Calculating LTV for SaaS: The Formula, the Math, and the Mistakes

Cal­cu­lat­ing LTV for SaaS sounds sim­ple — and that’s exact­ly why most CEOs get it wrong. The text­book for­mu­la is one line. The hon­est ver­sion requires gross mar­gin, seg­men­ta­tion, and a churn rate that com­pounds the way real cus­tomers behave. The gap between the text­book num­ber and the hon­est num­ber is usu­al­ly 2–3x. That gap is the dif­fer­ence between a board deck that holds up under scruti­ny and one that does­n’t.

This guide walks through the math the way you’d actu­al­ly use it inside a $5M–$15M ARR SaaS busi­ness — not as an aca­d­e­m­ic exer­cise. You’ll get the for­mu­la, a worked exam­ple at real­is­tic num­bers, the five mis­takes that inflate the result, and the seg­men­ta­tion approach that turns LTV from a van­i­ty met­ric into a deci­sion tool.

What LTV Means in SaaS (and Why the Simple Definition Is Misleading)

Life­time val­ue (LTV) is the total gross prof­it a sin­gle cus­tomer is expect­ed to deliv­er over the time they stay sub­scribed. In SaaS, “life­time” is not a num­ber you observe — it’s a num­ber you derive from your churn rate. That dis­tinc­tion mat­ters because every input is an esti­mate, and small esti­ma­tion errors com­pound into large LTV errors.

You’ll also see the met­ric writ­ten as CLV (Cus­tomer Life­time Val­ue) or CLTV. They all mean the same thing. SaaS finance teams and investors default to LTV, so that’s the con­ven­tion used here.

The rea­son LTV exists as a met­ric in the first place is that SaaS eco­nom­ics don’t fit a tra­di­tion­al prof­it-and-loss view. When you spend $10,000 to acquire a cus­tomer who pays $500 per month, you can’t ask “did that cus­tomer make us mon­ey this month?” The answer is always no for the first sev­er­al months. The right ques­tion is “did that cus­tomer make us mon­ey over the time they stayed?” — and to answer that, you need LTV.

LTV is half of the equa­tion that defines whether a SaaS busi­ness can scale. The oth­er half is CAC (Cus­tomer Acqui­si­tion Cost). The ratio of the two — cov­ered in depth in our LTV/CAC guide — is the sin­gle most impor­tant num­ber for eval­u­at­ing unit eco­nom­ics. But you can’t trust the ratio if the LTV in the numer­a­tor is wrong, which is why the cal­cu­la­tion itself deserves the care­ful walk­through below.

The Formula for Calculating LTV in SaaS

Three for­mu­las mat­ter. They’re list­ed below from sim­plest to most hon­est. Use the third one for any num­ber that will appear in a board deck or investor mod­el.

Formula 1: The Quick Formula (Use for Back-of-Envelope Only)

LTV = ARPA / Month­ly Churn Rate

Where:

• ARPA = Aver­age Rev­enue Per Account (month­ly, in dol­lars)
• Month­ly Churn Rate = the per­cent­age of cus­tomers (or rev­enue) you lose each month, expressed as a dec­i­mal

Exam­ple: $500 ARPA ÷ 2% month­ly churn (0.02) = $25,000 LTV.

This is the for­mu­la most blogs lead with. It’s wrong in one impor­tant way — it ignores gross mar­gin, so it treats every dol­lar of rev­enue as a dol­lar of prof­it. For a SaaS com­pa­ny at 75% gross mar­gin, this over­states LTV by 33%.

Formula 2: The Gross-Margin-Adjusted Formula (Use for Internal Decisions)

LTV = (ARPA × Gross Mar­gin %) / Month­ly Churn Rate

Same inputs, plus:

• Gross Mar­gin % = (Rev­enue − COGS) / Rev­enue, expressed as a dec­i­mal

Exam­ple: $500 ARPA × 0.75 gross mar­gin ÷ 0.02 month­ly churn = $18,750 LTV.

This is the ver­sion the cus­tomer life­time val­ue guide on saasceo.com walks through in detail. It’s the right for­mu­la for most inter­nal analy­ses — board report­ing, chan­nel ROI deci­sions, sales-team pay­back cal­cu­la­tions.

