Net Promoter Score (NPS)

What it is

Net Promoter Score, NPS, is the single-question customer-loyalty metric introduced by F. R. in 2003 and now standard across B2B service businesses: "How likely are you to recommend this consultant to a colleague, on a scale of zero to ten?" Respondents who answer nine or ten are Promoters, seven or eight are Passives, and zero through six are Detractors; the score itself is the percentage of Promoters minus the percentage of Detractors, producing a number between minus one hundred and plus one hundred. It matters to independent SAP analytics consultants specifically because referrals are the dominant source of new engagements in this market, and NPS is the closest thing available to a leading indicator of referral volume twelve months out.

Why it matters

• Anchor-customer relationships typically produce NPS 70-80 from the anchor itself — a score in that range is itself a signal the relationship has reached anchor status.
• A score below 0 means the consultant generates more detractors than promoters and needs an urgent engagement-quality intervention before the referral pipeline dries up completely.
• The 6-18 month lag between a delivered engagement and the referral materializing is why NPS as a leading indicator matters — waiting for the referral itself is too slow to act on.

Key points

• Single 0-10 question; bucket into Detractors (0-6) · Passives (7-8) · Promoters (9-10).
• NPS = %Promoters − %Detractors; range −100 to +100.
• B2B benchmarks: < 0 critical · 0-30 mediocre · 30-50 good · 50-70 excellent · 70+ rare.
• Top-quartile freelance: 50-70 sustained.
• Predicts referral volume 12 months later at r ≈ 0.55-0.7.
• Closed-loop = the value: Detractor diagnostic call + Promoter referral mining.
• Highest-leverage follow-up: 'Who specifically comes to mind?' on Promoters.
• Trend > absolute; act on 3-engagement trend, not single scores.

Terms used on this page

NPS

Net Promoter Score — single 0-10 likelihood-to-recommend metric. %Promoters − %Detractors.

Detractor

0-6 scorer. Likely to badmouth or churn; diagnostic call within 1 week.

Passive

7-8 scorer. Neutral; ask 'What would make it a 10?'.

Promoter

9-10 scorer. Likely advocate; ask 'Who specifically comes to mind?' for referral mining.

Closed-loop NPS

Discipline of following up with every Detractor (diagnostic) and Promoter (referral mining). Converts metric to revenue.

Rolling-12-month NPS

Portfolio-level NPS computed over the last 12 months of completed engagements. Trend matters more than absolute.

Cultural offset

Systematic NPS difference across cultures (DE typically -1-2 vs FR/Anglo at equivalent quality). Compare within region, not across.

Survivor bias

NPS only captures completed engagements; mid-engagement churns are invisible. Mitigate via separate failure-rate tracking.

Sources

1. Net Promoter System (Bain & Company) — Measuring your Net Promoter Score
2. HBR — The One Number You Need to Grow (F. R., Bain, December 2003 — the origin of the NPS methodology)
3. Qualtrics — What Is Net Promoter Score? (scoring bands, formula, and Bain's benchmark thresholds: >0 good, >20 favorable, >50 excellent, >80 world-class)
4. Bain & Company — Prescription for Cutting Costs (F. R., November 2001 — the retention-economics logic underlying why a loyalty signal predicts growth)
5. Harvard Business Review — Net Promoter 3.0 (Reichheld, Darnell & Burns, 2021; evolution of NPS toward earned growth)
6. Bain & Company — Net Promoter Score (NPS) & System (originator's topic hub: method, definitions and case material)
7. Bain & Company — Introducing the Net Promoter System (Loyalty Insights; how NPS is run as a closed-loop management system)
8. Bain & Company — The value of online customer loyalty and how you can capture it (repeat purchase and referrals as profit drivers)
9. Ipsos — The Net Promoter Debate (interview with T. Keiningham, critical academic view of NPS predictive claims)
10. Harvard Business Review — Don't Underestimate the Power of Customer Referrals (Reichheld, Cleghorn & Kokoszka, Sep-Oct 2026; >10M consumers: ~20% of new customers via referral = 72% of new-customer profit; consumer data, not B2B)
11. Harvard Business Review — Loyalty-Based Management (Reichheld, 1993; choosing the right customers is the foundation of loyalty economics)
12. Harvard Business Review — Understanding Customer Experience (Meyer & Schwager, 2007; customer experience across touchpoints)