Email Deliverability Dashboard: What Metrics to Track

Why Build a Deliverability Dashboard

Your ESP shows some metrics. Postmaster Tools shows others. Blacklist monitors show more. Without a unified view:

• You miss correlations between metrics
• Problems surface late, after damage compounds
• Reporting to stakeholders requires manual assembly
• Trends over time aren't visible

A deliverability dashboard consolidates everything into one place for real-time health monitoring.

Core Metrics to Track

Tier 1: Critical Health Indicators

These metrics need constant visibility. Problems here require immediate action.

Delivery Rate

(Emails Delivered ÷ Emails Sent) × 100

Target: >98%

Hard Bounce Rate

(Hard Bounces ÷ Emails Sent) × 100

Target: <0.5%

Spam Complaint Rate

(Complaints ÷ Emails Delivered) × 100

Target: <0.1%

Authentication Pass Rate

(SPF Pass + DKIM Pass + DMARC Pass) ÷ Total Checks × 100

Target: >99%

Tier 2: Reputation Indicators

Check daily; trends matter more than point-in-time readings.

Gmail Domain Reputation (from Postmaster Tools)

• High / Medium / Low / Bad

IP Reputation (from Postmaster Tools + SNDS)

• High / Medium / Low / Bad

Blacklist Status

• Listed: Yes/No
• Number of lists

Sender Score (if using dedicated IPs)

• 0-100 scale

Tier 3: Engagement Signals

Track weekly trends. Indirect deliverability impact through reputation.

Unique Open Rate (directional only)

(Unique Opens ÷ Emails Delivered) × 100

Click Rate

(Unique Clicks ÷ Emails Delivered) × 100

Unsubscribe Rate

(Unsubscribes ÷ Emails Delivered) × 100

Practitioner note: I put engagement in Tier 3 because it's a lagging indicator. By the time open rates drop, the reputation damage is already happening. Focus on Tier 1 for early warning.

Dashboard Layout

Section 1: Current Status (Top of Dashboard)

Big numbers at a glance:

• Last campaign delivery rate
• Current spam complaint rate (rolling 7 days)
• Gmail reputation (text indicator)
• Blacklist status (green/red indicator)

Section 2: Trend Charts (Middle)

Time-series graphs:

• Delivery rate over 30 days
• Bounce rate over 30 days
• Complaint rate over 30 days
• Open/click rate over 30 days (engagement proxy)

Section 3: Per-Campaign Table (Bottom)

Recent campaign performance:

Campaign	Sent	Delivered	Bounced	Complaints	Opens	Clicks
March Newsletter	50,000	49,200	800	35	18%	3.2%
Flash Sale	75,000	73,500	1,500	89	22%	4.1%

Section 4: Provider Breakdown (Optional)

If using inbox placement testing:

• Gmail: % inbox vs spam
• Outlook: % inbox vs junk
• Yahoo: % inbox vs spam

Data Sources and Integration

ESP API

Most ESPs provide APIs for pulling metrics:

SendGrid: Stats API for delivery, bounce, complaint data

curl -X GET https://api.sendgrid.com/v3/stats \
  -H "Authorization: Bearer API_KEY"

Mailgun: Analytics API for similar metrics

curl -X GET https://api.mailgun.net/v3/{domain}/stats/total \
  -u 'api:API_KEY'

Postmark: Stats API

curl https://api.postmarkapp.com/stats/outbound \
  -H "X-Postmark-Server-Token: API_KEY"

Google Postmaster Tools

No official API, but workarounds exist:

• Manual export (CSV download)
• Third-party scrapers (with caveats)
• Google BigQuery connection (for large operations)

DMARC Reports

Parse aggregate reports for authentication data:

• dmarcian API
• Postmark DMARC tools
• Custom RUA parser

Blacklist Monitoring

• MXToolbox API ($99+/month)
• HetrixTools API (free tier)
• Custom blacklist checker scripts

Building With Google Looker Studio (Data Studio)

Free option for smaller operations:

Setup Steps

1. Create data source: Google Sheets with daily metrics
2. Import ESP data: Manual or via script/Zapier
3. Add Postmaster data: Manual weekly export
4. Build visualizations: Scorecards, time series, tables
5. Set refresh schedule: Daily or on-demand

Template Structure

Sheet 1: Daily Metrics
Date | Sent | Delivered | Bounced | Complaints | Opens | Clicks

Sheet 2: Reputation
Date | Gmail Domain Rep | Gmail IP Rep | Sender Score

Sheet 3: Blacklists
Date | IP | Blacklist Name | Status

Limitations

• Manual data entry for some sources
• No real-time updates
• Limited alerting capability

Building With Datadog/Grafana

For engineering teams with existing monitoring infrastructure:

Datadog Setup

1. Send ESP webhooks to Datadog Events
2. Create metrics from event data
3. Build dashboard with time series + scorecards
4. Configure alerts on thresholds

Grafana Setup

1. Store metrics in InfluxDB or Prometheus
2. Ingest ESP webhooks via custom collector
3. Build Grafana dashboard with panels
4. Set up alert rules

Benefit: Integrates with existing infrastructure monitoring, enabling correlation between email issues and system health.

Benchmarks for Dashboard Thresholds

Metric	Excellent	Good	Warning	Critical
Delivery rate	>99%	97-99%	95-97%	<95%
Hard bounce rate	<0.1%	0.1-0.5%	0.5-2%	>2%
Spam complaint rate	<0.02%	0.02-0.1%	0.1-0.3%	>0.3%
Auth pass rate	>99.5%	99-99.5%	95-99%	<95%
Unique open rate	>25%	15-25%	10-15%	<10%
Click rate	>3%	2-3%	1-2%	<1%

Use conditional formatting to highlight when metrics cross warning/critical thresholds.

Dashboard Review Cadence

Daily (5 minutes):

• Glance at status indicators
• Check for alerts/critical thresholds
• Review yesterday's campaign performance

Weekly (30 minutes):

• Analyze 7-day trends
• Compare to previous weeks
• Note any drift requiring attention
• Update reputation data if manual

Monthly (1 hour):

• Full trend analysis
• Benchmark against targets
• Document notable events
• Plan optimization actions

Practitioner note: The teams with the best deliverability check their dashboard daily, even if just for 2 minutes. The ones who only look monthly are always surprised by problems that should have been caught weeks earlier.

If you want help building a custom deliverability dashboard or need guidance on which metrics matter most for your specific sending profile, schedule a consultation to design a monitoring system tailored to your needs.

Sources

• Google: Looker Studio
• Datadog: Email Monitoring
• SendGrid: Statistics API
• Mailgun: Analytics API

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v1.0 · March 2026