Drip Campaign Template for Product Growth

Most effective drip campaigns have 5-8 emails over 14-21 days. Shorter sequences (3-4 emails) work for simple conversions like booking a demo. Longer sequences (10-12 emails) suit complex enterprise sales cycles. The key constraint is value per email. If you cannot articulate a distinct purpose for each email, your sequence is too long. Track unsubscribe rates per email to identify the point where recipients lose patience.

For SaaS trial-to-paid drip campaigns, 10-25% total conversion (trial starts to paid) is strong. The drip campaign itself typically contributes 3-8 percentage points above what you would see with no email at all. For [onboarding](/glossary/activation-rate) sequences, measure activation rate rather than revenue conversion. Compare cohorts who received the drip against those who did not to isolate the campaign's impact. Use the [RICE Calculator](/tools/rice-calculator) to prioritize which sequence to optimize first based on reach and impact.

Test both. For B2B SaaS, plain text emails from a named sender (e.g., "Sarah from Acme") often outperform designed HTML emails because they feel personal. For B2C or e-commerce, branded HTML with product images typically performs better. The real answer depends on your audience. Run an A/B test on your first email using identical copy in both formats and let the data decide.

Set global suppression rules in your email platform. A user should not be in more than 2 automated sequences at once. Prioritize sequences by business impact: a trial conversion drip takes precedence over a feature announcement drip. Use a simple priority matrix: conversion campaigns > onboarding > engagement > promotional. Build a master campaign calendar that shows all active sequences and their cadences.

Review every campaign quarterly. Retire or rewrite campaigns when: open rates drop below 15%, the product has changed enough that the content is inaccurate, or you have new social proof that would be more persuasive. Drip campaigns are not "set and forget." The best teams treat them like product features that need regular iteration. ---