LTV Tracker

How much profit do you make on average from a single customer? And are you improving over time? These are essential questions every brand should be able to answer—especially when evaluating the return on marketing investment.

As not all customers are the same, it is equally important to understand the difference in LTV between your distinct customer groups. By doing so, you can assign a monetary value to these segments and identify the factors that drive customer loyalty and, ultimately, LTV. Is it your subscription model? Your loyalty program? Or perhaps some other customer characteristic?

The LTV Tracker report is designed to answer all these questions, so let's take a closer look at how it works!

How it Works

In simple terms, the LTV Tracker calculates the average lifetime value of a customer after a certain period of time, e.g. after a customer's first year – and tracks the development over time.

LTV reflects profitability at the CM1 (Contribution Margin 1) level, which is calculated as net revenue (after product returns) minus cost of goods sold (COGS).

LTV = ∑ Net Revenue - ∑ COGS

The biggest challenge when analyzing LTV is the time frame: LTV is always time-bound!
Let's assume you just increased your ad spend and attracted a high volume of new customers. These new customers will naturally have lower LTVs because they haven’t had the time to place follow-up orders, but if you factor in their LTV with the same weight as customers acquired years ago, it would skew your overall LTV. That's why RetentionX calculates the average LTV not just by averaging the current LTVs of all your customers, but by considering different time-bound breakdowns.

Step 1: Calculating the LTV per Customer

In the first step RetentionX calculates the LTV per customer. Under Customers > All Customers you'll find the LTV per customer and if applicable the LTV breakdown after 1, 3, 12, 24 and 60 months.

Step 2: Identifying Customer Cohorts

In the next step, RetentionX identifies which customers should be considered for the LTV averaging. For each average LTV calculation, only customers that have already passed the lifetime under consideration are included. For example, to calculate the average LTV 1 Year, only customers with a lifetime of at least one year are factored in. 

Step 3: Averaging the LTVs

Once the appropriate customers are identified, RetentionX averages the LTV for the specified lifetime. To calculate the average LTV 1 Year, only customers who have been around for at least one year are considered, and only the LTV generated in their first year is included. This allows you to understand the average value of a customer after one year.

Step 4: Recording a Daily Snapshot

As new customers join a cohort daily by surpassing the lifetime under consideration, the average LTV is recalculated every day. To understand the development over time and spot trends in customer quality, RetentionX tracks the daily calculated average LTV.

Identify LTV Drivers

Now that you know the average LTV of your customers at 30 days, 90 days, 1 year, 2 years, and 5 years, you can take the analysis a step further. By applying your customer segments to the report, you can compare the LTVs of these customer groups to each other. This reveals the monetary effect of your different strategies and customer behaviors. For example, you could compare the LTVs of:

• New vs. Returning Customers
  Understand the LTV impact of achieving the second order for your customers
• One-Time Purchasers vs. Subscribers
  Quantify the LTV uplift of converting a one-time purchaser into a subscriber
• Different Loyalty Tiers
  Analyze LTV differences between customers in different loyalty tiers (e.g. bronze, silver, gold)
• Welcome Code Users vs. Non-Redeemers
  Understand the quality of customers attracted by your welcome promotions
• Customers with Returns vs. Non-Returners
  Measure the effect of product returns on customer profitability

You can also combine this report with LTV Cohorts to quickly understand if you're able to improve the quality of your newest customers.

Predictions

If you add Forecast Plus to you plan, you can monitor the LTV development of your customers based solely on actual data, or activate our forecasts to consider the potential we project. For this, we predict the LTV for all customers with incomplete datasets. Returning to the LTV 1 Year example, we would include all customers, even those who haven’t been a customer for one year yet, by projecting their LTV for the remaining days until they reach the 1-year mark.

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