How to read this result
The number above is the gross profit you can expect from one customer across their entire relationship with your brand — first purchase, second, fifth, and the last one before they quietly stop. It is not annual revenue. It is not a billing metric. It is the ceiling on what you can rationally pay to acquire that customer.
On its own, the number is hard to grade. A $180 LTV is excellent for a $40 AOV consumable and middling for a $200 AOV one-off purchase. The metric that actually tells you whether the business works is LTV against acquisition cost — so add your CAC above and read the ratio. Below 1:1 you are losing money on every new customer. Between 1:1 and 3:1 you have a business that works but has no slack. At 3:1 or higher, you can keep spending on acquisition without breaking the model.
The LTV formula explained
Every LTV formula multiplies the same three things, with adjustments. Average order value is total revenue divided by the number of orders for the period you are measuring — usually the trailing twelve months. Pull it from your Shopify admin under Orders, or your Klaviyo segment-level metrics if you split by channel. The number you want is post-discount, pre-shipping.
Purchase frequency is how many times the average customer orders in a year. For a one-off DTC brand this is usually between one and three. For supplements or consumables it can be four or higher. For subscription it is often twelve. Frequency is easy to miscount — make sure you are counting orders per customer, not orders per session or per email recipient.
Gross margin is the percentage of revenue left after cost of goods sold. Before marketing, before salaries, before warehouse rent. Most DTC brands land between 50 and 70%; supplements and digital products run higher; apparel and food run lower. If you are guessing, guess low — over-estimating margin is the single most common way LTV gets inflated.
Customer lifespan or retention rateis the hardest input to get right. Lifespan asks “how many years before the average customer goes silent.” Retention asks “what percent of last year's customers buy again this year.” They're algebraically related — retention of 67% implies a lifespan of about three years — but you usually have one or the other observable in your data and not both.
Three ways to calculate LTV — and when to use each
Every calculator on the internet uses one of three formulas, and most of them only show you one. The difference between them is not academic — picking the wrong one for your business overstates or understates the answer enough to drive real budget decisions in the wrong direction.
Simple LTV
AOV × frequency × lifespan. The quickest pass. Useful when you need a number on a slide and don't care about whether the underlying business works. It overstates the answer because it ignores margin, so a brand with 30% margin looks identical to a brand with 70% margin at the same revenue. Use it for top-line storytelling, never for unit economics or ad-spend decisions.
Traditional LTV (margin-adjusted)
Simple LTV × gross margin. The default for most DTC reporting. Adjusts for margin so the answer reflects actual gross profit, not revenue. Use this when your customer lifespan is reasonably observable — a two-year-old brand with established repeat patterns is in good shape here. It still over-rewards aggressive lifespan assumptions, so be honest about how long customers actually stay.
Predictive LTV (retention-based)
(AOV × frequency × margin) ÷ churn rate. The version retention-focused operators use. Instead of guessing a lifespan in years, you measure churn directly — what fraction of customers don't come back — and let the math derive the implied lifespan. This is more honest because churn is observable monthly, where lifespan only crystallizes after years of data. Use this if you have retention numbers from Shopify or your ESP, and especially if your business is subscription or repeat-purchase. It assumes constant churn, which slightly understates lifespan for brands where customers who survive year two are stickier than year-one buyers — but that error is small compared to the error of guessing a lifespan wrong.
