Customer Lifetime Value (LTV) Calculator

What customer lifetime value actually measures (and what most calculators get wrong)

Customer lifetime value, in the form you can actually make decisions with, is the cumulative contribution profit a single acquired customer produces across their active relationship with your brand. It is not revenue. It is not AOV × orders. It is the sum of every margin dollar that customer will generate after COGS, pick-and-pack, shipping, payment fees, and returns — discounted for the fact that most of them churn.

Most LTV "calculators" floating around YouTube and Shopify app marketplaces compute AOV × orders/year × retention years and call it a day. That formula works if you sell toothbrush heads to subscribers. For every other DTC brand it over-states LTV by 40-120% because it ignores three things: (1) the margin component, (2) the cohort decay curve (retention isn't linear), and (3) the time value of the cash.

The calculator above fixes the first two. It takes your contribution margin explicitly, runs retention as a compounding multiplier year-over-year, and plots a cohort curve instead of a single number. You'll see that a customer with 42% YoY retention generates most of their LTV in Years 1-2 — everything after Year 3 is a rounding error. That matters when you're deciding whether a 24-month CAC payback is tolerable.

The formula — plain-English version

For a steady-state, infinite-horizon LTV:

LTV = (AOV × annual orders × gross margin) / (1 − YoY retention)

Worked example: a DTC coffee brand selling at $34 AOV, 4.2 orders/year, 62% contribution margin, 48% YoY retention. Year-one contribution is $34 × 4.2 × 0.62 = $88.54. Steady-state LTV is $88.54 / (1 − 0.48) = $170.27. That's what you can afford to lose on first-order CAC — before even deciding what payback window you're willing to finance.

For a 3-year cohort LTV (what most boards actually want to see):

LTV₃ = Y1 + Y1×r + Y1×r² where r is YoY retention.

Same coffee brand, 3-year cohort: $88.54 + $42.50 + $20.40 = $151.44. Six months later when retention ticks up to 55%, re-run the math and the 3-year number jumps to $175. This is why LTV is a living metric, not a one-time number on a pitch deck.

Category benchmarks (3-year contribution LTV, DTC operators, 2025-2026)

• Apparel / fashion: $180-$420 — highly seasonal, 35-45% Y2 retention, relies on drops and collabs to compound.
• Beauty / skincare: $220-$650 — consumable replenishment drives retention; brands like Glossier reportedly hit ~$600 3Y LTV on core skincare routines.
• Supplements / wellness: $280-$900 — subscription-heavy; Ritual, Athletic Greens, Seed run at the top of the range thanks to 60%+ subscription retention at month 12.
• Home goods: $140-$380 — purchase frequency is the killer (furniture is 1 order every 3-5 years; kitchen consumables more like 2-3/yr).
• Food, beverage, snack: $200-$480 — Dollar Shave Club and Magic Spoon style categories; subscription fixes the frequency problem but caps AOV.
• Pet: $350-$1,200 — Chewy famously hits ~$1,100 lifetime in a category where 90%+ of spend is consumable (food, litter, meds).

These ranges are pulled from public filings (Allbirds S-1, Warby Parker S-1, Honest Co S-1), DTC operator surveys (Common Thread Collective 2025, Triple Whale state-of-ecom), and our own merchant sample. They are directional, not gospel. Your mileage will vary by AOV, margin, and post-purchase program.

Why cohort LTV matters more than a single number

A "$240 LTV" brand and a "$240 LTV" brand can have completely different P&Ls. Consider two coffee brands:

• Brand A: Y1 contribution $160, 30% retention. 3-year LTV = $160 + $48 + $14 = $222. Front-loaded.
• Brand B: Y1 contribution $70, 75% retention. 3-year LTV = $70 + $52 + $39 = $161. Back-loaded — and it keeps compounding past Y3.

At a 12-month CAC payback constraint, Brand A can spend $160 to acquire; Brand B is capped at $70. Same "LTV story" on a slide; completely different ad budgets. The calculator above plots the cohort curve so you can actually see the difference.

