The standard SaaS LTV formula: Average Revenue Per Account / Monthly Churn Rate. Simple, clean, and for most businesses, significantly overstated.
The formula assumes customers churn suddenly and completely, that they pay the same amount throughout their lifetime, and that the cost to serve them is captured entirely in gross margin. All three assumptions fail in real businesses.
What your LTV calculation is missing:
Contraction. Most LTV models assume customers pay a consistent amount until they churn. In reality, accounts contract — they downsize their plan, reduce seats, or negotiate lower renewal rates over time. The average account that stays for 36 months often pays less in months 25-36 than it did in months 1-12. Ignoring contraction overstates LTV by 15-30% depending on your contraction rate.
CS and support cost to serve. Gross margin backs out COGS but often doesn't fully capture the CS investment in retention. If your enterprise accounts require 15 hours of CSM time per month to retain, and your CSM costs $100/hour fully loaded, that $1,500/month is part of the true cost of that account.
Expansion non-linearity. Standard LTV models that include expansion often apply a uniform expansion rate across all customers. In practice, expansion is concentrated in a subset of accounts. The average expansion rate overstates expected expansion for low-engagement customers.
Survivor bias in historical data. LTV calculations based on historical cohort data include only the customers who actually stayed. The implicit assumption is that new customers will behave like the survivors, not like the full cohort including churned accounts.
Build a cohort-level LTV model using actual revenue trajectory data for complete cohorts (including churned accounts). The number will be lower than your current model. Build toward the real one.