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Net Promoter Score (NPS) Driver Analyzer

Calculate NPS from customer survey responses and analyze drivers of loyalty with promoter/detractor breakdown.

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Worked Examples

Example 1: SaaS Company NPS Analysis

Problem: SaaS company surveys 100 customers: 40 score 9-10, 35 score 7-8, 25 score 0-6. Calculate NPS and interpret.

Solution: Categorization:\n- Promoters (9-10): 40 customers\n- Passives (7-8): 35 customers\n- Detractors (0-6): 25 customers\n- Total: 100\n\nNPS Calculation:\n- % Promoters: 40/100 = 40%\n- % Detractors: 25/100 = 25%\n- NPS = 40% - 25% = 15\n\nInterpretation:\n- NPS: 15 (needs improvement)\n- Industry average (B2B SaaS): 30-40\n- Status: Below average\n- 40% promoters: Decent loyalty core\n- 35% passives: Large opportunity (convert to promoters)\n- 25% detractors: High churn risk\n\nAction Plan:\n1. Interview detractors (25)—why unhappy?\n2. Focus on passives (35)—small wins to reach 9+\n3. Target: Reduce detractors to 15%, boost promoters to 50%\n4. Potential: If successful, NPS = 50% - 15% = 35 (healthy)

Result: NPS: 15 (needs improvement) | 40% promoters, 35% passives, 25% detractors | Focus on reducing detractors + converting passives

Frequently Asked Questions

What is Net Promoter Score (NPS)?

NPS measures customer loyalty on a -100 to +100 scale. Customers rate 'How likely are you to recommend us?' (0-10). Promoters (9-10) are loyal enthusiasts. Passives (7-8) are satisfied but unenthusiastic. Detractors (0-6) are unhappy and may damage your brand. NPS = % Promoters - % Detractors. Created by Fred Reichheld (Bain, 2003), it's now the standard loyalty metric.

What is a good NPS score?

NPS benchmarks vary by industry. Generally: >70 = World-class (Apple, Tesla), 50-70 = Excellent (Amazon), 30-50 = Good (most successful SaaS), 0-30 = Room for improvement, <0 = Critical (more detractors than promoters). B2B SaaS averages 30-40; B2C retail 40-50. Compare to your industry, not absolute standards.

How do I calculate NPS?

Survey: 'On a scale 0-10, how likely are you to recommend us?' Categorize: 9-10 = Promoter, 7-8 = Passive, 0-6 = Detractor. Calculate: NPS = (# Promoters / # Responses) × 100 - (# Detractors / # Responses) × 100. Example: 100 responses, 50 promoters, 30 passives, 20 detractors. NPS = 50% - 20% = 30.

Why are passives excluded from NPS?

Passives (7-8) are satisfied but not enthusiastic. They won't actively harm you (like detractors) or promote you (like promoters). NPS focuses on extremes: loyalty gap between those who amplify your brand vs those who damage it. Passives are 'neutral'—they could churn with better alternative. Goal: convert passives to promoters through incremental improvements.

What's the difference between NPS and CSAT?

NPS measures loyalty ('Would you recommend?'), CSAT measures satisfaction ('How satisfied are you with [transaction]?'). NPS is relationship metric—overall sentiment. CSAT is transactional—specific interaction. Use both: NPS for strategic health, CSAT for tactical feedback. NPS predicts growth; CSAT identifies issues. Example: Low CSAT on support call (fix process) + High NPS (overall relationship strong).

How often should I measure NPS?

Relationship NPS: Quarterly (track trends, avoid survey fatigue). Transactional NPS: After key interactions (purchase, support, onboarding). B2C: More frequent OK (large customer base). B2B: Less frequent (smaller sample, personal relationships). Annual too infrequent to act on feedback. Monthly may annoy customers. Sweet spot: Quarterly relationship + event-driven transactional.

Background & Theory

The Net Promoter Score (NPS) & Driver Analyzer applies the following established principles and formulas. Break-even analysis identifies the sales volume at which total revenue equals total costs, producing neither profit nor loss. The formula divides total fixed costs by the contribution margin per unit, where contribution margin equals selling price minus variable cost per unit. If a software product has $50,000 in monthly fixed costs and each licence generates $20 above its variable cost, break-even requires 2,500 unit sales per month. Above that threshold, each additional unit contributes directly to profit. Gross margin expresses the percentage of revenue remaining after direct cost of goods sold: gross margin equals revenue minus COGS, divided by revenue. A SaaS company with 80 percent gross margins retains $0.80 of every revenue dollar to cover operating expenses, while a manufacturer with 30 percent gross margins faces much tighter operating leverage. Customer acquisition cost (CAC) divides total sales and marketing expenditure in a period by the number of new customers acquired in that same period. Customer lifetime value (LTV) estimates the total profit attributable to a customer relationship. The standard formula multiplies average revenue per user (ARPU) by gross margin and divides by the monthly churn rate. A business with $50 ARPU, 75 percent gross margin, and 2 percent monthly churn has an LTV of $1,875. The LTV:CAC ratio benchmarks unit economics health; a ratio above 3:1 is generally considered sustainable, while ratios below 1:1 indicate the business is acquiring customers at a loss. Burn rate measures monthly cash expenditure net of revenue. Cash runway equals current cash reserves divided by net monthly burn. A company with $1.2 million in the bank burning $100,000 per month has twelve months of runway. The Rule of 40 is a benchmark for SaaS health: the sum of annual revenue growth rate (as a percentage) and profit margin (as a percentage) should equal or exceed 40. High-growth companies burning cash can still pass this rule if their growth rate compensates.

History

The history behind the Net Promoter Score (NPS) & Driver Analyzer traces back through the following developments. Early economic thought centred on mercantilism, the 16th and 17th century doctrine that national wealth derived from accumulating precious metals through export surpluses and colonial extraction. Adam Smith's "Wealth of Nations" in 1776 dismantled this framework, arguing that genuine prosperity arose from specialisation, division of labour, and freely operating markets. David Ricardo extended Smith's work with the theory of comparative advantage in 1817, demonstrating mathematically that mutually beneficial trade was possible even when one country was less productive in every industry. Alfred Marshall's "Principles of Economics" published in 1890 provided the modern framework of supply and demand curves, consumer surplus, price elasticity, and marginal analysis, establishing neoclassical economics as the dominant academic paradigm for decades. The Great Depression exposed the limits of laissez-faire assumptions, and John Maynard Keynes's "General Theory of Employment, Interest and Money" in 1936 argued that private-sector aggregate demand failures required countercyclical government fiscal intervention to restore full employment, shifting the policy consensus toward active macroeconomic management. The post-World War II decades constructed mixed-economy models combining market allocation with expanded welfare states and Keynesian demand management. Milton Friedman and the Chicago School challenged this consensus from the 1960s onward, championing monetarism and arguing that stable money supply growth was superior to discretionary fiscal policy. Their influence shaped the deregulatory and privatisation policies of the Reagan and Thatcher eras in the 1980s. Behavioural economics emerged through the work of Daniel Kahneman and Amos Tversky in the 1970s and Richard Thaler in the 1980s, using psychology to demonstrate that real human decision-making deviates systematically from rational-actor models through heuristics and biases. The rise of the internet and mobile platforms in the 2000s and 2010s created a new category of platform economics, where network effects, near-zero marginal cost of digital goods, and two-sided market dynamics generated winner-take-most competitive outcomes requiring new analytical frameworks for business valuation.

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