How retention actually decays (and why the flat-line assumption is dangerous)

In real cohorts, retention follows a shifted-beta-geometric distribution — the first-time-to-repeat hurdle is steep, then the survivors flatten out. Most brands see Y1 to Y2 retention of 30-45%, Y2 to Y3 of 60-70%, and Y3 to Y4 approaching 80% of the surviving cohort. So a simple "YoY retention = 42%" assumption over-penalizes your long-term LTV.

In practice: measure YoY retention from your own Shopify or Klaviyo cohort report, plug the Y1→Y2 number into this calculator, and know that the "steady-state LTV" output is conservative. If your brand has strong repeat dynamics past Y2, your real lifetime number is 10-25% higher than what's shown.

Using LTV to set max CAC (the only reason you care about this number)

LTV is worthless as a vanity metric. It earns its keep when it tells you what you can pay to acquire. Three rules:

• CAC payback ≤ 12 months: Max paid CAC = Y1 contribution profit. Safest; works for bootstrapped brands without debt.
• LTV:CAC ratio of 3:1 at 3-year LTV: Max paid CAC = LTV₃ / 3. This is the SaaS-style benchmark DTC borrowed. Works if you have 18-24 months of capital to float payback.
• Blended CAC (paid + organic): Mix paid and organic at your true channel split. A brand with 50% organic orders can afford 2x the paid CAC of a brand that pays for every visitor.

Run the paid CAC number through our customer acquisition cost calculator to sanity-check against what Meta and Google are actually charging you. If your LTV says you can pay $82 per customer and your paid CAC is $117, you don't have an LTV problem — you have a media efficiency problem.

Levers that actually move LTV (in rank order of impact)

1. Repeat frequency (30-50% LTV lift): Post-purchase email/SMS (Klaviyo flows: browse abandonment, 30-day reorder reminder, winback at 90/180 days). Real numbers: Klaviyo benchmark for welcome flow revenue-per-recipient is $3.20-$6.80, post-purchase $1.80-$4.10. A 15% lift in Y1 orders compounds into 18-22% lifetime lift.
2. AOV expansion (15-30% LTV lift): Bundles, free-shipping thresholds (see our free shipping threshold tool), post-cart upsells via ReConvert/AfterSell. Lift AOV from $52 to $68 and LTV moves in lockstep — no retention assumption required.
3. Contribution margin (direct): Every margin point is an LTV point. Renegotiate freight, consolidate packaging SKUs, switch to a lower-fee processor, audit the packaging cost line.
4. Subscription conversion (60-200% LTV lift in enrolled customers): ReCharge / Skio / Yotpo Subscriptions. Athletic Greens and Ritual built $100M+ businesses entirely on this lever.
5. Churn reduction (slow compounding lift): Best products for high churn categories are win-back flows and concierge CX. Moves 3-5 points of retention, which compounds meaningfully at Year 3+.

LTV and returns — the hidden margin killer

If your apparel brand has a 22% return rate, every $100 of gross revenue is really $78 of recognizable revenue — and the reverse logistics (return shipping, inspection, restock, often a partial refund) typically cost 18-35% of order value on returned items. Shove your return rate into our return rate impact calculator first, solve for the net AOV, and then re-run LTV. Most apparel brands over-state LTV by 15-25% simply by using gross AOV instead of net.

Common LTV mistakes DTC operators make

• Using revenue, not contribution: "We have $420 LTV" is meaningless without a margin number attached. It's like bragging about top-line revenue with a -10% net margin.
• Averaging across segments: Subscribers and one-time buyers have 4-8x different LTV. Your "blended" $180 LTV is a $42 one-time buyer averaged with a $480 subscriber, and that blended number doesn't help you set bid strategy.
• Over-projecting retention: Assuming flat retention past Year 1 inflates 5-year LTV by 30-60%. Use actual cohort data whenever you have it.
• Ignoring payback: $220 3-year LTV at 36-month payback is worthless if you're paying cash on cash for ad spend with a 12-month runway. Always pair LTV with a payback curve.
• Not re-running quarterly: LTV drifts. Margin compression, platform fee hikes (Meta CPMs jumped ~30% Q4 2024-Q1 2025), changing product mix all move the number. Re-compute every 90 days.

