Rough LTV Math for Founders

Lifetime value is total contribution you expect from an average customer over the relationship, after variable costs, before optionally allocating fixed costs. That definition matters because LTV appears in pitch decks as holy number while early founders copy formulas from growth podcasts without owning assumptions. Rough LTV done honestly beats fake precision that greenlights bad ad spend.

Rough LTV is contribution per month times months you actually keep the customer, compared honestly to what it cost to acquire them. Precision can wait. Direction cannot.

Path A: build LTV from contribution and retention evidence

Path A starts with monthly contribution: price minus variable costs per customer including processor, hosting allocation, email, usage APIs, support hours amortized.

Example napkin: price forty-nine dollars, variable costs eight dollars, contribution forty-one dollars monthly. If average customer stays six months, rough LTV contribution equals forty-one times six equals two hundred forty-six dollars before fixed costs. If three months, one hundred twenty-three dollars. Retention assumption dominates. Price alone misleads.

A solo founder selling analytics for food trucks guessed six months retention from validation conversations. Reality after ship: three months. LTV halved. Fixed onboarding instead of buying ads. Napkin saved cash.

Contribution times months retained is LTV building block. Estimate retention from evidence not hope. Early sources: validation asks what tools they stopped using and when, first cohort churn at thirty and ninety days, comparable public case studies weak prior, founder intuition labeled guess until data replaces.

Formula link simplified: monthly churn five percent implies average lifetime roughly twenty months in basic model. Monthly churn ten percent implies ten months. Models lie at edges. Good enough to compare scenarios.

In ARIA running rhythm, update retention assumption monthly once five plus customers exist. Export subscriptions with start and cancel date from processor. Build median lifetime in spreadsheet. Replace guess with median.

B2B LTV and annual contracts: annual payment front-loads cash not LTV automatically. LTV still contribution times expected renewal cycles. Pilot conversion rate affects CAC side.

Consumer LTV tied to habit retention curve. Day thirty active among payers predicts LTV better than day one download.

Net contribution subtract average refund percent. Expansion revenue add conservatively only if upsell shipped and observed. Negative LTV segments: stop marketing even if signup cheap.

LTV sensitivity table: pessimistic churn, base churn, optimistic churn. See range. Decide using pessimistic for spend choices. Customer lifetime rarely exceeds five years for SMB without enterprise pivot. Cap sanity check prevents infinite models.

Path A founder compares LTV contribution to CAC including founder time. CAC includes ads plus acquisition hours valued honestly. Rule thumb bootstrapped: LTV contribution should exceed CAC over reasonable payback window often twelve months max on solo runway. Payback months equals CAC divided by monthly contribution. Payback eighteen months with six month runway means problem clear without spreadsheet art.

When LTV math says do not scale ads: payback longer than runway, LTV pessimistic below CAC, churn rising while spending, contribution negative. Obey napkin. Ego expensive.

When cautious scale ok: stable three-month cohort, contribution positive, CAC logged falling with learning, refund rate low. Scale small batches. Recompute monthly.

Path B: copy industry LTV and defend it emotionally

Path B skips contribution math. Uses revenue not contribution. Assumes infinite retention because hopeful. Ignores founder time in CAC. Uses peak month revenue times random multiplier. Copies competitor LTV from blog post titled how we hit ten million ARR.

Path B produces deck LTV with zero churn assumption. Performance art, not business. Operating LTV with measured churn is business. Path B greenlights ad spend same day vanity signups spike. ROAS one point five sounds good while CAC still above LTV contribution. Compare to contribution not revenue.

Path B blends LTV validation segment with tourist segment. Understates or overstates depending on mix. Computes LTV validation segment only when honest.

Path B treats annual prepay as LTV times twelve automatically. First cycle prepay does not multiply LTV by twelve if churn at renewal high.

Path B skips gates: five customers retained ninety days, LTV pessimistic exceeds CAC, payback under twelve months, scale ad spend twenty percent month over month with weekly CAC log. Skip gates, burn cash.

Path B uses industry average LTV. Your segment, price, onboarding, support define LTV. Industry blog number fiction for you.

Path B ignores support hours in contribution. Support heavy customers may have negative LTV even if price looks fine.

