Understanding Campaign Analytics

Last updated: April 24, 2026

Campaign analytics tell you how your outreach is performing and where to focus your optimization effort. Knowing which metrics matter — and what to do when they're off — is what separates campaigns that compound over time from ones that plateau.

The metrics that matter

Reply rate

The most important metric. It's the only one that directly reflects whether your emails are resonating with the right people. A healthy cold email reply rate is 3–8% depending on your audience and personalization approach.

If reply rate is low: Check targeting (wrong audience?), personalization signal (relevant?), copy (too long, too salesy?), and CTA (too much friction?).

Open rate

Indicates whether your subject lines are earning opens and whether emails are reaching the inbox (not spam). A healthy open rate for cold email is 40–60%.

If open rate is low (<20%): Emails may be landing in spam. Check deliverability — warmup status, authentication records, bounce rate. Then review subject lines for spam trigger words.

If open rate is 100%: This is almost certainly a security gateway artifact, not real opens. Disable open tracking and use reply rate instead.

Bounce rate

Keep below 2%. Above this, you're damaging your domain reputation. High bounce rates indicate list quality issues.

Unsubscribe rate

Keep below 0.5%. A high unsubscribe rate usually means audience mismatch — you're reaching people who have no relevant context for your offer.

[Screenshot: Campaign Analytics showing reply rate, open rate, bounce rate, and unsubscribe rate with benchmark indicators]

Reading per-step analytics

Open the per-step breakdown to understand where in your sequence engagement drops off:

  • High open, low reply on Step 1 — Subject line works, but body copy or CTA isn't landing. Rewrite the ask.

  • Low open on Step 1 — Subject line or deliverability issue. Test a new subject line or check spam score.

  • Strong reply rate on Step 3 vs Step 1 — Follow-ups are outperforming the opener. Analyze what's different about the Step 3 copy.

Using analytics to iterate

  1. Run each campaign for at least 200 sends before drawing conclusions

  2. Change one variable at a time — subject line, opening line, CTA, or personalization signal

  3. Use A/B variants within Sequences to test changes cleanly without running separate campaigns

  4. Apply winning patterns to future campaigns — document what's working by audience segment