Formula 3: The Honest Formula (Use for Investor and M&A Math)

LTV = ARPA × Gross Mar­gin % × Aver­age Cus­tomer Lifes­pan

Where:

• Aver­age Cus­tomer Lifes­pan = 1 / Month­ly Churn Rate, expressed in months

Exam­ple: $500 ARPA × 0.75 gross mar­gin × (1 / 0.02 = 50 months) = $18,750 LTV.

Math­e­mat­i­cal­ly this is iden­ti­cal to For­mu­la 2 — the lifes­pan term is just the inverse of churn. But writ­ing it this way makes the implic­it assump­tion vis­i­ble: you’re mod­el­ing a cus­tomer who pays the same ARPA every month for exact­ly 1 / churn months, then leaves. That’s a sim­pli­fi­ca­tion of real­i­ty. The real cus­tomer base has a long tail of high-val­ue retain­ers and a fat ear­ly-can­cel­la­tion dis­tri­b­u­tion. Sophis­ti­cat­ed investors will dis­count the head­line LTV when they sus­pect the under­ly­ing dis­tri­b­u­tion.

Use For­mu­la 3 when you need to talk through the assump­tion set with a CFO, an audi­tor, or a strate­gic acquir­er. Use For­mu­la 2 for every­one else.

A Worked Example: LTV at $5M ARR

Let’s cal­cu­late LTV for a real­is­tic mid-stage SaaS com­pa­ny. The num­bers are the kind you’d see in a typ­i­cal $5M ARR B2B SaaS at the $5M–$15M ARR stage.

The Inputs

Input	Value	Source
Total customers	1,000	Active subscriptions at end of month
MRR (Monthly Recurring Revenue)	$416,667	$5M ARR ÷ 12
ARPA (Average Revenue Per Account)	$417	$416,667 MRR ÷ 1,000 customers (rounded)
Gross margin	78%	After hosting, support, third-party APIs, DevOps
Customers lost in the month	18	From cancellations
Monthly customer churn rate	1.8%	18 ÷ 1,000 = 0.018

The Calculation

Plug those into For­mu­la 2:

LTV = ($417 × 0.78) / 0.018 = $325.26 / 0.018 = $18,070

Let’s ver­i­fy that with For­mu­la 3:

• ARPA × Gross Mar­gin = $417 × 0.78 = $325.26 of gross prof­it per cus­tomer per month
• Aver­age Cus­tomer Lifes­pan = 1 / 0.018 = 55.56 months (about 4.6 years)
• LTV = $325.26 × 55.56 = $18,070

Same num­ber. That’s the LTV.

What This Number Actually Means

This cus­tomer is worth rough­ly $18,000 in gross prof­it over their expect­ed tenure. If you’re spend­ing more than ~$6,000 to acquire them, you’re in trou­ble (that would be a 3.0× LTV/CAC ratio — the text­book min­i­mum). If you’re spend­ing $4,000 or less, you’re in good shape (4.5× or bet­ter).

Notice what this num­ber does NOT tell you:

• It does­n’t tell you when that $18,070 arrives. Most of it comes in years 2 through 5.
• It does­n’t tell you whether this cus­tomer is rep­re­sen­ta­tive. The 1,000-customer aver­age hides huge seg­ment vari­ance.
• It does­n’t account for expan­sion. If your cus­tomers expand at 10% net rev­enue reten­tion per year, the real LTV is mean­ing­ful­ly high­er.

Those gaps are exact­ly what the next three sec­tions address.

Where Each Input Actually Comes From

The for­mu­la is easy. Get­ting clean inputs is the hard part. Here’s how to source each num­ber with­out fool­ing your­self.

ARPA: Revenue ÷ Customers (Choose the Denominator Carefully)

ARPA is just total recur­ring rev­enue divid­ed by the count of cus­tomers pay­ing it. The trap is the denom­i­na­tor.

If you count every account that touched your sys­tem this month — includ­ing 14-day tri­als, paused accounts, and free-tier users — your cus­tomer count bal­loons and ARPA col­laps­es. If you only count ful­ly paid annu­al con­tracts, you might exclude month­ly cus­tomers entire­ly.

