Lots of customers equal lots of revenue, right? But what if your actual customers are costing you more than they bring into your business?
Calculating the customer's Lifetime Value (LTV) not only detects the customers that are actually costing you money but also helps you determine which customers have the highest return on investment and what their common characteristics are. So let's take a look at your Daily LTV!
Definitions
In eCommerce, LTV is the value that a customer will contribute to your company over their entire lifetime. Essentially, it is the amount of money that they will spend on your products after expenses. The Daily LTV is calculated by averaging the LTVs of all your individual customers.
Before you dive into data analysis, let's ensure that we are on the same page:
LTV = ∑ Net Revenue - ∑ COGS
with
Net Revenue | Total revenue generated within the selected time period; by default excluding VAT, Shipping Revenue, Discounts, and Product Returns. |
COGS | Cost of goods sold including the purchase price |
You can monitor the LTV on the basis of the following lifetimes:
LTV 30 Days | Average lifetime value of all your customers after 30 days of lifetime. |
LTV 90 Days | Average lifetime value of all your customers after 90 days of lifetime. |
LTV 1 Year | Average lifetime value of all your customers after 1 year of lifetime. |
LTV 2 Years | Average lifetime value of all your customers after 2 years of lifetime. |
LTV 5 Years | Average lifetime value of all your customers after 1 year of lifetime. |
Understand additional report metrics:
Actual LTV 90 Days | Average lifetime value of your customers |
PoP Growth | Growth rate of the actual LTV against the previous period (PoP) |
Customers | Number of customers considered for the actual LTV calculation, customers who have already exceeded the selected lifetime |
Predicted LTV 90 Days | Average lifetime value of your customers, including our predictions for incomplete records |
PoP Growth | Growth rate of the predicted LTV against the previous period (PoP) |
Customers | Number of customers considered for the predicted LTV calculation, meaning customers who have either an actual or a predicted LTV for the selected lifetime |
What does this mean?
For each LTV calculation, we consider all customers that have already passed the lifetime under consideration. For example, to calculate the average LTV 30 Days, we include the LTV of all customers with a lifetime of at least 30 days.
If you booked our Predictions Add-On you can either monitor the LTV development of your customers based solely on actual data or activate our forecasts to also consider their potential we project. For this, we predict the lifetime value for all customers with incomplete datasets. Resuming the LTV 30 Days example, we would include all customers, even if they haven't been a customer for 30 days yet, but project their LTV for the remaining days until the 30 days mark. Prediction is performed via machine learning and searches data twins based on the following criteria:
- Frequency
- Average Order Value
- Return Behavior
- Order Quantity
- Demographics
Use Cases
The higher your LTV, the more loyal your customers are.
Congratulations! You get a steady flow of repeat purchases, people like your products and buy a lot more, and your business is healthy. You are good at customer retention. The report will answer the following questions:
- Does the net margin that you make with a customer within a period of time increase or decrease?
- What are the maximum short-term and long-term marketing costs I can spend to acquire a customer?
- Is the quality of my customers growing with time?
Also, you can combine this report with LTV Cohorts and get a full understanding of your LTV in different moments of your customer's journey.
- LTV Cohorts shows all LTV metrics for each acquisition cohort: it shows only new customers, so you get to understand the quality of your newly-acquired customers.
- Moving to Daily LTV, we can understand if acquisition LTV values translate into the same or higher LTV throughout the consumer's lifecycle: if we have a high LTV for new customers but a low LTV in our overall customer base, then it is time to implement strategies such as Cross-Selling, Up-selling or Product Bundles.
Not using RetentionX yet?
Read our full blog post about LTV analysis for Shopify stores here.
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