What this calculator does not account for

No LTV tool can capture (a) discount rates for time value of money — we treat cash tomorrow the same as cash today; (b) non-linear retention shapes — we assume flat YoY; (c) referral halo effects (your best LTV customers refer 2-3x more); (d) cross-sell into new categories as you expand SKU count. All four push real LTV higher than the headline, so consider this calculator a conservative floor.

Three brand LTV cohort walkthroughs

The cleanest way to internalize LTV math is to walk three cohorts across 36 months.

Cohort 1 — DTC beauty brand, consumable routine. $58 AOV, 3.2 orders/yr, 56% contribution margin, Y1→Y2 retention 48%, Y2→Y3 retention 68% (surviving cohort flattens). Y1 contribution per customer = $58 × 3.2 × 0.56 = $104. Y2 contribution (48% survive, repeat at same pattern): $50. Y3 (32.6% survive): $34. 3-year LTV: $188. Payback on $45 CAC = 5.2 months. Ratio 4.2x — healthy. Steady-state projection (including Y4+): $217.

Cohort 2 — Apparel brand, seasonal. $88 AOV, 1.8 orders/yr, 48% contribution margin, Y1→Y2 retention 32%, Y2→Y3 retention 58%. Y1 contribution = $88 × 1.8 × 0.48 = $76. Y2 = $24. Y3 = $14. 3-year LTV: $114. Payback on $58 CAC = 9.1 months. Ratio 1.97x — marginal. Steady-state adds only $4 due to low retention. Action: focus on getting Y1 orders from 1.8 to 2.4 via better post-purchase flows (direct 33% LTV lift) before scaling acquisition.

Cohort 3 — Supplement brand, subscription-first. $44 AOV, subscribers 8.2 orders/yr (avg), subscription retention 62% Y1→Y2, 78% Y2→Y3. Mix: 40% of first-order buyers subscribe. Subscriber Y1 contribution = $44 × 8.2 × 0.58 = $209. Non-subscriber Y1 contribution = $44 × 1.6 × 0.58 = $41. Blended Y1 = 0.4 × $209 + 0.6 × $41 = $108. Y2 blended (subscribers 62% retain, non-subs 20%): $71. Y3: $51. 3-year blended: $230. Subscriber-only 3-year: $420. Payback on $52 CAC = 5.8 months blended; 3 months for subscriber cohort. Lever: move subscription-attach-rate from 40% to 55% lifts blended LTV to $275 with zero CAC change.

Retention decay curves — what each category actually looks like

Built from public filings, Klaviyo cohort benchmarks, and operator audits. All are Y1→Y2 retention:

• Apparel / fashion: 28-42%. Basics brands hit 50%+; trend/seasonal brands 20-30%. Drops and collabs compound retention.
• Beauty / skincare (routine-driven): 42-62%. Glossier reportedly 55%+; newer indie brands 40%.
• Supplements (non-subscription): 35-52%.
• Supplements (subscription): 55-72% measured on subscribers only.
• Food / beverage (subscription): 48-68%. Magic Spoon, Athletic Greens reportedly 60%+.
• Food / beverage (one-time): 38-55%.
• Pet (consumable): 55-72%. Chewy reportedly 65%+ blended.
• Home / furniture (durable): 12-22%. Low by design; purchase cycle 3-5 years.
• Home / kitchen consumables: 35-48%.
• Consumer electronics / accessories: 18-32%.
• B2B / wholesale: 60-85%. Churn is slow and asymmetric.
• Subscription box: 25-45% at month 12. See subscription box pricing tool.
• SaaS (for contrast): 80-93% annual; completely different economics.

The five LTV levers — worked example lift

Concrete deltas on the apparel cohort above (baseline 3-year LTV $114):

• Lever 1: Y1 orders from 1.8 → 2.4 (via post-purchase flows). Y1 contribution $76 → $101. 3-year LTV: $151. +33%.
• Lever 2: AOV from $88 → $105 (via bundle / free-ship threshold). Y1 contribution → $91. 3-year LTV: $136. +19%.
• Lever 3: Contribution margin 48% → 54% (freight renegotiation, packaging SKU consolidation). Y1 → $85. 3-year LTV: $127. +11%.
• Lever 4: Retention Y1→Y2 32% → 42% (better winback, reorder reminders). 3-year LTV: $142. +25%.
• Lever 5: Add subscription for 25% of buyers at 3.8 orders/yr. Subscriber cohort Y1 contribution jumps to $154. Blended 3-year: $158. +39%.
• Stack 1+2+4 together: 3-year LTV: $214. +88%. Realistic 12-month improvement roadmap.