The right denom­i­na­tor is the count of accounts pay­ing recur­ring rev­enue at the end of the mea­sure­ment peri­od. Tri­als don’t count until they con­vert. Free accounts don’t count at all. Paused accounts count only if they’re con­tract­ed to resume.

The numer­a­tor should be recur­ring rev­enue only. Strip out one-time imple­men­ta­tion fees, pro­fes­sion­al ser­vices charges, and any expan­sion that has­n’t yet hit recur­ring billing. Mix­ing these in inflates ARPA in the ear­ly months and makes LTV look bet­ter than it is.

Gross Margin: Subtract True Cost of Revenue Only

SaaS gross mar­gin should sit between 70% and 85% for a healthy busi­ness. If yours is below 60%, you have a ser­vice-heavy mod­el mas­querad­ing as SaaS — your LTV cal­cu­la­tion should reflect that.

What goes into COGS for SaaS:

• Host­ing and infra­struc­ture (AWS, GCP, Azure)
• Direct cus­tomer sup­port staff (not sales-aligned cus­tomer suc­cess)
• Third-par­ty APIs and soft­ware costs embed­ded in the prod­uct
• Site reli­a­bil­i­ty and on-call DevOps

What does NOT go into COGS:

• R&D and engi­neer­ing pay­roll
• Sales and mar­ket­ing
• Gen­er­al and admin­is­tra­tive over­head
• Cus­tomer suc­cess roles that dri­ve expan­sion (those are S&M)

The most com­mon mis­take here is over-count­ing COGS by stuff­ing cus­tomer suc­cess into it. CS that dri­ves expan­sion is acqui­si­tion expense; CS that resolves tick­ets is COGS. Split your CS head­count between the two before you com­pute gross mar­gin.

Monthly Churn Rate: Use Customer Churn or Revenue Churn (Be Explicit)

Churn comes in two fla­vors, and they often pro­duce dif­fer­ent num­bers:

Type	Formula	When to Use
Customer churn (logo churn)	Customers Lost / Starting Customers	LTV for the average customer
Revenue churn (gross MRR churn)	Churned MRR / Starting MRR	LTV weighted by customer size

If your cus­tomer mix is uni­form — most accounts pay rough­ly the same ARPA — the two num­bers will be close. If you have a long tail of small accounts that churn fast while large accounts retain, rev­enue churn will be low­er than cus­tomer churn, and using rev­enue churn pro­duces a high­er (and more accu­rate) LTV.

The hon­est default is to cal­cu­late both and report them side by side. Pick one for the head­line LTV num­ber, but dis­close the oth­er so the read­er knows what they’re look­ing at.

Average Customer Lifespan: Trust the Math, Then Sanity-Check It

The for­mu­la says lifes­pan = 1 / month­ly churn. At 2% month­ly churn, that’s 50 months. At 1% month­ly churn, it’s 100 months. At 5% month­ly churn, it’s 20 months.

This math is cor­rect in expec­ta­tion, but only if churn is steady-state. If your cohort reten­tion curve drops sharply in months 1–3 and then flat­tens, the for­mu­la over­states LTV — because the for­mu­la assumes uni­form month­ly churn while the real­i­ty is that ear­ly churn­ers exit first and the remain­ing cohort churns more slow­ly.

The san­i­ty check: look at the actu­al reten­tion of your old­est cohort. If a cohort that signed up 36 months ago still has 50% of its orig­i­nal cus­tomers active, your “aver­age lifes­pan” cal­cu­la­tion should pro­duce some­thing close to that obser­va­tion. If the math says 80 months but you’ve nev­er seen any­one stay longer than 30, your churn rate is being aver­aged over too short a win­dow.

Segmented LTV: Why the Blended Number Is Almost Always Wrong

The sin­gle biggest mis­take in cal­cu­lat­ing LTV for SaaS is com­put­ing one num­ber for the whole com­pa­ny. 100% of the time, there are sig­nif­i­cant vari­ances between cus­tomer seg­ments — and the blend­ed num­ber hides them.