The line we draw is this

Path A is napkin math updated monthly with cohort truth from processor you own. Path B is pitch theater copied from podcasts. ARIA assumes you validate willingness to pay, ship honest scope, run business with weekly reconciliation. That path requires Path A math before scaling acquisition.

Fixed cost allocation optional layer: subtract monthly fixed divided by expected customers for fully loaded view. Workspace, base hosting. Optional early. Mandatory before full-time salary decision maybe. LTV contribution does not subtract workspace unless fully loaded model chosen. Label which LTV version you use in decisions.

Cutting price can raise LTV if buyer marginally fit and retention rises. Raising price can raise LTV if wrong customers leave and support drops. LTV function of price, segment, product, not monotonic price down good. Test carefully. Log cohort by price era.

Overpromise on pricing page lowers effective retention. Honest scope raises realized LTV even if signup count drops.

Monthly LTV review ritual ten minutes: update months retained assumption, recompute contribution if costs changed, compare to CAC trend, one decision scale hold or fix product.

Spreadsheet template columns: customer_id, start_date, monthly_price, monthly_variable_cost, contribution, months_active, ltv_contribution, acquisition_channel, cac_estimate, notes. Copy row monthly from processor.

Churn from small sample caution: three customers one churns equals thirty-three percent monthly churn headline. Too volatile. Wide confidence band until fifteen plus customers.

LTV drives maximum CAC budget: if LTV pessimistic two hundred dollars, max CAC might be one hundred dollars bootstrapped rule half LTV for safety. Adjust risk tolerance consciously.

LTV homework tonight: compute contribution one row, guess retention three scenarios, compute LTV three scenarios, estimate CAC last month including hours, write one sentence decision scale hold fix. Fifteen minutes.

When contribution negative, variable costs exceed price, LTV negative regardless of retention. Fix contribution before retention work.

LTV milestone gates for ads documented above. LTV narrative for yourself: write paragraph explaining assumptions to imaginary skeptical friend. Gaps appear in prose not only cells.

Connection first paying customer: customer one retention months updates guess from theoretical to slightly observed. Do not extrapolate forever from one point.

Connection revenue quality: LTV of validation-segment customer matters. Blended LTV with slop segment misleads.

Connection unit economics article: contribution defined there. LTV uses contribution. Read together.

Founders math club accountability: monthly fifteen minute call with partner update LTV inputs, compare CAC, one decision.

Pre-revenue validate phase ignore LTV except hypothesis. Post first five payers begin rough LTV monthly update.

What to believe instead

Believe rough LTV is contribution per month times months you actually keep the customer, compared honestly to acquisition cost including your time.

Believe Path A napkin updated monthly beats Path B deck precision copied from strangers.

Believe pessimistic scenario should drive spend choices unless strong reason not to.

Believe five customers enough to start rough LTV with wide band. Fifty better. Zero customers means hypothesis only.

Founders who napkin LTV before scaling ads keep bank accounts longer than founders who worship vanity signups. Listen to rude friend math anyway.

Worked LTV example end to end

Price sixty-nine dollars monthly. Variable costs twelve dollars monthly. Contribution fifty-seven dollars monthly. Observed average retention four months early cohort. LTV contribution rough fifty-seven times four equals two hundred twenty-eight dollars.

Founder CAC six hours times sixty dollars hourly equals three hundred sixty dollars per customer if one customer per six hours outreach. LTV below CAC. Actions improve retention to six months, reduce CAC via sharper ICP list, or raise price if validation supports. Math fits one screen. Screen fits napkin.

Payback period formula repeated: CAC divided by monthly contribution equals months to recover acquisition cost ignoring churn. If greater than average lifetime, structural problem not messaging tweak.

LTV when contribution negative: if variable costs exceed price, LTV negative regardless of retention. Fix contribution before retention work. Math order matters like foundation before paint.

LTV and price elasticity rough: if doubling price halves conversions but doubles contribution per customer, LTV may rise or fall depending retention of higher price cohort. Test small batch not public price change for entire list.

LTV milestone gates for ads gate one five customers retained ninety days. Gate two LTV pessimistic exceeds CAC. Gate three payback under twelve months. Gate four scale ad spend twenty percent month over month with weekly CAC log. Skip gates burn cash with impressive top of funnel.

LTV review questions before partner call: what changed assumption since last month? What would kill LTV pessimistic scenario? What product fix moves retention most? Honest answers beat slide fantasy every time.

