💸LTV/Retention by Dimension
This report is derived from your Sales data (e.g. DTC Sales from Shopify or Amazon Sales from Amazon).
Last updated
This report is derived from your Sales data (e.g. DTC Sales from Shopify or Amazon Sales from Amazon).
Last updated
Cohort Start Date: This filter defines the period in which the customers made their first purchase. By default, this report is set to a period from two years ago to one year ago so that we use a large cohort that has aged exactly one year.
Cohort Dimension: Pick the dimension you would like to compare LTVs or retention between. For instance, if you select "First Order - Product Title", you'll receive a cohorted comparison over time of each product title purchased on the first order in terms of the metric you select (e.g. Customer Retention).
Interval Since First Purchase: This is a control available in the Filters menu with the possible options of Month, Week, and Day. Each option calculates the calendar distance since the first purchase.
Metrics:
Customer Retention: Returning Customers / Cohort Size
Gross LTV: Cumulative Gross Sales / Cohort Size. Net Sales LTV: Cumulative Net Sales / Cohort Size. Net Sales = Gross Sales - Discounts - Returns. Net Revenue LTV: Cumulative Net Revenue / Cohort Size. Net Revenue = Net Sales + Taxes + Shipping.
This report only outputs LTVs or Retention Rates of n Intervals Since First Purchase such that every customer within the cohort would've had a chance to purchase up through the very last Interval Since First Purchase.
Let's dig into that further...
When opening the report for the first time, it will default to a Cohort Start Date range between two years ago and one year ago. As a result, the report will pull LTVs of a length exactly equal to one year. The report will also default to using Months as the Interval Since First Purchase. This means that, for every month represented in this report, every customer in the cohort would've have a chance to make a returning purchase from Month 0 all the way to Month 12.
So if you were to look at Days Intervals Since First Purchase and set the Cohort Start Date range to, say, six months ago to 15 days ago, the LTVs outputted would only be a length equal to 15 days. This is because we're only constructing LTVs such that every customer has had the same length of time to make a returning purchase. (The customers who were acquired 15 days ago have only had 15 days where they could've made a returning purchase.)
Amazon can often experience a 14 day lag. Click below to learn more.
Make sure to set the Cohort Start Date to a range of dates in the past.
View the performance by cohort of your previous 365 days in a graph and table.
Hovering over the graph will show the customer lifetime value by a specific segment.
💡Example: After 21 days, the net revenue customer lifetime value of customers who bought a subscription in Feb-23 is $51. After 250 days their net revenue customer lifetime value is $63.