Here’s why it mat­ters: a blend­ed LTV of $18,000 sounds healthy. But if your enter­prise seg­ment has an LTV of $80,000 and your SMB seg­ment has an LTV of $3,000, you don’t have an $18,000 cus­tomer base. You have two com­plete­ly dif­fer­ent busi­ness­es shar­ing a P&L. One of them is a unit-eco­nom­ics pow­er­house; the oth­er might be los­ing mon­ey on every acqui­si­tion. The blend­ed num­ber tells you noth­ing about which is which — and worse, it gives the SMB seg­ment cov­er to keep burn­ing cash.

The Segments That Matter Most

For a $5M–$15M ARR B2B SaaS, seg­ment LTV by at least these dimen­sions:

• Con­tract size tier (SMB under $5K ACV, mid-mar­ket $5K–$25K, enter­prise $25K+)
• Indus­try ver­ti­cal (each ver­ti­cal has its own churn dynam­ics)
• Acqui­si­tion chan­nel (inbound vs. out­bound vs. part­ner vs. paid)
• Con­tract term length (month-to-month vs. annu­al vs. mul­ti-year)
• Geog­ra­phy (if you sell inter­na­tion­al­ly, region­al churn varies)

You won’t always have clean data for all five. Start with con­tract size tier and acqui­si­tion chan­nel — those almost always pro­duce the largest vari­ance and are usu­al­ly track­able in CRM data with­out new instru­men­ta­tion.

Worked Example: Same Company, Two Segments

Same $5M ARR busi­ness, bro­ken into two seg­ments. The blend­ed num­bers from the pri­or exam­ple come from this exact mix — 800 SMB accounts at $200 ARPA plus 200 enter­prise accounts at $1,283 ARPA pro­duces $416,600 in MRR and the same 1.8% blend­ed month­ly churn (800 × 2.0% + 200 × 1.0% = 18 cus­tomers lost).

Segment	Customers	ARPA	Gross Margin	Monthly Churn	LTV
SMB	800	$200	75%	2.0%	$7,500
Enterprise	200	$1,283	80%	1.0%	$102,640
Blended	1,000	$417	78%	1.8%	$18,070

Math check on the seg­ments:

• SMB: $200 × 0.75 / 0.02 = $150 / 0.02 = $7,500 ✓
• Enter­prise: $1,283 × 0.80 / 0.01 = $1,026 / 0.01 = $102,640 ✓

Now imag­ine you have a $4,000 CAC. Against the blend­ed LTV of $18,070, you’re at a 4.5× LTV/CAC ratio. Looks great.

Against the seg­ments:

• SMB: $7,500 LTV / $4,000 CAC = 1.88× — below the 3.0× min­i­mum; once you account for opex above the gross mar­gin line, this seg­ment is like­ly los­ing mon­ey
• Enter­prise: $102,640 LTV / $4,000 CAC = 25.7× — extra­or­di­nary, and a clear sig­nal you’re under-invest­ing in enter­prise acqui­si­tion

The blend­ed ratio hides the truth: your enter­prise seg­ment is sub­si­diz­ing a mar­gin­al-at-best SMB acqui­si­tion motion. The deci­sion the seg­ment­ed view enables — “cut the SMB top-of-fun­nel spend, raise SMB pric­ing, or dou­ble-down on enter­prise” — is invis­i­ble when you only look at the blend­ed num­ber.

You can nev­er out­grow bad unit eco­nom­ics. The seg­ment that’s bro­ken stays bro­ken regard­less of how much the strong seg­ment grows. Cal­cu­lat­ing LTV at the seg­ment lev­el is the first step to fix­ing it.

The Five Most Common Mistakes in Calculating LTV for SaaS

These are the mis­takes that show up most often in client board decks. Each one inflates LTV by 20–100%. Togeth­er they can pro­duce a num­ber 3× high­er than real­i­ty.

Mistake 1: Forgetting Gross Margin

The most com­mon error. Using ARPA / churn instead of (ARPA × Gross Mar­gin) / churn. At 75% gross mar­gin this over­states LTV by 33%. At 65% gross mar­gin it over­states by 54%.

