Customer lifetime value (LTV) calculator

LTV: the number that decides your entire marketing budget

Customer lifetime value is the most important number in your business, and almost every DTC brand and SaaS company I audit calculates it wrong. The common error: using average order value × expected orders × some guess at gross margin, ignoring retention curves, churn acceleration, and the fact that your best customers behave nothing like your average. A company with a stated $340 LTV often has a $95 10th-percentile LTV and a $1,400 top-decile LTV. The average hides the distribution — and CAC decisions made against the average misfire on either end.

This calculator gives you the clean AOV × frequency × margin × retention formula for a first-cut LTV. Below is the context that turns it into a decision-grade number.

LTV benchmarks by business model

The LTV formula that actually matters

For subscription businesses: LTV = (ARPU × gross margin %) ÷ churn rate. If your ARPU is $40/month, gross margin is 80%, and monthly churn is 4%, LTV = ($40 × 0.80) ÷ 0.04 = $800. This is the classical SaaS formula and it works for any true subscription.

For transactional DTC (non-subscription): LTV = AOV × purchase frequency × gross margin × expected lifespan. A $95 AOV Shopify food brand with 2.3 annual orders, 55% margin, and 2.5-year expected customer lifespan has an LTV of $95 × 2.3 × 0.55 × 2.5 = $300. The weak link: "expected lifespan" is a guess until you have 18–24 months of cohort data.

For hybrid (SaaS with usage add-ons, DTC with subscription opt-in, marketplaces): cohort-based LTV curves are the only honest approach. Compute actual revenue-per-customer at 30, 90, 180, 365, 730 days and project forward. The Cohort LTV tool handles this.

Why average LTV lies to you

In almost every business, customer value follows a Pareto distribution: 20% of customers drive 60–80% of revenue. Using "average LTV" to set CAC tolerance means you overpay to acquire low-value customers and underpay for high-value ones. The cleaner approach:

1. Segment customers into value deciles at 12 and 24 months.
2. Identify the acquisition signals (channel, landing page, first product purchased, demographic) that correlate with top-decile LTV.
3. Bid aggressively on those signals — often 2–3x average CAC — because the LTV justifies it.
4. Bid conservatively on signals that correlate with bottom-decile LTV.

Shopify's own data shows brands using LTV-based bidding (uploading top-customer LAL audiences as value-based Custom Audiences) achieve 30–80% lower CAC on high-LTV cohorts. Meta's Value-Based Lookalike feature leans on this explicitly.

The LTV:CAC ratio everyone quotes and mostly misunderstands

The "3:1 LTV:CAC" rule is a VC heuristic, not a universal truth. It assumes a SaaS-style cost structure with ~75%+ gross margin and ~12-month payback. The honest version:

• SaaS (80%+ gross margin, recurring): 3:1 is healthy, 4:1+ is great, below 2:1 is a problem.
• DTC (40–60% margin, transactional): 3:1 is great, 2:1 is workable if retention is strong.
• Marketplace / low-margin (15–30%): LTV:CAC of 8:1+ is needed just to cover overhead.
• Enterprise SaaS with 120%+ NRR: LTV is understated in most formulas because net expansion compounds. 2:1 at signing can be 4:1 by year 3.

Use the Payback Period tool to stress-test the ratio against cash-flow realities, not just the headline number.

Improving LTV is almost always cheaper than reducing CAC

Most growth teams obsess over reducing CAC. The math of LTV improvement is usually easier:

• Increase AOV through bundling. 10–25% AOV lift is achievable with a proper upsell widget (Rebuy, ReConvert on Shopify). Direct LTV improvement.
• Reduce churn. For SaaS, a 1 percentage-point monthly churn reduction often translates to 25–40% LTV improvement. Customer success investment pays for itself 3–5x.
• Price increases. 10% price increase with acceptable churn usually adds 7–9% to LTV. Review pricing annually.
• Repeat purchase frequency. Loyalty programs, email-driven reorders, subscription opt-ins — all lift frequency without touching acquisition. Use the Loyalty ROI tool to model this.

