A cohort is a fancy word for a group
It is a predefined grouping of your customers. -- "First order placed in August 2021"
It allows us to see trends in behavior over time.
You'll track the cohort customers’ journeys as they purchase more/less from your brand. Cohort Analysis is a visual chart for plotting and comparing the progression of specific METRICS for each cohort over time.
You can run heaps of analysis - Repurchase Rate, Returning Rate, Days since First Order, AOV, Refunds, Discounts, Lifetime Revenue, Churn, MRR, Gross Margin Rate, etc. in cohort form. Peel supports all of these analyses out of the box.
Each row represents a cohort of users -- "July 2021"
Each column represents a month following the cohort's creation. Month 1 being the month they became a customer. Month 2 being the 2nd month after being a customer "August 2021" in this example.
The value in the cell is the analysis you are computing - Repurchase Rate, LTV, Returning Rate, AOV, Discounts, Refund, etc. etc.
Left to right: How is that cohort progressing over time? Are values growing?
Top to bottom: How do the cohorts compare to one another?
Diagonally: Is there seasonality. Does a time in the year increase sales, orders, customer behavior?
Color shading is usually applied to cohorts to allow your eyes to quickly identify the key differentiators/spikes in behavior.*
Cohort analysis allows us to directly compare cohorts to each other - by lining up the start date of each cohort.
It is the best way to look at activity and retention numbers on a cohort-by-cohort basis.
It is extremely important to identify and target problems/wins in the customer lifetime. Cohort analysis allows you to zero in on specific months and at specific times in the calendar year.
"Customer acquisition rate is significantly higher in Nov/Dec than in other months, but the repurchase behavior by month 3 is only 10% while in July cohort, it is 25%."
Helps you uncover the characteristics in your best and worst performing GROUPS/COHORTS of customers.
Updated 3 months ago