SaaS Pricing Strategy Model
Project-management SaaS · 1,620 customers (1,200 active + 420 churned) · 24-month projection vs. do-nothing baseline
Current State (derived from saas-customers.csv)
At-risk segments
“Dormant” = active customer with days since last login > 30. “Heavy discount” = discount > 10%. “Low adoption” = seats active (30d) < 40% of licensed seats.
Assumption Sliders
Defaults reflect the brief: A raises prices 25% (+0.8pp Starter / +0.4pp Pro churn, −10% new-customer conversion); B adds a usage add-on ($0.40/project over 20 ≈ $22/mo, 35% Pro+Business adoption); C kills Starter → force-migrate to $49 Team (30% migration churn). Churn deltas are added to the monthly churn rate.
24-Month MRR / ARR Projection
Revenue Waterfall (24-month flow)
Side-by-side Comparison
ΔARR = strategy ending ARR − baseline ending ARR. Churned MRR = cumulative MRR lost to churn over 24 months. Blended ARPU = ending MRR ÷ ending customers.
Verdict
Methodology. Starting state is computed live from the embedded CSV: net MRR and customer counts per tier come from active rows; monthly churn rate per tier = (churned ÷ total cohort) ÷ avg tenure (a hazard-to-monthly conversion of the observed cumulative churn). Implied monthly new-customer acquisition = active customers ÷ avg tenure; new-customer ARPU = mean net MRR of signups ≤ 6 months old. Expansion pace = total expansion MRR ÷ total net MRR ÷ avg tenure. Each month the model applies, per tier: +new MRR (acquisition × new-customer ARPU × growth), +expansion (MRR × expansion rate), −churn (MRR × churn rate), −contraction (MRR × 0.4%/mo). Strategy A lifts MRR 25% and ARPU 25% on day 1; B layers add-on MRR (adoption × Pro+Business customers × $22) that grows with new Pro/Business logos; C replaces Starter with a $49 Team tier in month 1 (30% of Starter logos churn, 70% convert to $49) and routes future low-tier acquisition to Team. ARR = ending MRR × 12. No external libraries; charts are inline SVG.