D1: Customer Impact

Core Question: How does this problem affect the people who pay us?

Customer impact is often the most visible dimension — and one of the most dangerous when it cascades.

Primary Cascade: Customer → Revenue (70% of cases)

Observable Signals

Don't wait for customers to leave. Look for early warning signals in your systems:

Signal Type	Observable	Data Source	Detection Speed
Immediate	Support ticket spike	Helpdesk (Zendesk, ServiceNow)	Hours
Behavioral	Renewal hesitation	Sales notes, CRM	Days-Weeks
Sentiment	NPS/CSAT score drop	Survey platforms	Weekly
Engagement	Product usage decline	Analytics (Mixpanel, Amplitude)	Days
Escalation	Exec-level complaints	Email, meeting requests	Hours
Silent	Reduced feature adoption	Product analytics	Weeks
Churn	Cancellation requests	Billing/CRM	Immediate
Trust	Reference refusals	Sales team feedback	Variable

Trigger Keywords

Language patterns indicate severity. Train your team to flag these:

High Urgency (Sound = 8-10)

"unacceptable"             "breach of contract"      "legal action"
"canceling"                "considering alternatives" "escalating"
"demand refund"            "not what we signed up for"

Action: Executive escalation within 1 hour.

Medium Urgency (Sound = 4-7)

"disappointed"             "concerned about"         "need clarification"
"frustrating"              "expected better"         "reconsidering"
"will not renew"           "shopping around"

Action: Manager review within 24 hours.

Low Urgency / Early Warning (Sound = 1-3)

"just wondering"           "any updates on"          "is this normal"
"thought it would be"      "not urgent but"          "for future reference"

Action: Track pattern over time.

Metrics

Track both leading (predictive) and lagging (historical) indicators:

Metric Type	Metric Name	Calculation	Target	Alert Threshold
Leading	Support ticket velocity	Tickets/day vs 30-day avg	<120% of baseline	>150%
Leading	NPS trend	Week-over-week delta	Positive or stable	-5 points
Leading	Feature adoption rate	New feature usage %	>30% within 30 days	<15%
Lagging	Customer churn rate	Lost customers / Total	<5% annually	>7%
Lagging	Customer lifetime value	Revenue × Retention period	Increasing	Decreasing
Lagging	Net revenue retention	(Start + Expansion - Churn) / Start	>100%	<95%

Example Dashboard Query

-- Support ticket velocity alert
SELECT
  COUNT(*) as tickets_today,
  AVG(COUNT(*)) OVER (ORDER BY date ROWS BETWEEN 30 PRECEDING AND 1 PRECEDING) as baseline_30d,
  COUNT(*) / AVG(COUNT(*)) OVER (ORDER BY date ROWS BETWEEN 30 PRECEDING AND 1 PRECEDING) as velocity_ratio
FROM support_tickets
WHERE date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY DATE(created_at)
HAVING velocity_ratio > 1.5  -- Alert at 150%

Cascade Pathways

Customer impact multiplies rapidly across other dimensions:

Cascade Probabilities

Cascade Path	Probability	Severity if Occurs
Customer → Revenue	70%	High
Customer → Employee	50%	Medium
Customer → Regulatory	20%	Very High

Why Revenue Cascade is Most Common:

1. Dissatisfied customers don't renew (direct churn)
2. They demand discounts to stay (margin compression)
3. They don't expand/upsell (lost opportunity)
4. They request refunds (negative revenue)

Multiplier Factors

Not all customer issues cascade equally. The multiplier depends on:

Factor	Low (1.5×)	Medium (3×)	High (6×+)
Customer Size	Small account (<$10K ARR)	Mid-market ($10K-$100K)	Enterprise/Strategic (>$100K)
Contract Term	Month-to-month	Annual	Multi-year
Reference Value	Unknown industry presence	Industry peer	Marquee logo, case study customer
Relationship Length	<1 year	1-3 years	>3 years (deep integration)
Expansion Potential	Maxed out	Moderate upsell opportunity	Significant whitespace