DTC industry benchmarks
Use these as sanity checks, not targets. They're drawn from publicly available benchmark studies (Shopify's Commerce Trends reports, Klaviyo's benchmark database, and aggregated DTC operator surveys), and represent typical ranges for brands in the $1M–$50M annual revenue band. Your category, your acquisition mix, and your retention quality can push you outside these bands in either direction. For a deeper breakdown of these numbers — including LTV:CAC by vertical and what public DTC brand data tells us — read What's a good LTV for a DTC brand? 2026 benchmarks by vertical.
| Vertical | Typical AOV | 12-mo LTV | Repeat rate |
|---|---|---|---|
| Skincare & beauty | $40 – $80 | $120 – $240 | 35 – 50% |
| Supplements & wellness | $45 – $90 | $180 – $360 | 45 – 65% |
| Apparel | $60 – $140 | $120 – $320 | 25 – 40% |
| Home goods | $80 – $200 | $140 – $360 | 20 – 35% |
| Food & beverage | $35 – $70 | $110 – $260 | 40 – 60% |
| Subscription boxes | $30 – $60 | $240 – $540 | 60 – 80% |
Ranges synthesized from Shopify Commerce Trends, Klaviyo benchmark studies, and operator surveys, 2022–2024. Treat as directional. Your category and acquisition channel mix will shift these meaningfully.
The pattern that matters more than any single row: subscription and consumable categories produce higher LTV not because they have higher AOV, but because retention is observable and defensible. Apparel and home goods sit at the bottom of this table for the same reason — long replacement cycles and high switching willingness. If your category has structurally low repeat rates, you can either accept lower LTV or build a retention engine that fights the gravity of the category.
Worked example: a skincare brand at $45 AOV
A skincare brand spent two years on Meta and Google ads acquiring customers at $52 CAC. AOV is $45, frequency is 1.8 orders per year, gross margin is 65%, and retention is 55% — meaning a little more than half of last year's customers buy again this year.
At 55% retention, churn is 45%, which implies an average lifespan of about 2.2 years. The traditional LTV calculation comes out to $117: ($45 × 1.8 × 2.22) × 0.65 = $117. The predictive formula gets the same answer for a reason — in the predictive math ($45 × 1.8 × 0.65) ÷ 0.45 = $117 — because when lifespan is derived directly from churn, the two formulas are algebraically identical. The split only matters when you have a measured lifespan that disagrees with your measured churn.
LTV:CAC for this brand is $117 / $52 = 2.25:1. In the warning band. The business is alive, but there's no margin for an ad-platform price hike or a bad month. The founder's instinct is to attack CAC — better creative, tighter targeting. The math says the higher-leverage move is retention. Pushing retention from 55% to 65% (still realistic for skincare with a real win-back program) drops churn from 45% to 35%, which pushes LTV to ($45 × 1.8 × 0.65) ÷ 0.35 = $150, and LTV:CAC to 2.9:1. Doing the same thing on AOV — pushing from $45 to $55 — only moves LTV to $143. Retention is the bigger lever almost every time.
Five common mistakes when calculating LTV
1. Confusing LTV with twelve-month revenue
The number most teams call “LTV” is actually trailing-twelve-month revenue per customer — ARPU. LTV is the full relationship, including the orders that haven't happened yet. The distinction matters because TTM is defensible (you can point at the database) and projected LTV is a model output. Don't hide model assumptions in a number that sounds like it came from a query.
2. Not adjusting for margin
Revenue-LTV is the version executives like because it's the biggest number. Margin-adjusted LTV is the version that tells you what you can pay for acquisition. If you're setting CAC targets off revenue-LTV in a 50% margin business, you're paying twice what the business can actually support.
3. Using the mean instead of the median
LTV distributions are right-skewed in every DTC business we've looked at. A small number of whales pull the mean up — sometimes way up. The median customer's LTV is what your acquisition strategy actually needs to clear. Report both. If they differ by more than 2× you have a heavy-tail problem worth understanding before you spend any more on paid.
4. Using years when your decision cycle is months
A “three-year lifespan” sounds neat. It is also meaningless for a customer who either reorders in 90 days or never reorders at all. Most DTC purchase cycles are short-tail: customers either find their groove in the first two or three orders, or they leave. Model lifespan in months for these brands, not years, and use the predictive formula against measured 30-/60-/90-day churn instead of pretending you know what happens in year three.
