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 LTV Cohorts:
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 LTV Cohorts are calculated by averaging the LTVs of all your new customers acquired in the same time period.
Before you dive into data analysis, let's ensure that we are on the same page:
LTV = ∑ Net Revenue - ∑ COGS
Net Revenue | Total revenue generated within the selected time period; excluding VAT, Shipping Revenue, Discounts, and Product Returns. |
COGS | Cost of goods sold including the purchase price |
Cohorts Size | Number of customers who made their first purchase |
vs. Average LTV | Percentage difference of the cohort's LTV compared to the average LTV of all customers after the same lifetime. |
You can monitor the LTV based on the following metrics:
LTV 30 Days | Average Lifetime Value of all your customers within their first 30 days as a customer. |
LTV 90 Days | Average Lifetime Value of all your customers within their first 90 days as a customer. |
LTV 1 Year | Average Lifetime Value of all your customers within their first year as a customer. |
LTV 2 Years | Average Lifetime Value of all your customers within their first 2 years as a customer. |
LTV 5 Years | Average Lifetime Value of all your customers within their first 5 years as a customer. |
Now, you can compare your LTV evolution for different days, weeks, months, quarters, half, and a full year.
LTV Cohorts
This report breaks down your customers into related groups to gain a better understanding of their purchase behaviors. In this case, your customers are divided by when they placed their first order and we can measure the lifetime value of these cohorts.
This means that in each bar we can see the selected LTV for all customers acquired in that time period. But what if you choose LTV 1 Year and you are looking at customers acquired last month? That's when predictions come in handy!
This report calculates the historical LTV. However, if a customer has not been a customer sufficiently long by the time of consideration, the LTV is predicted based on RX Prediction™.
RX Prediction – wait, what?
Prediction is performed via machine learning and searches data twins based on the following criteria:
- Frequency
- Average Order Value
- Return Behavior
- Order Quantity
- Demographics
Based on this information, RX predicts the lifetime value for all customers with still incomplete datasets.
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:
- Will the customers you've acquired today be worth more or less than those you've acquired a month ago?
- When did you acquire the most valuable customers?
- When did this year's customers outperform last year's one and by how much?
- Can you increase your marketing costs per customer as the current customer quality allows it?
Also, you can combine this report with Daily LTV 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 if you are acquiring high-quality 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.
Comments
0 comments
Please sign in to leave a comment.