Summary

Lifetime Value (LTV) represents the total revenue you can expect from each customer over their relationship with your business. Because LTV calculations factor in all orders made by these customers—sometimes within a specific window, such as 60 or 90 days—this metric naturally evolves as more purchases occur. Changes in time range selection, additional orders from existing customers, and different product-specific calculations further explain why the number you see for LTV isn’t static.

Why This Happens

1. Rolling Cohorts and Additional Purchases

   • LTV is typically calculated by summing all order revenue from a group of customers and dividing by the number of unique customers in that group.
   • If these same customers make subsequent purchases, the total order value grows—thus raising (or occasionally lowering) the average LTV over time.

2. Time Range Selection (60-Day or 90-Day LTV)

   • In some reports, the LTV focuses on orders placed within 60 or 90 days of a customer’s initial purchase.
   • If a customer makes multiple purchases within that window, all those purchases are added to their total, which can cause the LTV to increase as the data updates.

3. Excluding $0 Orders and Customers Without IDs

   • Many LTV tools (including Triple Whale’s 60/90 LTV pages) exclude orders with a $0 total or orders without valid customer information.
   • If previously untracked orders become valid (e.g., corrections to the order record), LTV may shift because the underlying set of included orders changes.

4. Product-Specific Filtering

   • In certain pages, LTV is calculated only for customers who purchased a specific product in their first order.
   • Any subsequent purchases (with or without that product) are still added to their lifetime revenue, so LTV can keep rising as these customers place new orders.

5. Different Definitions in Different Reports

   • Some pages measure LTV using a “lifetime” approach with no cutoff window, while others focus strictly on a 60- or 90-day period after a first purchase.
   • These variations can make LTV appear to “change,” but it often reflects the same data applied to different time spans or product filters.

Example Scenario

1. Day 1: A new customer buys Product X for $50 (COGS excluded for simplicity).
2. Day 15: The same customer returns and makes a second purchase of $30.
   • 60-Day LTV: Now includes both orders ($80 total) for this one customer, raising the per-customer LTV to $80.
   • If the tool only had the first purchase accounted for at $50, it updates once the second purchase is recognized, causing an apparent “change” in LTV.

How This Affects Reporting

• Fluctuating Averages: If a large cohort of customers makes follow-up purchases, the average LTV can rise significantly over time.
• Differences Across Tools: Various dashboards (e.g., the 60/90 LTV page vs. Product Analytics) have unique filters and definitions, so the same customer data can produce different LTV results.
• Ongoing Recalculation: Every new order from an existing customer re-enters the formula. This can boost (or occasionally lower) the average if the subsequent orders have lower or higher values than the original purchase.

How to Interpret the Data Correctly

1. Identify the Time Window

   • Confirm whether you’re looking at a 60-day, 90-day, or unlimited timeframe. Understand that customers who purchase again during that period increase the total.

2. Check Excluded Orders

   • Remember that $0 orders or orders without valid customer data may be omitted. Corrections to those records can change your LTV down the line.

3. Evaluate Product-Specific Views

   • If the LTV is filtered for a certain product, only the first purchase of that product defines the customer pool. Any subsequent purchases—of any product—will raise their LTV.

4. Watch for Delayed Updates

   • If a purchase wasn’t fully captured or has been updated in the system (e.g., an order gets corrected), the LTV might jump once the platform recognizes the change.

5. Monitor Trends, Not Just a Single Number

   • LTV is dynamic by nature. Observe how it shifts over weeks or months to gain a more reliable view of customer profitability rather than focusing on a single snapshot in time.

By keeping in mind that LTV is regularly updated with each new purchase—whether the focus is on a 60/90-day period or a product-specific view—brands can better understand why this key metric continues to evolve rather than remaining fixed.