"My executive team wants LTV in our monthly report. But there are like four different formulas online — how do I pick the right one?" This is one of the most common questions we hear from EC operators. LTV (Customer Lifetime Value) is widely used as a metric, but at least five common calculation methods exist. Pick the wrong one, and your business decisions rest on a shaky foundation. There are five common LTV calculation methods: Simple, Gross Margin, Cohort, LTV/CAC, and DCF. Choose by business stage and product LTV alone cannot drive investment decisions. View it together with CAC, with LTV/CAC = 3:1 as a baseline The three prerequisite metrics are AOV, RPS, and purchase frequency. Without stable measurement of these, LTV figures lack foundation LTV looks deceptively simple. The textbook formula is: LTV = AOV × Purchase Frequency × Customer Lifespan But ask any operator running a real Shopify store, and you'll get a different number depending on what they include — gross margin, cohort retention, CAC, future cash flow discount. These produce different LTVs by 2-3x for the same business. The question is not "which formula is correct" but "which formula fits this stage of the business." LTV = AOV × Purchase Frequency × Customer Lifespan The simplest formula, also presented in Shopify's official documentation. AOV ¥5,000 × 3 orders/year × 2 years = LTV ¥30,000. Sufficient when gross margin and customer ID linkage aren't yet structured. Note: revenue-based, so margin differences are not reflected. LTV = (AOV × Gross Margin) × Orders × Years Once you start serious ad investment, profit-based LTV is essential. Otherwise you hit the "LTV looks fine but no profit" trap. With 30% gross margin: ¥9,000 gross-margin LTV. Translation: keep CAC under ¥9,000. LTV = Cohort cumulative revenue ÷ Cohort customers Highest accuracy because it's based on observed values. Customer ID linkage is mandatory. Bain & Company has long noted that retention improvements have outsized impact on profit, and cohort-level visibility directly drives continuous improvement. LTV/CAC = LTV ÷ CAC (baseline: 3:1) Strictly speaking, this is not a formula for calculating LTV — it's an investment-decision lens using the LTV/CAC ratio. The four formulas for LTV calculation proper are 1, 2, 3, and 5 here. The "LTV/CAC = 3:1" baseline widely used in SaaS also applies to EC. Below 1 = unprofitable acquisition, above 3 = room to scale spending. The appropriate ratio varies by industry and product, so use your own channel-level actuals. LTV = Σ(Annual CF / (1 + r)^n) Discounts future cash flows to present value. Used for subscription EC and high-AOV products in 3-5-year investment decisions. Discount rate (typically 5-10%) heavily influences output, so document your assumptions explicitly. All five methods share a common assumption: that AOV and purchase frequency are already being measured stably. Without that foundation, LTV figures lack reliability. The three prerequisite metrics: Metric Unit Role Relationship to LTV AOV per order Order efficiency Starting point of LTV formula RPS per session Revenue per visit Acquisition efficiency that creates LTV CAC per customer Acquisition cost Denominator of LTV/CAC ratio In practice: build a state where AOV and RPS are measured monthly with stability, then compute LTV quarterly. There's no need to view LTV daily — but AOV and RPS should be visible every day. LTV/CAC ratio State Recommended action Below 1 New acquisition is loss-making Pause ads, or improve product first 1-2 Recoverable but thin margin Decompose by channel, cut high-CAC channels 2-3 Healthy range Maintain + improve AOV/CVR to lift the ratio Above 3 Room to scale spending Increase ad budget, open new channels Critical caveat: this baseline must be viewed at channel and cohort level. Even if total LTV/CAC = 3, if Paid sits at 0.8 and Organic at 5.0, the right call is to pause Paid acquisition. Averages mislead. Pitfall What happens Treatment One-time customers Single-purchase customers drag down the average Split "first purchase only" vs "repeat" Fixed measurement period Fixing lifespan to 3 years undervalues new customers Use observed lifespan months by cohort Pre/post discount mixing Heavy coupon usage inflates AOV Match AOV practice — use post-discount Channel allocation Mixing ad-acquired with Organic customers Split cohorts by initial-touch channel The summary: LTV has five common calculation methods. Choose by business stage and product LTV alone does not enable investment decisions. Use LTV/CAC = 3:1 as the baseline The three prerequisite metrics are AOV / RPS / Purchase Frequency Realistic operation: LTV quarterly, AOV and RPS visible daily Decompose LTV/CAC by channel and cohort — averages mislead I'm building RevenueScope, a tool that automatically expands the prerequisite metrics — AOV, RPS, CVR — by channel and device on the dashboard. It doesn't compute LTV directly, but it's designed to surface "the data foundation underneath LTV" — the kind of view that's missing when teams jump straight to LTV reporting. What LTV formula does your team currently use, and what tripped you up the first time? Curious to hear from other operators — especially the "looked good in the spreadsheet but didn't survive contact with reality" stories.