account management
• Build credibility with leadership through data-driven recommendations and pattern recognition

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PART 1: GROWTH ACCOUNTING AND CUSTOMER SEGMENTATION

Growth Accounting Formula

What it is: Framework for forecasting and analyzing trends through inflows and outflows across time periods.

How it works:

Core principle: Any metric can be analyzed through what comes in (inflows) and what goes out (outflows).

Application to ARR:

Period 1 ARR: $10M

Inflows (additions):

• New ARR: +$3M
• Expansion ARR: +$1M
• Total inflows: +$4M

Outflows (reductions):

• Churned ARR: -$800K
• Downgrade ARR: -$200K
• Total outflows: -$1M

Period 2 ARR: $10M + $4M - $1M = $13M

Net change: +$3M (30% growth)

Visual stacking: Shows each component's contribution visually making growth drivers obvious.

Next Level Analysis - Identifying Drivers:

Once net change understood, identify underlying drivers through:

1. Dimensions (Attributes): Examine by geography, customer segment, product line

• Which regions growing fastest?
• Which customer segments churning most?
• Which products driving expansion?

2. Cohorts (Groups by shared characteristics): Analyze by onboarding date, acquisition source, usage pattern

• Are newer cohorts performing better than older?
• Which acquisition channels produce stickiest customers?
• Do usage patterns predict retention?

Customer Segmentation

What it is: Grouping customers based on attributes to deliver tailored strategies for retention and growth.

Common Segmentation Approaches:

By ARR/Contract Value:

• Enterprise (>$100K ARR): High-touch, dedicated CSM, monthly touchpoints
• Mid-Market ($25K-$100K): Standard CSM, quarterly QBRs
• SMB (<$25K): Low-touch, automated, reactive support

By Industry Vertical:

• FinTech customers: Compliance focus, security emphasis
• Healthcare customers: HIPAA requirements, data privacy
• Retail customers: Seasonal considerations, high volume

By Geography:

• North America: English language, US business hours
• EMEA: Multi-language, EU compliance (GDPR)
• APAC: Time zone challenges, local market nuances

By Usage Pattern:

• Power users: High adoption, expansion ready
• Standard users: Meeting adoption, maintain engagement
• Low users: At-risk, need intervention

Why Segmentation Matters:

Tailored engagement:

• Enterprise customers receive QBRs and dedicated CSMs
• SMB customers receive automated check-ins and self-service resources

Efficient resource allocation:

• High-value segments get more CSM time
• Low-value segments get automated scalable support

Better outcomes:

• Engagement matches customer needs and expectations
• Resources deployed where they have most impact

Example: CSM managing 60 accounts uses segmentation:

• 10 Enterprise accounts (>$100K): 60% of time, monthly calls
• 25 Mid-Market ($25-100K): 30% of time, quarterly check-ins
• 25 SMB (<$25K): 10% of time, automated + reactive

Result: Maintains 95% retention across segments with differentiated service levels.

💡 Pro Tip: Create your own segmentation model for your book even if company doesn't formally segment. Categorize accounts by ARR + health score, then allocate time proportionally. Example: "High ARR + Low Health = Priority 1 (immediate attention), High ARR + High Health = Priority 2 (expansion focus), Low ARR + Low Health = Priority 3 (assess if saveable)." This systematic prioritization ensures time spent where it matters most.

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Best Practices: Growth Accounting and Segmentation

• Use Growth Accounting to visualize ARR changes through inflows (New + Expansion) and outflows (Churn + Downgrade)
• Identify growth drivers through dimensional analysis (geography, segment, product) and cohort analysis (timing, source, patterns)
• Segment customers by multiple attributes: ARR, Industry, Geography, Usage pattern for tailored engagement
• Allocate CS time proportionally to segment value: Enterprise accounts get 60% time despite being 20% of accounts
• Create personal segmentation model for your book prioritizing by ARR + health score combination
• Use segmentation data to justify resource requests: "Managing 60 accounts across 3 segments requires different approach than treating all equally"
• Provide segmented performance data to leadership showing which customer types have best retention and why
• Review segment performance quarterly adjusting engagement strategies based on what's working vs. struggling

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PART 2: COHORT ANALYSIS AND CHURN ANALYSIS

 

Cohort Analysis

What it is: Grouping customers by shared attributes (signup date, product tier, acquisition source) and tracking performance over time.

Example Cohort Analysis:

Cohort (Signup Month)	Month 1 Retention	Month 3 Retention	Month 6 Retention	Month 12 Retention
January 2024	100%	92%	87%	82%
April 2024	100%	95%	91%	TBD
July 2024	100%	97%	TBD	TBD

Insights:

• Newer cohorts (July) showing better early retention than older (January)
• Suggests onboarding improvements working
• July cohort 97% at month 3 vs. January 92% (5% improvement)

Why Cohort Analysis Matters:

Identify patterns:

• Do customers from certain acquisition sources retain better?
• Are newer cohorts performing better after process improvements?
• At what point do customers typically churn?

Evaluate initiatives:

• Did new onboarding program improve retention?
• Are product updates helping or hurting adoption?
• Is pricing change affecting churn patterns?