Predicted LTV tooling — what actually works in April 2026

• Shopify Predicted LTV (native): Black-box ML on your cohort. Uses gross revenue. Directional but under-sampled on early cohorts. Free.
• Klaviyo Predicted LTV & churn risk: Strong for segmentation (trigger winback when predicted churn crosses threshold). Updates nightly. Free with Klaviyo.
• Triple Whale cohort reports: Good time-based cohort visualization. $129-$999/mo.
• Cohort Analysis in Looker Studio / Metabase: DIY. Pull raw Shopify orders, group by acquisition month, plot cumulative revenue. Most accurate if you have the data skill.
• Lifetimely: Shopify app, $49-$349/mo. Good packaging of cohort + LTV + subscription mix.
• Peel Insights: Shopify-native analytics, LTV/CAC view, $149-$999/mo.
• Custom BTYD model (Buy Till You Die): Academic model (Bruce Hardie, Peter Fader). Python implementation is 40 lines. Best theoretical fit for pre-subscription DTC. Requires analyst.

Decision framework — setting max CAC from LTV

Three patience windows, three CAC caps. Use the one that matches your capital reality:

• Bootstrapped (cash-flow constrained): Max paid CAC = 6-month contribution profit. For the beauty cohort above: max CAC = $52. Safest.
• Credit-line backed (12-18% APR): Max paid CAC = 12-month contribution profit. Max CAC = $104 for beauty cohort.
• Equity-backed (18-24 month patience): Max paid CAC = LTV / 3. Max CAC = $63 for beauty cohort (conservative) or Y2 cumulative = $154 for aggressive scale.
• Growth-equity (24-36 month): Max paid CAC = LTV / 2 if cohort retention is proven. Max CAC = $94 on the beauty cohort.

Key rule: if your realized paid CAC is above your window-cap, you're not growing — you're liquidating enterprise value to acquire customers.

Frequently asked (operator edition)

How do I LTV-adjust when 30% of my customers come from referrals? Assign zero acquisition cost to referral customers; their contribution goes directly into LTV. But count them separately when setting paid CAC — never average paid-acquired with referral-acquired for media-planning purposes.

Does LTV include Amazon customers? Separate bucket. Amazon customers don't enter your email list (Amazon blocks it), have different purchase frequency, and aren't yours to retain. Model Amazon LTV independently. See Amazon FBA fees.

Should I discount LTV for the time value of money? Yes if you're making financing decisions. Use a 10-15% annual discount rate on future contribution. For most DTC operational decisions, undiscounted is fine and 20-30% more conservative anyway due to churn under-forecasting.

What counts as the "start" of a cohort — first site visit, first order, or first paid conversion? First order, always. Site visit cohorts are for CRO; order cohorts are for LTV.

How do I compute LTV for a brand-new category expansion? Use your existing brand's retention curve as a proxy, adjust AOV and frequency for the new category. Don't assume perfect carryover — new categories have higher churn in Year 1.

Does email signup contribute to LTV? Indirectly — email-driven revenue is part of contribution. But an email-only signup (no purchase) isn't a customer and shouldn't be in the LTV denominator.

Do I count Year 4+ contribution in "3-year LTV"? No — be explicit about the window. Report both 3Y and steady-state. Investors often want 3Y (testable with data); operators care about steady-state (planning horizon).

How does promotion and discounting affect LTV? Each promo-acquired customer has 15-30% lower Y2 retention than a full-price acquired customer (Klaviyo aggregated data). Discount-trained customers abandon when promos stop. Factor into both AOV (lower) and retention (lower) for discount-heavy acquisition.

Is LTV different by acquisition channel? Yes, sometimes dramatically. Klaviyo-acquired customers typically have 1.5-2.2x the LTV of Meta-acquired. Organic / referral 2-3x. Always analyze LTV by first-touch channel when setting channel-specific CAC caps.

Related calculators

LTV is one pillar of unit economics. Pair this with CAC, repeat purchase rate, and subscription churn to build out the full picture.