First purchase LTV curve
Compare revenue trends across monthly customer cohorts over calendar time. Use the report to see how cohort revenue changes as calendar dates progress.
Authored by Sid Chaudhary
Founder & CEO at Intempt
Agentic workflow
Coming soon1 step Blu runs end to end. It drafts a plan and nothing runs until you approve it.
- 1
Plot revenue per cohort by age
Coming soonBlu builds a step
About this recipe
When to use it
LTV modeling is guesswork without a real cumulative revenue curve to anchor it. This plots cumulative revenue per cohort member against cohort age - the standard view DTC finance teams build payback-period math on.
What it delivers
Plots cumulative revenue per member of each acquisition cohort against cohort age, producing the standard LTV curve used for payback-period and LTV:CAC calculations.
How you prompt this
Describe the outcome in your own words and Blu Agent maps it to this recipe, or run it by name. It drafts a plan first and nothing runs until you approve it.
Tell Blu Agent what you want
“Compare revenue trends across monthly customer cohorts over calendar time. Use the report to see how cohort revenue changes as calendar dates progress.”
recipe.md preview
Built from the published catalog. Blu Agent's full step prompts load in your workspace when you run it.
Inputs & outputs
What the recipe needs before it runs, and what it leaves in your workspace.
Inputs
- Nothing declared beyond an Intempt workspace. Blu asks for anything else it needs as it goes.
Outputs
How the recipe runs
Blu follows the steps in order and shows you each one before anything goes live.
- 01Plot revenue per cohort by ageCreate an Insights report called "First-Purchase Cohort LTV Curve". Series A: Event "Placed order", aggregation: Sum of "total_price", scoped per user, cumulative from each user's first Placed order Series B: Computed: Series A / cohort size, unit: $, label: "Cumulative Revenue per Cohort Member" Cohort: Monthly cohort defined by month of first Placed order (each user's first Placed order event determines their cohort) Time range: Last 12 months of cohorts (allow some cohorts to have shorter LTV tails: surface "incomplete cohort" labels for the most recent ones) Breakdown: By Users.UTM source (the user's first-touch acquisition channel, from the Users object) Chart type: Multi-line chart: each line is a cohort, X axis is cohort age in months (0, 1, 2, ..., 12), Y axis is cumulative revenue per cohort member Annotations: - Highlight the highest-LTV cohort and lowest-LTV cohort at month 6 and month 12. - Flag any cohort where LTV growth flattens prematurely (LTV-curve "going horizontal" by month 3-6 indicates a one-time-buyer cohort). - Highlight channels where cohort LTV is increasing across recent cohorts (acquisition quality improving). Taxonomy notes: - "First purchase" is determined per-user by the earliest Placed order event for that customer_id. - Users.UTM source is a real first-touch attribution attribute on the Users object. - LTV is cumulative sum of Placed order.total_price per user from first purchase onward.
Install Intempt and run it
- 1
Sign up
Create a free Intempt workspace.
- 2
Connect your data
Add the sources this recipe reads from.
- 3
Ask Blu
Type /first-purchase-cohort-ltv-curve in Blu once this recipe is live there.
- 4
Review and approve
Blu builds each step and waits for your OK before anything goes live.
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