Customer Health Score Calculator

A health score is a weighted index that compresses several account signals into one number on a 0 to 100 scale so that a portfolio of customers can be triaged rather than treated uniformly. The weighting used here gives 30 percent to engagement, built from logins per month capped at 20 and the share of features in use, 20 percent to recency of last login, 15 percent to support ticket volume, 20 percent to a normalised satisfaction rating, and 15 percent to expansion growth, with a tenure multiplier between 0.95 and 1.10 that discounts accounts under six months old and rewards those past two years. Support is scored as an inverted U rather than a straight line: one to two tickets a month scores highest, while zero is penalised because silence often means abandonment rather than mastery. Scores above 80 are read as healthy, 60 to 79 as neutral, 40 to 59 as at risk, and below 40 as critical, with those bands mapped to indicative churn probabilities and multiplied by annual contract value to express exposure in currency. The important caveat is that the weights are a starting template, not a finding. Predictive weights should be fitted to a company's own outcomes, typically by logistic regression on twelve to twenty-four months of renewal and cancellation records, and recalibrated as the product changes. Churn is a rare event, so naive models trained on imbalanced data tend to predict retention for everyone and still look accurate. A single satisfaction response reflects one individual at one moment and can move independently of account-level reality. Score direction is usually more informative than score level, and a drop of fifteen points inside a week deserves attention even when the absolute value is still comfortable.

Scoring customers by observable behaviour began in direct marketing well before software. Catalogue and mail-order firms ranked their house lists using recency, frequency and monetary value, a scheme refined and widely taught during the 1990s through practitioners such as Arthur Hughes, and the logic transferred cleanly to subscriptions: how lately, how often, and how much a customer engages predicts whether they will engage again. The satisfaction component has a more precise origin. Fred Reichheld introduced the Net Promoter Score in a 2003 Harvard Business Review article developed with Bain and Company and Satmetrix, proposing a single likelihood-to-recommend question as a proxy for loyalty; his earlier 1990 work with W. Earl Sasser on defections had already argued that small retention improvements produce disproportionate profit gains. The composite health score as software teams now use it emerged with the customer success function in the mid-2000s, when subscription vendors realised that renewal, not the initial sale, determined enterprise value and staffed dedicated teams to protect it. Specialist tooling followed: Totango was founded in 2010 and Gainsight took its current name in 2013 after starting as JBara Software, and both shipped configurable health scores that pulled product telemetry, support systems and survey data into one dashboard. The method has since moved from hand-set weights toward models fitted on historical churn, though most production implementations remain deliberately simple so that customer success managers can explain to an account why its score moved.