Customer Lifetime Value (LTV) is a metric that calculates the total amount of revenue a customer is expected to generate for a business over the course of their entire relationship. In eCommerce, LTV is a critical metric that helps businesses understand the long-term profitability of their customer base.
Several factors can impact LTV in eCommerce. These factors include:
Purchase frequency: The more frequently a customer purchases from a business, the higher their LTV will be.
Average order value: The higher the average order value, the higher the LTV will be.
Retention rate: The longer a customer remains loyal to a business, the higher their LTV will be.
Acquisition cost: The lower the cost of acquiring a customer, the higher the LTV will be.
Cohort analysis is a technique used to group customers based on a specific characteristic and track their behaviour over time. In eCommerce, cohort analysis is often used to track how customers behave over time based on their acquisition date.
To use cohort analysis to analyze LTV, businesses can group customers based on the date of their first purchase and track their behaviour over time. For example, a business may group customers who made their first purchase in January and track their behaviour over the next 12 months.
By tracking the behaviour of each cohort over time, businesses can gain insights into how their LTV is changing over time. For example, if a business notices that the LTV of customers who made their first purchase in January is declining over time, they may want to investigate what is causing this decline and take steps to address the issue.
Customer Lifetime Value (LTV) is a critical metric in eCommerce that helps businesses understand the long-term profitability of their customer base. Factors such as purchase frequency, average order value, retention rate, and acquisition cost can all impact LTV. Cohort analysis is a technique used to group customers based on a specific characteristic and track their behaviour over time, which can be used to analyze changes in LTV over time. Here are a few commonly used Cohort analyses examples to gain more insights into your customer behaviour.
- Acquisition Cohorts: This type of cohort groups customers based on the month or quarter in which they were acquired. For example, all customers who made their first purchase in January 2022 would form an acquisition cohort. By tracking the behaviour of each cohort over time, businesses can identify trends and changes in customer lifetime value.
- Behaviour Cohorts: This type of cohort groups customers based on their behaviour or actions. For example, all customers who made a purchase in a specific category or product line could form a behaviour cohort. By tracking the behaviour of each cohort, businesses can identify which products or categories are driving customer lifetime value.
- Demographic Cohorts: This type of cohort groups customers based on demographic characteristics such as age, gender, location, or income level. For example, all customers who live in a specific city or region could form a demographic cohort. By tracking the behaviour of each cohort, businesses can identify which demographics are most valuable and tailor their marketing efforts accordingly.
- Engagement Cohorts: This type of cohort groups customers based on their level of engagement with the brand or website. For example, all customers who have visited the website in the last 30 days could form an engagement cohort. By tracking the behaviour of each cohort, businesses can identify which engagement metrics (such as time spent on site or the number of pages visited) are most closely correlated with customer lifetime value.
By cohorting customer lifetime value in these and other ways, businesses can gain deeper insights into the drivers of customer value and make more informed decisions about where to focus their resources and efforts.
