Customer lifecycle overview
Displays the breakdown of customers across lifecycle stages and tracks repeat-purchase metrics on a centralized dashboard.
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
Build the customer 360 board
Coming soonBlu builds a step
About this recipe
When to use it
CRM and lifecycle teams usually piece together lifecycle stage, repeat-purchase data, and LTV from separate reports. This puts all three in one view.
What it delivers
Combines lifecycle stage distribution, repeat-purchase mechanics, and LTV by acquisition cohort into a single CRM / Lifecycle dashboard.
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
“Displays the breakdown of customers across lifecycle stages and tracks repeat-purchase metrics on a centralized dashboard.”
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.
- 01Build the customer 360 boardCreate a Dash board (12-column composition canvas) titled "Customer 360". Persona: CRM Lead, Lifecycle Marketer, or Retention/Loyalty Lead. Question answered: "Where are my customers in their lifecycle, and how do they progress?" Board-level configuration: - defaultDateRange: last_90_days - exclusionPeriod: incomplete_periods - visibility: project - boardFilters: none by default - boardBreakdowns: Lifecycle score (the canonical 6-stage Users-object enum: At risk, Needs attention, New customers, Promising, Regulars, Champions) Layout: 4 rows. Row 1: Lifecycle KPIs (heightPx: 200, four metric cards at widthUnits: 3): - Card 1: Insights metric to source recipe: customer-lifecycle-distribution, vizType: metric, titleOverride: "Total Active Customers" - Card 2: Insights metric to source recipe: customer-lifecycle-distribution, vizType: metric, titleOverride: "% in Champions + Regulars" - Card 3: Insights metric to source recipe: customer-lifecycle-distribution, vizType: metric, titleOverride: "% in At Risk + Needs Attention" - Card 4: Insights metric to source recipe: first-purchase-cohort-ltv-curve, vizType: metric, titleOverride: "Average LTV (M6)" Row 2: Lifecycle distribution and migration (heightPx: 440, full-width single card at widthUnits: 12): - Card 1: Insights to source recipe: customer-lifecycle-distribution, displayMode: chart (the stacked bar showing all 6 lifecycle stages with the migration view as a side panel) Row 3: Repeat-purchase mechanics (heightPx: 400, two cards at widthUnits: 6): - Card 1: Retention to source recipe: purchase-retention, displayMode: chart, vizType: retention_curve (cohort by first-purchase month) - Card 2: Insights to source recipe: post-purchase-second-order-velocity, displayMode: chart (histogram of days from 1st to 2nd order: informs replenishment journey timing) Row 4: Long-term value (heightPx: 440, two cards at widthUnits: 6): - Card 1: Insights to source recipe: first-purchase-cohort-ltv-curve, displayMode: chart, vizType: line (cumulative LTV per cohort member) - Card 2: Path to source recipe: post-conversion-onboarding-paths, displayMode: chart (what new paying customers do in their first session: the post-purchase moment) Annotations: - Row 1 KPIs are filtered views of customer-lifecycle-distribution and first-purchase-cohort-ltv-curve: Lovable applies the Lifecycle score IN filter and renders the metric vizType. - Row 2 (the full-width lifecycle distribution) is the dashboard's centerpiece. The single most important metric here is the migration view: "147 Regulars moved to At risk this month" is more actionable than any point-in-time percentage. - Row 3 surfaces operational levers: the 2nd-order velocity histogram tells you the right replenishment-trigger delay per category. - Row 4 closes the loop: which acquisition cohorts produce high-LTV customers, and what does the post-purchase moment look like for newly-converted customers. Taxonomy notes: - All source recipes use canonical events: Placed order (with items, total_price), Session start, View page. - Users.Lifecycle score is the canonical 6-stage enum (At risk / Needs attention / New customers / Promising / Regulars / Champions). Do NOT introduce textbook RFM segment names like "Loyal," "VIP," "Hibernating," etc.
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 /customer-360-dashboard 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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