CSM Application:

Identify high-risk cohorts: Use analysis to find groups with lower retention, then:

• Offer additional training
• Provide proactive check-ins
• Address common pain points

Measure engagement strategy impact:

• Track cohort before implementing new strategy
• Compare subsequent cohort performance
• Determine if strategy actually improved outcomes

Example:

Before: Q1 2024 cohort had 85% 6-month retention Intervention: Implemented monthly check-in calls for all new customers After: Q2 2024 cohort has 92% 6-month retention Result: Intervention improved retention by 7% (measurable impact)

Churn Analysis - Six Types of Churn

 

1. Customer Churn

• Definition: Percentage of customers lost
• Use: High-level retention view
• Limitation: Doesn't account for customer size differences

2. Revenue Churn

• Definition: Percentage of revenue lost
• Use: Financial impact perspective
• Advantage: Weighted by customer value

3. Involuntary Churn

• Definition: Customers lost due to failed payments (expired cards)
• Use: Identifies technical billing issues
• Prevention: Payment method update campaigns

4. Voluntary Churn

• Definition: Customers choosing to cancel
• Use: Richest insights for product and CS improvement
• Analysis: Why did they leave? What could have prevented it?

5. Downgrade Churn

• Definition: Customers reducing spending (lower tier)
• Use: Tracks revenue leakage from downgrades
• Often missed: Companies focus on full cancellations, ignore downgrades

6. Good Churn

• Definition: Poor-fit customers leaving voluntarily
• Use: Streamlines customer base toward product-market fit
• Positive sign: Losing customers who shouldn't have been acquired

Churn Analysis Best Practices:

• Distinguish between voluntary and involuntary to address root causes
• Track revenue churn separately from customer churn for financial impact
• Analyze voluntary churn for product and CS improvement insights
• Address involuntary churn through billing process improvements
• Monitor downgrade churn as early warning before full cancellation
• Recognize good churn helps focus on ideal customer profile

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PART 3: THE LAND-AND-EXPAND MODEL

How Land-and-Expand Works

 

Phase 1: LAND - Acquiring Customers

Goal: Secure initial customer adoption and establish foothold in organization.

Tactics:

• Efficient onboarding ensuring quick time-to-value
• Building trust through early wins and reliability
• Targeting entry points (small teams, limited licenses initially)

Example: SaaS company sells project management software to 50-person marketing team in larger enterprise. Initial contract: 10 users at $100/user/month = $12,000 ARR.

Phase 2: EXPAND - Growing Customer Value

Goal: Increase account's revenue through upselling, cross-selling, and wider adoption.

Tactics:

• Upselling: Higher-tier plans, add-on features, premium services
• Cross-selling: Complementary products enhancing primary solution
• Wider adoption: Expanding across teams, departments, regions

Example: After successful onboarding:

• Month 3: Marketing adds 20 more users → $36,000 ARR
• Month 9: Sales team adopts platform → $48,000 ARR
• Month 15: HR team implements → $60,000 ARR
• Total expansion: From $12K to $60K ARR (400% growth)

Why Land-and-Expand Succeeds

Revenue efficiency:

• Expansion revenue more cost-effective than new acquisition (3-5x cheaper)
• No CAC for expansion (customer already acquired)
• Shorter sales cycles for upsells vs. new sales

Customer stickiness:

• More teams using product = harder to leave
• Deeper integration into workflows = higher switching costs
• Multi-department adoption = more champions internally

Predictable growth:

• Strong land-and-expand drives NRR >100%
• Existing base grows in value year-over-year
• Less dependent on new customer acquisition for growth

Key Metrics:

1. Expansion ARR Tracks additional revenue from existing customers

2. Net Revenue Retention (NRR) Measures overall retained and expanded revenue

3. Customer Lifetime Value (CLV) Successful expansion significantly boosts CLV

CSM's Role in Land-and-Expand:

During LAND phase:

• Ensure rapid time-to-value
• Build trust through early wins
• Create foundation for expansion

During EXPAND phase:

• Identify expansion opportunities through usage analysis
• Drive adoption creating demand for more
• Collaborate with Sales on strategic upsells

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Best Practices: Performance Analysis

• Use Growth Accounting to visualize metric changes through inflows and outflows over time
• Conduct cohort analysis tracking customer groups to identify retention patterns and improvement opportunities
• Segment customers by multiple dimensions for tailored engagement strategies
• Analyze all six churn types understanding voluntary vs. involuntary for targeted prevention
• Implement Land-and-Expand model through efficient landing and strategic expansion execution
• Track cohort retention improvements measuring impact of onboarding and engagement changes
• Use behavioral cohorts to understand how usage patterns correlate with retention outcomes
• Provide data-driven Product feedback based on cohort performance and churn analysis insights

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KEY TAKEAWAYS: BEST PRACTICES RECAP

✓ Growth Accounting Formula tracks inflows (New + Expansion ARR) and outflows (Churn + Downgrade ARR) visualizing net change drivers

✓ Customer segmentation tailors engagement by attributes: Enterprise gets QBRs and dedicated CSMs, SMB gets automated check-ins and self-service

✓ Cohort analysis tracks customer groups over time revealing retention patterns and onboarding effectiveness improvements

✓ Six types of churn each require different analysis: Customer, Revenue, Involuntary, Voluntary, Downgrade, Good churn

✓ Voluntary churn provides richest insights for product and CS improvements showing why customers chose to leave

✓ Involuntary churn (payment failures) addressable through billing process improvements like payment method update campaigns

✓ Four actionable churn analysis techniques: Behavioral cohort (engagement), Acquisition cohort (signup timing), Subscription plan (tier performance), Billing interval (monthly vs. annual)

✓ Land-and-Expand model: Land phase (efficient customer acquisition), Expand phase (upselling/cross-selling/wider adoption)

✓ Expansion revenue 3-5x more cost-effective than new acquisition with no CAC and shorter sales cycles

✓ Strong Land-and-Expand drives NRR >100% through existing base growing in value year-over-year

✓ CSM role critical in Expand phase: Identify opportunities, Drive adoption creating demand, Collaborate with Sales on strategic upsells

✓ Cohort retention improvements measure onboarding effectiveness: Q2 cohort 92% vs. Q1 87% shows 5% improvement from new program