LTV projection errors to avoid

• Projecting linearly from early data. Month-1 revenue × 12 ≠ year-1 LTV. Retention curves flatten; your month-1 is almost always the highest-value month. Use cohort-based projection.
• Ignoring return/refund rate. A 15% apparel return rate is an effective 15% discount on stated AOV.
• Treating LTV as a fixed number. LTV shifts with offer changes, price changes, product mix. Recompute quarterly.
• Using lifetime revenue instead of lifetime gross profit. CAC is paid from gross profit, not revenue. LTV for CAC decisions must be margin-adjusted.

Three LTV archetypes — real cohort math, full stack cost

LTV benchmarks become actionable when you trace them end-to-end through a specific business. These three archetypes capture ~80% of the companies I consult with.

Archetype 1: DTC replenishment CPG (coffee, supplements, household)

$38 AOV, 58% contribution margin after COGS and fulfillment, 3.1 orders in year one for the average customer. Year-one contribution LTV: $38 × 3.1 × 0.58 = $68. Year-two cohort adds 1.7 additional orders at similar AOV for a $37 marginal contribution. Year-three adds 0.9 orders for $19. 24-month contribution LTV of $124. Top-decile customers (16% of cohort) deliver $385 LTV because they subscribe via Recharge at $19.99 once per 30 days with 93% retention month-over-month. Bottom-decile (one-and-done, 31% of cohort) delivers $22. Stack cost on this model: Shopify at $399/month, Recharge at $60 + 1% of subscription revenue, Klaviyo at $600/month on a 25k-profile list, Gorgias at $300/month. Those costs run maybe $1.80/customer at scale and come out of the 58% contribution margin — factor them in before pricing CAC.

Archetype 2: Self-serve B2C SaaS ($14/month ARPU)

Classic Calm, Duolingo-Plus, or Headway-style consumer app. ARPU of $14 blended (mix of monthly at $14 and annual at $95 / 12 = $7.92), 82% gross margin after Stripe fees, App Store fees, and infrastructure. Monthly churn at 7.5% on monthly plans, 2.1% effective on annual (after considering annual-renewal step-down). Blended LTV formula: $14 × 0.82 / 0.048 = $239. That formula is sensitive — a 1-point churn improvement (from 4.8% to 3.8%) lifts LTV to $302, a 26% gain with zero acquisition effort. The stack: Stripe fees at 2.9% + $0.30, Sentry at $80/month, Mixpanel or Amplitude at $0.93/MAU above the free tier, Braze or OneSignal at $700-$1,800/month for lifecycle messaging. Those infrastructure costs compress gross margin to 76%, dropping real contribution LTV to about $222.

Archetype 3: Mid-market B2B SaaS (ACV $9,200, 94% annual retention, 112% NRR)

ACV $9,200, 82% gross margin, 94% logo retention, 112% net revenue retention via seat expansion and upsell into adjacent SKUs. Naive LTV of $9,200 × 0.82 / 0.06 = $125,700 understates because it ignores NRR compounding. A more honest cohort model: year one contribution $7,540, year two $8,410 (NRR), year three $9,330, tapering as cohort thins. 5-year contribution LTV lands at $42,000 on the median cohort, $88,000 on the top quartile. Stack cost to serve: Salesforce Sales Cloud at $165/user/month (10 seats = $20k/year), HubSpot Service Hub Pro at $800/month, Gainsight or Catalyst at $50k-$120k/year for CS orchestration, Gong at $1,600/user/year for 4 AEs. Loaded to cost-of-serve, net contribution LTV is closer to $31,000 in year 5 on the median cohort — still supports CAC of $9,000-$11,000 at a healthy 3.5:1 ratio.

April 2026 tool pricing that shapes LTV economics

Decision framework: when LTV data is ready to drive CAC decisions

LTV estimates become reliable enough for CAC caps when three conditions hold: (1) you have at least 12 months of cohort data with cohorts of 200+ customers each, (2) the retention curve has visibly flattened in months 9-12 (not still dropping 8%+/month), and (3) your top and bottom deciles differ by less than 6x — if they differ by 10x+, you have two different businesses inside one LTV number and should segment CAC caps by acquisition signal. Before those conditions hold, treat LTV as a directional range, not a hard number: set CAC caps at a conservative 2:1 ratio against the midpoint, and re-examine quarterly. The mistake I see most often in Series-A DTC and SaaS companies is declaring LTV from a single 6-month cohort and setting aggressive CAC caps against it — when the cohort retention curve inevitably flattens differently than projected, the P&L surprises by 30%+.