![[Case Study] NPS® is much more sensitive than Customer Satisfaction](/_astro/nps-sensitivity-case-study-e1638779666853.DmSBgNIL.jpg)
Customer satisfaction surveys often show stable scores while churn quietly climbs — and most teams can't explain the gap. nib health funds' data, analysed properly, shows NPS is roughly three times more sensitive at predicting churn than CSAT, and Detractors are 1.5 times more likely to leave than Promoters. Here's the analysis.
Strip away the CRM jargon and customer loyalty management comes down to two things — listening to customers and remembering what they told you. That sounds trivial. The Reichheld research on why most companies still fail at it isn't. Here's what to actually remember, and why it matters more than the tooling.
Customer loyalty programs need regular check-ups the same way an exotic sports car does — both are temperamental and both quietly stop running well long before they fail spectacularly. Here are five quick checks to run on your loyalty program now, from "is it still mechanically sound" to the one that matters most: is it still fun to be in?
Trigger-based marketing can lift conversions to 45% and cut DM costs by 35% — and most teams freeze before they start because of six predictable objections. Data isn't good enough. Whole-of-customer view is too hard. Customers will feel watched. Here are the six road-blocks, all six demolished, so you can stop using them as reasons not to start.
Charity donations, magazine subscriptions, event re-attendance, mail-order purchases — non-contract, discrete-transaction relationships are everywhere, and the standard CLV formula doesn't fit them well. Here's the Fader-Hardie model for that quadrant translated into actionable steps, with the data you need and how to use the resulting customer-value forecasts.
Fader and Hardie's CLV models are well known in marketing academia and largely ignored in marketing practice — partly because the source papers are dense, partly because nobody distils the actionable steps. Here they are for retail and other non-contract continuous-purchase customer bases — what data you need, the assumptions to check, and how to use the results.