How to Calculate True Customer Lifetime Value (And Why Most Stores Get It Wrong)
Customer Lifetime Value (LTV) is the most important metric in e-commerce. It determines how much you can spend on acquisition, which marketing channels are profitable, and whether your business is truly sustainable. But here's the problem: most Shopify stores calculate LTV completely wrong. They use simplified formulas that ignore critical factors, leading to wildly inaccurate numbers that destroy decision-making. Let's fix that.
The Common LTV Mistakes (That Kill Profitability)
Before we get to the right way, let's understand why most LTV calculations are broken:
Mistake 1: The "Average Order Value × Number of Orders" Trap
The formula: LTV = AOV × Average Number of Orders
The problem: This ignores the time value of money, acquisition costs, and the fact that customers churn. A customer who spends $1,000 over 5 years is not as valuable as a customer who spends $1,000 in 6 months—but this formula treats them identically.
The damage: You overestimate LTV, overspend on acquisition, and wonder why you're unprofitable despite "good" metrics.
Mistake 2: Using Total Revenue Instead of Gross Profit
The problem: LTV should be based on gross profit (revenue minus COGS), not total revenue. If you're calculating LTV on revenue but spending acquisition dollars against profit, your economics are completely broken.
Example: A customer generates $500 in revenue with 40% gross margin. Their actual LTV contribution is $200, not $500. If you spend $300 to acquire them thinking LTV is $500, you're losing $100 per customer while believing you're profitable.
Mistake 3: Not Segmenting by Cohort or Channel
The problem: Using a single "average LTV" number for all customers ignores massive variation. Facebook ad customers might have 30% lower LTV than organic customers. Q4 cohorts might have different behavior than Q2 cohorts.
The damage: You allocate marketing budget based on averages, which means you're overspending on low-LTV channels and underspending on high-LTV channels.
Mistake 4: Ignoring Customer Churn
The problem: Many formulas assume customers keep buying forever at the same rate. In reality, customers churn. Your LTV calculation must account for the probability that customers stop buying.
The damage: You think you have $500 LTV customers, but 60% churn after the first purchase. Your actual LTV is dramatically lower.
The Pattern
Most LTV calculations are simplistic shortcuts that produce numbers, but not insights. They're easy to calculate, but they destroy decision-making. True LTV requires accounting for margins, time, churn, and segmentation. Anything less is guessing.
The Right Way to Calculate LTV: Three Approaches
There isn't one perfect LTV formula—the right approach depends on your business model and data sophistication. Here are three methods, from simple to advanced:
Method 1: Simple LTV (For New Stores)
If you don't have much historical data, start here:
LTV = (Average Order Value × Purchase Frequency × Gross Margin) / Churn RateWhere:
- Average Order Value = Total revenue / Number of orders (last 12 months)
- Purchase Frequency = Number of orders / Number of unique customers (last 12 months)
- Gross Margin = (Revenue - COGS) / Revenue (as decimal)
- Churn Rate = Customers who didn't repurchase in expected timeframe / Total customers
Example: AOV = $75, Purchase Frequency = 2.5 orders/year, Gross Margin = 45%, Churn Rate = 40%
LTV = ($75 × 2.5 × 0.45) / 0.40 = $210.94
Method 2: Cohort-Based LTV (For Growing Stores)
Once you have 6-12 months of data, calculate LTV by cohort:
Step 1: Group customers by acquisition month (cohort)
Step 2: Track total gross profit generated by each cohort over time
Step 3: Calculate cumulative gross profit per customer at different time intervals (30 days, 60 days, 90 days, 180 days, 365 days)
Step 4: Average cohort LTV curves to project future value
Why it's better: Cohort-based LTV accounts for the fact that different acquisition periods perform differently. Your Q4 holiday customers might have lower LTV than Q2 customers. This method reveals that.
Example Cohort Progression:
Month 0 (acquisition): $60 gross profit per customer
Month 3: $105 cumulative
Month 6: $140 cumulative
Month 12: $190 cumulative
Projected 24-month LTV: $240
Method 3: Predictive LTV (For Mature Stores)
The most accurate method uses machine learning to predict individual customer LTV based on behavioral signals:
- First order value and timing
- Second order timing (strong predictor)
- Product category preferences
- Engagement behavior (email opens, site visits)
- Discount sensitivity
- Purchase sequence patterns
Why it's better: Predictive LTV gives you a probability distribution of future value for each customer. You don't just know average LTV—you know that Customer A has an 80% chance of $300+ LTV while Customer B has a 60% chance of churning after one purchase.
