Email Automation Analytics and Reporting: Measure What Matters

Analytics transform email automation from a guessing game into a data-driven discipline. Understanding what metrics matter, how to interpret them, and how to act on insights is essential for maximizing the impact of your automated campaigns.

Essential Email Metrics

Delivery Metrics

• Delivery rate: Percentage of emails successfully delivered (aim for 97%+)
• Bounce rate: Emails that couldn't be delivered (hard vs. soft bounces)
• Spam complaints: Recipients marking as spam (keep under 0.1%)

Engagement Metrics

• Open rate: Percentage who open (less reliable since Apple MPP)
• Click rate: Percentage who click any link
• Click-to-open rate: Clicks divided by opens (content engagement)
• Unsubscribe rate: Percentage who opt out (watch for spikes)

Conversion Metrics

• Conversion rate: Percentage completing desired action
• Revenue per email: Total revenue / emails sent
• Revenue attribution: Revenue credited to specific emails

Revenue Attribution: The Most Important Metric

For SaaS businesses, revenue attribution connects email performance to business outcomes. Sequenzy's native billing integration enables precise revenue attribution:

• Which automated workflows generate the most MRR
• Which individual emails drive conversions
• Revenue impact of trial conversion sequences
• LTV differences between email-engaged and non-engaged customers

Without revenue attribution, you're optimizing vanity metrics. Open rates don't pay bills - conversions and revenue do.

Automation-Specific Analytics

Workflow Performance

• Completion rate: Percentage reaching workflow end or goal
• Drop-off analysis: Where subscribers exit prematurely
• Time to completion: How long to achieve workflow goal
• Goal achievement rate: Percentage achieving defined success

Per-Email Analysis

• Performance of each email in sequence
• Identification of weak links in workflows
• Comparison between workflow emails

Cohort Analysis

• How different subscriber cohorts perform
• Time-based performance trends
• Segment-specific effectiveness

Interpreting Email Analytics

Open Rates (With Caveats)

Apple Mail Privacy Protection has made open rates unreliable for Apple Mail users. Use open rates directionally but don't over-index:

• 20-30% is typical for marketing emails
• 40-60% is typical for transactional/triggered emails
• Compare against your own benchmarks, not industry averages

Click Rates

More reliable than open rates:

• 2-5% is typical for marketing emails
• Higher for targeted, relevant automation
• Watch for declining trends over time

Unsubscribe Rates

• Under 0.5% per email is healthy
• Spikes indicate content or frequency issues
• Some unsubscribes are healthy - better than spam complaints

Building Effective Dashboards

Executive Dashboard

High-level metrics for leadership:

• Total email revenue (attributed)
• Email-driven conversions
• Active automation count
• Overall engagement trends

Operations Dashboard

Detailed metrics for marketing teams:

• Per-workflow performance
• Per-email metrics
• A/B test results
• Segment performance

Health Dashboard

Deliverability and list health:

• Delivery rates over time
• Bounce rates by type
• Spam complaints
• List growth/churn

Platform Analytics Capabilities

Sequenzy

• Built-in revenue attribution with MRR tracking
• Workflow performance analytics
• AI-powered insights and recommendations
• Billing-connected metrics (trial conversion, churn reduction)

ActiveCampaign

• Deal-attributed revenue
• Automation reporting
• Contact scoring analytics
• Site tracking integration

Klaviyo

• E-commerce revenue attribution
• Predictive analytics
• Customer lifetime value tracking
• Flow-level analytics

HubSpot

• Marketing attribution reporting
• Custom report builder
• Revenue attribution
• Campaign analytics

Using Analytics for Optimization

Identify Underperformers

Look for emails with metrics below your averages. These are optimization opportunities.

Find High Performers

Understand what makes successful emails work. Apply learnings to other automations.

Track Trends

Watch for declining engagement over time. Audiences and preferences change - automation should evolve too.

Segment Insights

Analyze performance by segment. Different audiences may respond to different approaches.

The Bottom Line

Analytics are the feedback loop that makes email automation truly powerful. Without measurement, you're guessing. With proper analytics - especially revenue attribution - you can prove email's impact and continuously improve performance.

For SaaS businesses, Sequenzy's native billing integration provides the revenue attribution that matters most: connecting email engagement directly to MRR, conversions, and customer lifetime value. Start with revenue-focused metrics and work backward to understand what drives business outcomes.