Example Calculation

Scenario: Enterprise customer ($250K ARR, 3-year contract, marquee logo, 5-year relationship)

Multiplier factors:
- Customer size: High (6×)
- Contract term: High (6×)
- Reference value: High (6×)
- Relationship length: High (6×)
- Expansion potential: Medium (3×)

Average multiplier: (6 + 6 + 6 + 6 + 3) ÷ 5 = 5.4×

Impact:

• Direct cost of issue: $50K (support hours, fixes)
• Multiplied impact: $50K × 5.4 = $270K
• Plus revenue cascade risk: 70% probability of churn = $250K × 0.7 = $175K
• Total risk: $445K from a $50K problem

3D Scoring (Sound × Space × Time)

Apply the Cormorant Foraging lens to customer dimension:

Lens	Score 1-3	Score 4-6	Score 7-10
Sound (Urgency)	Feedback survey comment	Direct complaint to CSM	Legal threat, exec escalation
Space (Scope)	One customer, one issue	Customer segment (e.g., all enterprise)	Market-wide (competitors know)
Time (Trajectory)	First occurrence, isolated	Recurring pattern over weeks	Accelerating trend, viral

Formula: Dimension Score = (Sound × Space × Time) ÷ 10

Example Scoring

Scenario: Multiple enterprise customers reporting the same bug, complaints escalating to execs, pattern emerging over 3 weeks

Sound = 8 (exec-level complaints)
Space = 7 (segment-wide: all enterprise customers)
Time = 6 (pattern emerging, not yet accelerating)

Customer Impact Score = (8 × 7 × 6) ÷ 10 = 33.6

Interpretation: High urgency (33.6 > 30). Expect significant cascade to Revenue and Employee dimensions.

Detection Strategy

Automated Monitoring

Set up alerts for:

1. Ticket velocity anomaly (>150% of baseline)
2. NPS drop (>5 points week-over-week)
3. Usage decline (>20% drop in key features)
4. High-severity keyword mentions ("cancel", "lawsuit", "unacceptable")

Human Intelligence

Train your CSM/Support teams to:

1. Flag language patterns (use trigger keyword lists)
2. Report sentiment shifts (tone, not just content)
3. Escalate silence (customers going dark is a signal)
4. Track reference refusals (loss of trust indicator)

Real-World Example

The "Reconsidering" Signal:

Observable	Data Point	3D Score
Signal	"We're reconsidering our options" in renewal call	Sound = 6
Context	Enterprise customer ($180K ARR), 2-year relationship	Space = 5
Trend	Third time this quarter they've mentioned it	Time = 7
Score	(6 × 5 × 7) ÷ 10 = 21	Medium urgency

Cascade Prediction:

• 70% probability → Revenue impact ($180K at risk)
• 50% probability → Employee impact (CSM burnout, blame culture)
• Multiplier: 3-4× (relationship length, contract size)

Action Taken:

1. Executive sponsor assigned (within 24 hours)
2. Product roadmap alignment session (within 1 week)
3. Quarterly business review restructured (outcome-focused)
4. Result: Renewed for 3 years, expanded to $250K ARR

Industry Variations

B2B SaaS

• Primary metric: Net Revenue Retention (NRR)
• Key signal: Product usage decline (leading indicator)
• Cascade risk: Customer → Revenue → Operational

Healthcare

• Primary metric: Patient satisfaction (HCAHPS scores)
• Key signal: Readmission rates, complaint volume
• Cascade risk: Customer (Patient) → Regulatory → Revenue

Financial Services

• Primary metric: Assets Under Management (AUM) flows
• Key signal: Relationship tenure, advisor turnover
• Cascade risk: Customer (Client) → Regulatory → Reputation

Next Steps

📊 D2: Employee Impact — How customer issues burn out your team

💰 D3: Revenue Impact — The 70% cascade from customer to revenue

🔄 Cascade Analysis — Map how customer issues multiply

📖 Observable Properties — Complete signal catalog

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Remember: The customer who complains is giving you a chance. The customer who goes silent has already decided. Track both. 🪶