Solution: Health score: 88/100 = Low Risk. ~95% renewal probability. Action: Explore expansion opportunities, gather case study content, maintain engagement.
Result: 88/100 health | Low risk | Expansion opportunity | Standard cadence
Example 3: SMB Warning Signs
Problem: $25K ARR. Usage declining (60%), neutral sponsor, support tickets rising. 4 months to renewal.
Solution: Health score: 58/100 = Medium Risk. ~75% renewal probability. Action: Product training, usage analysis, identify adoption barriers. Address before risk escalates.
Result: 58/100 health | Medium risk | Proactive intervention | Still saveable
Frequently Asked Questions
What is a renewal health score?
A renewal health score combines multiple signals (product usage, NPS, support, relationship, competitive activity) into a single number predicting renewal probability. It enables proactive intervention for at-risk accounts before renewal conversations begin.
How far in advance should I identify renewal risk?
Ideally 6-12 months before renewal for enterprise accounts, 3-6 months for mid-market. This allows time for intervention. Red flags often appear earlierβdeclining usage, champion departure, support spikes.
What are the biggest renewal risk factors?
Top risks: declining product usage, executive sponsor departure, competitive evaluation, budget cuts, merger/acquisition, unresolved support issues, poor onboarding/adoption, and lack of demonstrated ROI.
How do I intervene with at-risk renewals?
Escalate to leadership, schedule executive alignment, conduct value assessment, address specific pain points, offer contract flexibility (payment terms, pricing), and deliver quick wins to rebuild confidence. Tailor intervention to specific risk factors.
Should I offer discounts to save at-risk accounts?
Discounts treat symptom, not disease. If product isn't delivering value, discounting postpones churn. Better: invest in making them successful. That said, strategic pricing adjustments can be part of a broader intervention plan.
What's the difference between churn risk and renewal risk?
Renewal risk is specific to contract renewals (B2B, subscriptions). Churn risk is broader (any customer loss). Renewals are discrete events that can be anticipated and influenced. Churn may happen anytime.
Background & Theory
The Renewal Risk & Health Score Estimator applies the following established principles and formulas.
Health and medicine calculators are grounded in validated physiological measurement methods established through decades of clinical research. Body Mass Index, or BMI, is calculated by dividing weight in kilograms by height in meters squared (kg/mΒ²), a formula originating from Adolphe Quetelet's 19th-century statistical work and later codified by the WHO into standard classifications: underweight below 18.5, normal weight 18.5 to 24.9, overweight 25 to 29.9, and obese at 30 and above.
Basal Metabolic Rate quantifies the minimum energy required to sustain life at rest. The Mifflin-St Jeor equation, published in 1990 and widely regarded as the most accurate for most adults, calculates BMR as (10 Γ weight in kg) + (6.25 Γ height in cm) β (5 Γ age) Β± sex adjustment. The older Harris-Benedict equations, revised in 1984 by Roza and Shizgal, remain in common use. Total Daily Energy Expenditure is derived by multiplying BMR by a physical activity factor ranging from 1.2 for sedentary individuals to 1.9 for extremely active ones, following the methodology validated by doubly labeled water studies.
Body fat percentage can be estimated without laboratory equipment using the U.S. Navy circumference method, which uses neck, waist, and hip measurements, or via BMI-derived equations adjusted for age and sex. The Jackson-Pollock skinfold method offers higher precision with calipers. Blood pressure classification, according to the American College of Cardiology and the 2017 ACC/AHA guidelines, defines normal as below 120/80 mmHg, elevated as 120 to 129 systolic, and hypertension stage 1 as 130 to 139 systolic or 80 to 89 diastolic.
Target heart rate zones for aerobic exercise are derived from maximum heart rate estimates, most commonly using the formula 220 minus age in years, with moderate-intensity training typically defined as 50 to 70 percent of maximum heart rate and vigorous intensity at 70 to 85 percent, consistent with CDC and American Heart Association guidelines. These thresholds guide safe and effective cardiovascular conditioning.
History
The history behind the Renewal Risk & Health Score Estimator traces back through the following developments.
The history of health measurement stretches back to ancient Greece, where Hippocrates around 400 BCE laid the foundation for observational medicine by systematically recording patient symptoms, diet, and environment. His humoral theory, though scientifically superseded, established the principle that the body operates as an interconnected system subject to measurable imbalance.
The transformation toward modern medicine accelerated in the 19th century. Louis Pasteur and Robert Koch developed germ theory in the 1860s and 1870s, identifying microorganisms as disease agents and enabling targeted interventions. Florence Nightingale, working during the Crimean War in the 1850s, introduced statistical analysis to nursing practice, demonstrating through data visualization that sanitation reduced mortality. Her work is foundational to evidence-based health measurement.
The discovery of vitamins in the early 20th century, beginning with Casimir Funk's coinage of the term in 1912 and culminating in the isolation of vitamins A through K, created the field of nutritional science and gave rise to dietary reference intake frameworks. The World Health Organization, founded in 1948, subsequently established global standards for health metrics, disease classification through the International Classification of Diseases, and recommended daily allowances.
The BMI as a clinical screening tool gained traction in the 1970s through Ancel Keys' large-scale epidemiological work, which validated Quetelet's index as a population-level obesity indicator. Through the 1980s and 1990s, the Framingham Heart Study produced landmark data linking cholesterol, blood pressure, and lifestyle factors to cardiovascular disease risk, directly shaping the numeric thresholds still used in health calculators.
The evidence-based medicine movement, formalized by Gordon Guyatt and colleagues at McMaster University in the early 1990s, demanded that all health recommendations derive from systematically graded clinical evidence. The digital health era beginning in the 2000s brought these formulas to consumer devices, wearable sensors, and smartphone applications, expanding access to health self-monitoring on a global scale and enabling population-level data collection that continues to refine clinical reference ranges.
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