What goes in an email marketing dashboard in Metabase?

An email marketing dashboard runs the whole program from one screen: whether the list is growing faster than it churns, how campaigns perform, what each send earns, whether mail is actually reaching inboxes, and what the automation flows contribute. It's the weekly review layer above the metric-by-metric detail in an email engagement dashboard.

What does an email marketing dashboard look like?

Here’s the layout this guide builds. Program numbers — subscribers, rates, revenue, complaints — sit at the top for the weekly read. Audience and engagement trends come next, with deliverability beside them because a complaint spike explains an engagement dip more often than content does. Revenue and the campaign table sit at the bottom, where individual sends get compared.

Which cards belong on an email marketing dashboard?

The eight below cover audience, engagement, deliverability, and revenue — the four ways an email program succeeds or quietly fails.

• Program numbers — active subscribers, open and click rates, monthly email revenue, spam complaint rate (numbers)
• Active subscribers over time, weekly (area)
• New subscribers versus unsubscribes per month (bar)
• Open and click rate trend by month (line)
• Deliverability — hard bounce and spam complaint rates (line)
• Email revenue and revenue per recipient per month (combo)
• Automation flow revenue per recipient — welcome, abandoned cart, post-purchase, win-back (row)
• Campaign performance — delivered, open, click, conversions, and revenue per campaign (table)

What data does the dashboard need?

• An email_events table with one row per recipient per event — sent, delivered, opened, clicked, bounced, spam_complaint, unsubscribed — with timestamps and campaign or flow IDs.
• A campaigns table (name, type, subject, sent_at, audience) and a flows table for automations.
• A subscribers table with subscribed_at, unsubscribed_at, and status, to compute list size and net growth over time.
• An orders table with an attribution link back to the campaign or flow, for revenue per send.
• Bounce classification (hard versus soft) — the deliverability cards need hard bounces separated out.

How do you build it?

1. Sync your ESP’s event-level data to the warehouse — the Mailchimp and Klaviyo guides cover connector options — and land orders beside it.
2. Build one Metabase model over email_events that defines every rate once: opens and clicks over delivered, bounces over sent, complaints over delivered.
3. Pick and encode the revenue attribution rule (say, click-to-purchase within 5 days) in the model, so campaign revenue and monthly revenue always agree.
4. Compute daily list size from the subscribers table as a running sum of subscribes minus unsubscribes and hard bounces, and snapshot it if your ESP overwrites status.
5. Add filters for date range, campaign type, and audience list, then wire an alert on the spam complaint card at 0.1% so deliverability problems don’t wait for the weekly review.

Example card SQL

SELECT
c.campaign_name,
c.sent_at::date                              AS send_date,
COUNT(*) FILTER (WHERE e.event = 'delivered') AS delivered,
ROUND(
  100.0 * COUNT(DISTINCT e.recipient_id)
    FILTER (WHERE e.event = 'clicked')
  / NULLIF(COUNT(*) FILTER (WHERE e.event = 'delivered'), 0), 2
)                                            AS click_rate_pct,
ROUND(
  100.0 * COUNT(*) FILTER (WHERE e.event = 'bounced')
  / NULLIF(COUNT(*) FILTER (WHERE e.event = 'sent'), 0), 2
)                                            AS bounce_rate_pct,
SUM(o.order_total) FILTER (
  WHERE o.ordered_at <= e.event_at + INTERVAL '5 days'
)                                            AS attributed_revenue,
ROUND(
  SUM(o.order_total)
  / NULLIF(COUNT(*) FILTER (WHERE e.event = 'delivered'), 0), 2
)                                            AS revenue_per_recipient
FROM campaigns c
JOIN email_events e USING (campaign_id)
LEFT JOIN orders o
ON o.customer_id = e.recipient_id
AND o.attributed_campaign_id = c.campaign_id
WHERE c.sent_at >= NOW() - INTERVAL '90 days'
GROUP BY 1, 2
ORDER BY send_date DESC;

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