Fix: Always include gross mar­gin. There is no defen­si­ble rea­son to omit it.

Mistake 2: Using Annual Churn × 12 Logic

If your month­ly churn is 2%, your annu­al churn is NOT 24%. It’s 21.5%, because churn com­pounds:

Annu­al Churn = 1 − (1 − Month­ly Churn)^12

• 2% month­ly → 21.5% annu­al (NOT 24%)
• 5% month­ly → 46.0% annu­al (NOT 60%)
• 10% month­ly → 71.8% annu­al (NOT 120%)

The arith­metic-vs-com­pound dif­fer­ence mat­ters because some ana­lysts back into LTV from “annu­al” churn fig­ures, then divide annu­al ARR by annu­al churn. If they mul­ti­plied month­ly × 12 to get there, their lifes­pan esti­mate is biased low and LTV ends up under­stat­ed. If they took observed annu­al cohort attri­tion (the cor­rect method) and treat­ed it as if it com­pound­ed month­ly, LTV ends up over­stat­ed. Either way the answer is wrong.

Fix: Com­pute LTV from month­ly ARPA and month­ly churn. If you need to con­vert between month­ly and annu­al churn, use the com­pound for­mu­la above. Nev­er mul­ti­ply or divide by 12 to switch peri­ods.

Mistake 3: Counting Trials, Pauses, or Free Users as Customers

If your cus­tomer count includes 200 tri­al accounts that will con­vert at 25%, your ARPA gets dilut­ed by 200 × 0 / total. That col­laps­es LTV. Con­verse­ly, if you exclude pay­ing month-to-month cus­tomers because “they’re not real annu­al con­tracts,” you over­state ARPA.

Fix: Define “cus­tomer” as an account pay­ing recur­ring rev­enue at the mea­sure­ment-peri­od close. Apply the same def­i­n­i­tion every­where — to ARPA, to churn, to the head­count in your seg­ment break­downs.

Mistake 4: Calculating Once and Trusting It Forever

LTV is not a fixed prop­er­ty of your busi­ness. It changes month to month as your cus­tomer mix, churn rate, ARPA, and gross mar­gin move. A com­pa­ny that cal­cu­lat­ed LTV at $20K in 2024 and did­n’t recal­cu­late in 2025 is mak­ing 2025 deci­sions on a 2024 num­ber.

Fix: Recal­cu­late at least quar­ter­ly, ide­al­ly month­ly. Track the trend, not just the snap­shot. The direc­tion LTV is mov­ing mat­ters as much as the cur­rent val­ue.

Mistake 5: Ignoring Expansion Revenue

The basic LTV for­mu­la assumes a cus­tomer pays the same ARPA every month for their entire tenure. In a healthy SaaS busi­ness, ARPA grows for retained cus­tomers through seat addi­tions, upgrades, and cross-sells. That expan­sion is real LTV and the for­mu­la miss­es it.

Fix: If your net rev­enue reten­tion is above 100%, your true LTV is high­er than the basic for­mu­la sug­gests. For most inter­nal deci­sions, the con­ser­v­a­tive basic LTV is fine — you’re bet­ter off being pleas­ant­ly sur­prised. For investor and M&A con­ver­sa­tions, mod­el the expan­sion explic­it­ly:

Expan­sion-Adjust­ed LTV = Basic LTV × (1 + Annu­al Expan­sion Rate / 2)

Use half the annu­al expan­sion rate as a rough adjust­ment that accounts for the fact that expan­sion does­n’t all hap­pen in year one. A more rig­or­ous mod­el uses a cohort reten­tion curve with expan­sion lay­ered on top — overkill for most com­pa­nies but stan­dard for top-quar­tile met­rics report­ing.

How to Use Your LTV Number Once You Have It

LTV in iso­la­tion is inter­est­ing. LTV paired with the right com­par­i­son is deci­sive.

