MARKETING

Archive Losing Landing-Page Variants and Free Deployments

After a test concludes, this cleans up every losing variant: marks them archived in the experiments table, deletes their idle Vercel preview deployments.

CategoryMarketing
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerExperiment-complete webhook arrivesHTTP webhook
  • ActionQuery all non-winning variants for the experimentPostgreSQLPostgres
  • LogicSkip any deployment still serving the production alias
  • ActionDelete idle preview deploymentsVercelVercel
  • ActionMark loser rows as archivedPostgreSQLPostgres
  • OutputFile loss recap in results logNotionNotion

What it does

Once an experiment is marked complete, it sweeps the losing variants out of the way: it archives their records, removes the stale Vercel preview deployments they left behind, and preserves what was tested and why it lost in your results log.

When to use it

Use it when finished experiments pile up dead preview deployments and orphaned rows, and you want a clean slate plus a permanent record of every loss before you spin up the next test.

How it works

  1. 1A webhook fires when an experiment is marked complete in your dashboard.
  2. 2It queries Postgres for all variants in that experiment except the promoted winner.
  3. 3For each loser, a logic step confirms the deployment is no longer aliased before touching it.
  4. 4It calls Vercel to delete each idle preview deployment.
  5. 5It flips those variant rows to archived in Postgres.
  6. 6It writes a loss recap (variant, hypothesis, final lift, reason) to the Notion results log so the insight survives the cleanup.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect VercelDeploys, runtime logs, analytics.
  4. 4
    Connect NotionPages, databases, comments.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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