LTV update calendar invite monthly recurring first Friday fifteen minutes. Treat like minor dental cleaning. Skip twice and assumptions rot. Consistency beats heroic quarterly spreadsheet binge.

Using LTV in support decisions: if support hours per customer high subtract from contribution before LTV. Support heavy customers may have negative LTV even at price that looks healthy on revenue chart alone.

Using LTV in pricing decisions: if LTV low because price low test raise on new customers only. Measure retention impact separately from legacy cohort you grandfathered.

LTV presentation to partner show range not single number. Show assumptions listed. Credibility beats false precision copied from podcast episode you half remember.

Excel not required. Paper napkin sufficient weekly. Spreadsheet when cohorts exceed memory. Processor export plus spreadsheet beats unused analytics suite subscription.

Common founder LTV mistakes catalog: using revenue not contribution, assuming infinite retention because hopeful, ignoring founder time in CAC, using peak month revenue times random multiplier, copying competitor LTV from blog, blending tourist segment with validation segment, treating annual prepay as LTV times twelve automatically.

Monthly LTV review ritual ten minutes update months retained assumption recompute contribution if costs changed compare CAC trend one decision scale hold fix product. Ten minutes monthly cheaper than one panic quarter.

Handoff validate ship run: validate hints price and buyer, ship delivers scope retaining customers, run exports cohort truth into LTV model monthly. Chain breaks if any link skipped.

Founders math club accountability monthly fifteen minute call with partner update LTV inputs compare CAC one decision. External mirror reduces self-deception solo founders cultivate at two in morning.

Pre-revenue validate phase ignore LTV except hypothesis written one sentence. Post first five payers begin rough LTV monthly update even if wide confidence band ugly on paper.

Sensitivity analysis and ad gate detail

Sensitivity chart narrative example pessimistic three months retention LTV one hundred seventy-one dollars base four months two hundred twenty-eight optimistic six months three hundred forty-two spend decisions use pessimistic unless strong reason optimism warranted document reason writing not only gut.

LTV drives maximum CAC budget if LTV pessimistic two hundred dollars max CAC might one hundred dollars bootstrapped rule half LTV safety adjust risk tolerance consciously document risk tolerance paragraph imaginary skeptical friend reads.

Cohort export from processor export subscriptions start date cancel date monthly build median lifetime spreadsheet replace guess retention median five customers noisy fifteen better fifty actionable.

LTV wrong segment pollution compute LTV validation segment only blended LTV tourists understates overstates depending mix marketing message wrong if blended.

LTV annual prepay annual customer LTV contribution twelve months times renewal cycles expected first cycle prepay not multiply LTV twelve automatically churn renewal high cliff year two hurts more than monthly drip churn.

Using LTV pricing decisions LTV low price low test raise new customers only measure retention impact separately legacy cohort grandfathered communicated.

Using LTV support decisions support hours per customer high subtract contribution before LTV support heavy customers negative LTV price looks healthy revenue chart alone.

ROAS ad platform one point five sounds good CAC still above LTV contribution ROAS theater compare contribution not revenue ROAS on revenue while contribution negative is expensive vanity with decimal.

LTV cap realistic customer lifetime rarely exceeds five years SMB without enterprise pivot cap sanity check prevents infinite models investor deck not operating model different documents.

Downgrade contraction tier downgrades exist net revenue retention below gross retention subtract downgrade rate expansion dreams honest modeling beats hockey stick.

Expansion revenue conservative ten percent customers upgrade plus twenty dollars monthly after month three add zero point one times twenty times expected months LTV only upsell shipped observed not roadmap fantasy.

Negative LTV customers some segments destroy value identify segment tag refunds stop marketing segment even signup cheap tourists often negative LTV blended hides them.

LTV homework assignment tonight compute contribution one row guess retention three scenarios compute LTV three scenarios estimate CAC last month write one sentence decision scale hold fix fifteen minutes done beats perfect spreadsheet never opened.

Path A versus Path B recap Path A napkin monthly cohort truth processor own Path B deck theater podcasts Path ARIA assumes validate willingness pay ship honest scope run weekly reconciliation Path A required before scaling acquisition Path B optional for performative foundership not operating foundership choose path with bank account consequences.