Workflow · Customers · Opening soon

Customer lifetime value by cohort

See customer lifetime value by signup month cohort from your Shopify exports. Track revenue per customer so far and average order count, while excluding refunded orders.

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Someone typed

“using the shopify customers and shopify orders, show each signup month cohort with revenue per customer and average order count, excluding refunded orders and counting customers by their first signup month”

The agent read it as

Using the Shopify customers and Shopify orders, show each signup month cohort with revenue per customer and average order count, excluding refunded orders and counting customers by their first signup month.

What the agent built

3 steps, each one an ordinary Mammoth step you can open and change.

File

Shopify customers

CSV export · 15 rows

File

Shopify orders

CSV export · 30 rows

Step

Summarize non-refunded orders

Step 1

Join

Bring in order totals

15 of 15 paired

Step

Summarize signup cohorts

Step 3

Result

Signup Cohort Revenue

13 rows

Schedule

Runs when you say

Proposed

File
Shopify customers
CSV export · 15 rows
File
Shopify orders
CSV export · 30 rows
Step
Summarize non-refunded orders
Step 1
Join
Bring in order totals
15 of 15 paired
Step
Summarize signup cohorts
Step 3
Result
Signup Cohort Revenue
13 rows
Schedule
Runs when you say
Proposed

Checked on the sample files: every step ran, 13 rows came out, and the join paired 15 of 15 rows.

Download Shopify customers sample (15 rows)Shopify admin: Customers > Export
Download Shopify orders sample (30 rows)Shopify admin: Orders > Export

What you get back

The result of that run, the rows to look at first.

Signup Cohort RevenueSample data13 rows

Signup month	Revenue per customer	Average order count	Customers
2025-11-01	255.76	3	1
2025-12-01	125.27	2	1
2026-01-01	360.54	4	1
2026-02-01	68.48	1	1
2026-03-01	155.52	2	1
2026-04-01	129.34	2	1
2026-05-01	298	3	1
2026-06-01	57.78	1	1
2026-07-01	136.44	1.50	2
2026-08-01	146.88	2	1
2026-09-01	356.40	3	1
2026-10-01	90.36	1	2

13 rows in the result · 12 shown, problems first. Sample data: illustrative figures, not business results.

How do you work out customer lifetime value by cohort?

Export your Shopify customers and orders, then upload both files. Mammoth groups customers by their first signup month, sums non refunded orders, and shows revenue per customer plus average order count for each cohort. Rows that do not match the rules are left out of the cohort result.

How it works

How to use the Signup Cohort Revenue workflow

1Get early accessWe invite people in small batches, job by job. You'll land on this workflow, already built and checked on the sample files.
2Swap in your exportsUpload your own files as they come out of your tools. The agent checks the workflow on your rows.
3Change it in words, then turn it onSay what to change and see the new result before anything saves. Then choose when it runs.

Signup Cohort Revenue: questions

Which export files should you use?

Use a Shopify customers export and a Shopify orders export. The workflow needs customer signup dates and order totals to group customers by cohort and calculate lifetime value metrics.

What happens to refunded or unmatched rows?

Refunded orders are excluded from the order totals. Rows that do not match the workflow rules, or cannot be linked into the cohort summary, are not included in the final metrics.

How do you change the cohort rules?

Edit the steps in words, such as the cohort date field, the refund rule, or the metric you want to summarise. Then run the workflow again on the exported files.