The catch: This requires significant data and ML expertise. Most stores can't build this themselves—which is where platforms like Lumino come in.
The Critical Elements Every LTV Calculation Must Include
Regardless of which method you use, your LTV calculation must account for these factors:
1. Use Gross Profit, Not Revenue
Always calculate LTV based on gross profit (revenue minus COGS, shipping, payment processing). This is what's available to cover acquisition costs and operating expenses. Using revenue will make you think customers are more valuable than they actually are.
2. Account for Time
A dollar today is worth more than a dollar next year. If you're calculating multi-year LTV, apply a discount rate (typically 10-15% annually) to account for the time value of money and business risk.
3. Segment by Acquisition Channel
Never use a single average LTV. Calculate separate LTV for each acquisition channel (organic, paid search, paid social, email, referral). This reveals which channels bring high-value customers vs. one-time buyers.
4. Include Churn Probability
Not all customers keep buying forever. Your LTV calculation must factor in the probability of churn at each time interval. This is why cohort-based or predictive methods are superior—they inherently account for churn.
5. Update Regularly
LTV isn't static. As your product mix changes, as you acquire different customer types, as market conditions shift—LTV changes. Recalculate monthly or quarterly, not once and forget.
How to Use LTV to Make Better Decisions
Accurate LTV unlocks better decision-making across your entire business:
1. Set Acquisition Budgets
The golden rule: Customer Acquisition Cost (CAC) should be ≤ 1/3 of LTV for sustainable growth. If your LTV is $210, you can profitably spend up to $70 on acquisition. Spend more, and you're bleeding cash. Spend less, and you're leaving growth on the table.
2. Prioritize Channels
If Facebook customers have $150 LTV but Google customers have $250 LTV, you should allocate budget accordingly. Most stores optimize for CAC alone—big mistake. Optimize for LTV-to-CAC ratio.
3. Segment Retention Efforts
High-LTV customers deserve more retention investment than low-LTV customers. If you know a customer has $400 predicted LTV, spending $50 on retention makes sense. For a $80 predicted LTV customer, it doesn't.
4. Price Your Products
If customers with higher first-order values have higher LTV, you can justify higher prices because you're attracting more valuable customers. Conversely, if discount shoppers have low LTV, stop running promotions that attract them.
5. Forecast Revenue
When you know LTV by cohort, you can predict future revenue with surprising accuracy. If you acquired 1,000 customers in January and your cohort data shows they'll generate $200 each over 12 months, you can forecast $200K from that cohort.
The LTV Reality Check
Here's a simple exercise to see if your LTV calculation is accurate:
The Back-Test
Step 1: Take your customer cohort from 12 months ago
Step 2: Calculate what your LTV formula predicted they would generate over 12 months
Step 3: Calculate what they actually generated in gross profit
Step 4: Compare predicted vs. actual
If your prediction was off by more than 20%, your LTV formula is broken. Most stores discover their calculated LTV is 50-100% higher than actual realized value. That's why they're unprofitable despite "good" unit economics.
How Lumino Calculates LTV Accurately
Lumino uses Method 3: Predictive LTV. It analyzes your entire customer base across dozens of behavioral dimensions, identifies patterns that predict future value, and generates individual LTV predictions for each customer. But it doesn't stop there—it segments customers by LTV potential and creates targeted strategies to maximize the value of each segment.
You get accurate, actionable LTV intelligence without the data science degree. No spreadsheets. No manual cohort tracking. No guessing. Just precise, predictive intelligence that drives better decisions.
The Bottom Line
LTV is the most important metric in e-commerce, but only if you calculate it correctly. Most stores use broken formulas that produce inflated numbers, leading to disastrous acquisition decisions. True LTV requires accounting for margins, time, churn, and segmentation. Get it right, and every other metric falls into place. Get it wrong, and no amount of traffic or conversion optimization will save you.