The LTV/CAC Ratio (The Number That Matters Most)

LTV/CAC = LTV ÷ Cus­tomer Acqui­si­tion Cost

This is the unit-eco­nom­ics head­line. The bench­marks:

LTV/CAC Ratio	Interpretation
< 1.0×	Losing money on every customer — fix immediately
1.0–2.0×	Marginal — may not cover operating expenses
3.0×	Industry benchmark — healthy unit economics
3.0–5.0×	Strong — efficient growth engine
> 5.0×	Possibly under-investing in growth

If you’re above 5×, the answer isn’t “cel­e­brate.” The answer is “spend more on growth until the ratio com­press­es to 3–4×.” You’re leav­ing com­pound­ing rev­enue on the table.

If you’re below 3×, the answer isn’t “spend less on sales.” The answer is to fig­ure out which lever is bro­ken — LTV (reten­tion, expan­sion, gross mar­gin) or CAC (sales effi­cien­cy, chan­nel mix, con­ver­sion rate) — and fix it before increas­ing invest­ment.

CAC Payback Period (The Cash-Flow Companion)

CAC Pay­back = CAC / (ARPA × Gross Mar­gin %)

This tells you how many months it takes to recov­er what you spent acquir­ing a cus­tomer. The bench­marks:

Payback Period	Interpretation
< 12 months	Excellent — fast capital recycle
12–18 months	Good — typical for healthy SaaS
18–24 months	Acceptable if retention is strong
> 24 months	Concerning — capital-intensive growth

LTV/CAC tells you whether the math works long-term. CAC pay­back tells you whether you have the cash to wait. A $5M ARR com­pa­ny with a 36-month pay­back can’t fund growth out of oper­a­tions — you need out­side cap­i­tal just to keep the engine run­ning.

What to Do When LTV/CAC Is Below 3×

The temp­ta­tion is to cut sales spend. The right move is to diag­nose which input is weak­est:

• Low ARPA? Test pric­ing increas­es on new logos. Pric­ing pow­er is the most under­uti­lized lever in SaaS.
• High month­ly churn? Make reten­tion the com­pa­ny’s annu­al pri­or­i­ty — get it from 5% to 2.5% and watch LTV dou­ble.
• Low gross mar­gin? Audit host­ing costs and sup­port staffing. SaaS gross mar­gin should sit above 70%.
• High CAC? Seg­ment by acqui­si­tion chan­nel. Inbound and part­ner-sourced CAC is usu­al­ly 50–70% low­er than out­bound. Reweight toward the effi­cient chan­nels.

Each of these moves takes 6–12 months to ful­ly reflect in the LTV/CAC ratio. The recal­cu­la­tion dis­ci­pline from Mis­take 4 is what tells you whether the moves are work­ing.

How Calculating LTV Changes by Company Stage

The right lev­el of pre­ci­sion depends on where you are. A $1M ARR start­up does­n’t need cohort-mod­eled expan­sion-adjust­ed LTV; a $50M ARR com­pa­ny at the edge of an exit can’t ship with­out it.

Stage	LTV Approach	What to Avoid
< $1M ARR	Quick formula (ARPA / churn). Update quarterly.	Don't waste cycles segmenting — you don't have the data
$1M–$5M ARR	Gross-margin-adjusted (Formula 2). Segment by acquisition channel.	Don't trust the blended number — segment as soon as you can
$5M–$15M ARR	Formula 2, segmented by contract size + channel + vertical. Recalculate monthly.	Don't ignore expansion — start tracking NRR
$15M–$50M ARR	Formula 3 with expansion adjustment. Cohort retention curves.	Don't ship investor decks without the assumption set documented
$50M+ ARR	Full cohort-modeled LTV with cohort-specific churn and expansion.	Don't rely on a single methodology — back-test against actual observed lifetime gross profit

The $5M–$15M ARR band is where most CEOs first real­ize their blend­ed LTV has been hid­ing deci­sions for years. If you’re in that band, the high­est-lever­age ana­lyt­ics work you can do this quar­ter is seg­ment­ed LTV by con­tract tier and acqui­si­tion chan­nel. The first time you run it, the num­bers will sur­prise you. That sur­prise is the entire point of the exer­cise.

Frequently Asked Questions

What is the sim­plest for­mu­la for cal­cu­lat­ing LTV for SaaS?