5. Ignoring returns, refunds, and chargebacks
In apparel and beauty, returns can erase 10–15% of gross revenue. The LTV math doesn't care unless you subtract a returns reserve from AOV before you start. Skip this step and you'll overpay for acquisition by exactly the amount your fulfillment team is quietly absorbing on the back end.
Frequently asked questions
What is a good LTV for a DTC brand?
There isn't a universal number — it depends on your margin, acquisition cost, and category. The metric to watch is LTV:CAC. Most healthy DTC brands sit at 3:1 or better. A $200 LTV brand with $50 CAC is in a much stronger position than a $500 LTV brand spending $300 to acquire each customer.
What's the difference between LTV and CLV?
Nothing — they're the same metric under two names. Customer Lifetime Value (CLV) and Lifetime Value (LTV) are used interchangeably across e-commerce, subscription, and SaaS. Some teams reserve LTV for revenue and CLV for gross profit, but the convention isn't universal. When in doubt, ask which formula the other person is using.
How is LTV different in subscription vs. one-time-purchase businesses?
Subscription LTV is easier because retention is observable every month — you know whether each customer is still active. For one-time-purchase DTC, you have to infer retention from repeat-order timing. That's why subscription brands report tighter LTV numbers and one-off DTC reports a wider range. The math is the same; the input quality differs.
What's a healthy LTV:CAC ratio?
3:1 is the common rule of thumb — every dollar of CAC produces three dollars of lifetime gross profit. Below 1:1 you are losing money on every customer; between 1:1 and 3:1 you have a narrow business; at 5:1 or higher you may be under-investing in growth. The right ratio depends on your payback period and how patient your capital is.
How often should I recalculate LTV?
Quarterly for strategic planning, monthly if you are actively optimizing acquisition spend. Recalculate any time something major changes — new product line, big price change, channel-mix shift. Avoid recalculating weekly; the noise overwhelms the signal at that cadence for most DTC brands.
Should I use gross LTV or net LTV?
Net — meaning revenue minus returns, refunds, and discounts — for unit-economics decisions. Gross LTV (top-line revenue) flatters the picture and leads to overspending on acquisition. The traditional and predictive formulas above are net of margin but not of returns; subtract a returns reserve (5–15% depending on category) from AOV for the cleanest answer.
How does AOV vs. frequency vs. retention impact LTV most?
Retention has the biggest leverage by a wide margin. Doubling retention more than doubles LTV (the math is asymptotic at the limit). Doubling AOV doubles LTV linearly. Doubling frequency doubles LTV linearly. Most brands obsess about AOV when they should be obsessing about whether the second order ever comes.
Why is my LTV so low (or so high)?
Low LTV usually means weak retention, low frequency, or thin margin — diagnose by changing one input at a time and watching the number move. Unrealistically high LTV usually means using lifespan in years instead of an honest churn-based estimate, or using mean LTV in a heavily skewed customer base where a few whales pull the average up.
Can LTV vary by acquisition channel?
Significantly. Customers from organic search or referral typically have 2–3× the LTV of customers from paid social, even at the same AOV. If you only compute aggregate LTV, you'll keep spending on channels that bring expensive, low-LTV customers. Segment LTV by acquisition source before allocating ad budget.
How do you calculate LTV without a year of data?
Use the predictive formula with an estimated churn rate from a similar business or category benchmark. The number will be directional, not precise. Mark it provisional, recalculate every month as your real cohort data accumulates, and treat the first 12 months of any new business or product line as an LTV estimate, not a measurement.
How RetentionLab uses LTV
This calculator gives you one number for the whole business. It's the right number for board decks and ad budgets, and the wrong number for deciding which customers to send your next campaign to. Every customer has a different expected LTV — some of them are worth investing $50 to keep, and some of them are worth nothing because they were never going to come back regardless.
RetentionLab scores expected LTV at the individual customer level, ranks every customer in your store by churn risk and retention potential, and routes campaigns to the customers actually worth the spend. The calculator above is the starting point. The platform is what comes after.