Cometly
AcademyModule 03 · Product-Led Growth Reports
PLGReportLesson 3.7·8 min read

Plan-level attribution report

Free trials, $1 trials, Pro, Enterprise — each behaves differently.

Plan-level reporting is what turns generic PLG attribution into something your finance team can act on. Not every customer is created equal — a Pro Annual user is worth 5x a Pro Monthly user, and an Enterprise contract is worth 50x. Allocating spend without knowing which plans each channel attracts means you’re guessing about half the economics.

Why this matters

A Meta campaign that delivers 100 Pro Monthly trials at $30 CAC and a LinkedIn campaign that delivers 20 Pro Annual trials at $200 CAC look very different on a cost-per-trial report — but they’re actually similarly profitable if you account for plan LTV. Plan-level attribution makes that visible.

Section 01

Setting up plan tags

Add a plan-name filter to each of your Cometly Stripe events: Trial Started (Pro Monthly), Trial Started (Pro Annual), Trial Started (Enterprise). Cometly will pull the plan name directly from Stripe and you can use it as a filter or grouping in any report.

Build a Source Attribution report with Plan as the column dimension. Each row is a source, each column is a plan, and each cell is the count of trials, customers, or revenue for that source/plan combination.

  • Tag each Stripe event with a plan filter
  • Group source-attribution reports by Plan
  • Calculate plan-level LTV separately and use as the bidding value
  • Build separate lookalike audiences for high-LTV plans
Section 02

Acting on plan mix

Look for channels with a plan-mix bias. A channel that over-indexes on Pro Annual and Enterprise is usually a high-intent channel worth scaling at the plan level — even if its raw cost-per-trial looks expensive. A channel that over-indexes on free trials with low conversion is usually a top-of-funnel awareness channel that needs longer cohort horizons before judgment.

Sync plan-level audiences back to your ad platforms as separate lookalikes. A 1% lookalike on Pro Annual customers performs very differently than a 1% lookalike on all customers — usually with much higher LTV.

Common pitfalls

What to watch for.

  • Reporting only blended LTV

    Blended LTV averages out a 50x range across plans. Always break by plan before making spend decisions.

  • Optimizing on Trial Started without plan filter

    Meta will deliver more of whatever plan converts cheapest — usually free trials. Filter the event by plan to keep the algorithm focused on high-value plans.

  • Treating annual and monthly the same

    Annual contracts are 12x the up-front revenue and usually 1.3–1.8x the LTV of monthly. Worth their own dedicated treatment.

Key takeaways

Recap.

  • Use a plan-name filter on each Cometly event mapped from Stripe
  • Add a Plan dimension to your source attribution report as a column or grouping
  • Track LTV by plan to allocate ad spend toward the highest-margin tier
  • Identify channels that over-index on free trials vs paid plans
  • Use plan-level audiences in your ad platforms to bias toward higher-LTV customers
Put it into practice

Build this report inside your own Cometly workspace.

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