The sim­plest defen­si­ble for­mu­la is LTV = (ARPA × Gross Mar­gin %) / Month­ly Churn Rate. ARPA is month­ly recur­ring rev­enue per account. Gross mar­gin accounts for the cost of deliv­er­ing the ser­vice. Month­ly churn is the per­cent­age of cus­tomers (or rev­enue) you lose each month. The quick for­mu­la that omits gross mar­gin (ARPA / churn) over­states LTV by 25–40% depend­ing on your mar­gin and should­n’t be used for any deci­sion more con­se­quen­tial than an ear­ly-stage back-of-enve­lope san­i­ty check.

What is a good LTV in SaaS?

LTV in absolute terms is only mean­ing­ful rel­a­tive to CAC. A $5,000 LTV is excel­lent if CAC is $1,000 and ter­ri­ble if CAC is $6,000. The bench­mark to tar­get is an LTV/CAC ratio of 3.0× or high­er. Top-quar­tile B2B SaaS com­pa­nies hit 4.0× to 6.0×, accord­ing to recent indus­try bench­marks report­ed by Besse­mer Ven­ture Part­ners.

How is SaaS LTV dif­fer­ent from e‑commerce LTV?

E‑commerce LTV mod­els dis­crete repeat pur­chas­es over a long hori­zon — you pre­dict how many times a cus­tomer will come back and what they’ll spend. SaaS LTV mod­els con­tin­u­ous month­ly rev­enue with churn as the exit con­di­tion — you pre­dict how long they’ll stay and what they’ll pay each month. The SaaS for­mu­la uses ARPA and churn; the e‑commerce for­mu­la uses pur­chase fre­quen­cy and aver­age order val­ue. They’re both life­time val­ue cal­cu­la­tions, but the inputs and the time dynam­ics are fun­da­men­tal­ly dif­fer­ent.

Should I use cus­tomer churn or rev­enue churn for LTV?

Use the one that match­es the ques­tion you’re answer­ing. For “what is the aver­age cus­tomer worth,” use cus­tomer churn. For “what is a dol­lar of MRR worth,” use rev­enue churn. If you have a mix of small and large accounts that churn at dif­fer­ent rates, the two num­bers will diverge — cal­cu­late both and report them side by side. The hon­est default is to lead with rev­enue churn for any exter­nal report­ing because it weights the cal­cu­la­tion by ARPA.

How does net rev­enue reten­tion affect LTV?

NRR above 100% means exist­ing cus­tomers expand their spend faster than the com­pa­ny los­es rev­enue to churn and con­trac­tion. The basic LTV for­mu­la assumes flat ARPA and miss­es this expan­sion entire­ly. For inter­nal deci­sions, leave LTV con­ser­v­a­tive (basic for­mu­la) and track NRR sep­a­rate­ly. For investor or M&A con­ver­sa­tions, mod­el the expan­sion explic­it­ly using cohort reten­tion curves — the net rev­enue reten­tion guide on saasceo.com walks through how to set those up.

How often should I recal­cu­late LTV?

Month­ly for the blend­ed num­ber, quar­ter­ly for the full seg­ment­ed break­down. The trend mat­ters as much as the snap­shot. LTV that’s flat or ris­ing while CAC drops is the strongest pos­si­ble sig­nal of com­pound­ing unit eco­nom­ics. LTV that’s falling while CAC ris­es is the ear­li­est warn­ing of trou­ble — usu­al­ly vis­i­ble 6–12 months before it shows up in growth rate or burn rate.

Why is seg­ment­ed LTV more use­ful than blend­ed LTV?

Blend­ed LTV aver­ages out the vari­ance between seg­ments that have com­plete­ly dif­fer­ent unit eco­nom­ics. A com­pa­ny with an excel­lent enter­prise seg­ment and a mon­ey-los­ing SMB seg­ment may show a healthy blend­ed LTV/CAC ratio while bleed­ing cash on every SMB cus­tomer. Seg­ment­ing by con­tract tier, acqui­si­tion chan­nel, and ver­ti­cal reveals which parts of the busi­ness are actu­al­ly work­ing — and which deci­sions (reweight chan­nel spend, sun­set a seg­ment, raise prices in a tier) the blend­ed num­ber hides.