How to build Outreach sales-engagement dashboards in Metabase

{
  "mcpServers": {
    "outreach": {
      "url": "https://your-outreach-mcp-endpoint/mcp"
    }
  }
}

# Install the Metabase CLI
npm install -g @metabase/cli

# Log in (opens your browser; requires Metabase v62+)
mb auth login --url https://your-metabase.example.com

# Load an Outreach CSV export — creates a table AND a model
mb upload csv --file outreach-sequences.csv --collection root

# Refresh that same table later from a new export
mb upload replace <table-id> --file outreach-sequences.csv

Create a polished Metabase dashboard for Outreach sales-engagement analytics.
Work end to end: get the data into Metabase if it isn't there yet, then build.

Goal: Help sales leaders understand the outbound funnel, sequence performance,
email deliverability, and rep activity from Outreach data.

Step 1 — Find or load the data:
- First, check what already exists in Metabase (search for Outreach tables and
  models). If durable Outreach data is already present — synced from a warehouse
  or uploaded earlier — use it and skip to Step 2.
- If nothing is there, pull it with the Outreach MCP server (scope access so
  analysis stays read-oriented): prospects, sequences, mailing activity, calls,
  tasks, and opportunities. Write each result to a CSV, then load it with the
  Metabase CLI — run "mb upload csv --file <export>.csv" so each upload creates a
  table and a ready-to-query model. Use "mb upload replace <table-id> --file
  <export>.csv" to refresh an existing table instead of creating duplicates.

Step 2 — Inspect before querying:
Outreach CSV exports are usually flat and pre-aggregated (one row per sequence or
prospect, with columns like delivered, open rate, reply rate, and meetings).
Warehouse tables are raw and event-grained (a mailings table with sent, delivered,
opened, replied, bounced, opted-out events). Inspect the actual tables and column
names first; do not assume exact names or that an event-level table exists.

Important:
- Build on whatever data is present; don't claim Metabase connects natively to
  Outreach — it reads a database or CLI-uploaded tables.
- If the data already provides rates, chart them directly; only recompute open and
  reply rates over the delivered (not sent) base when raw counts are available, and
  track bounce rate separately.
- Distinguish reply rate from positive-reply rate, and count a "meeting booked"
  from a consistent signal — state which one.
- Report rates with denominators visible; small sequences are noisy.
- Only build a card if its underlying column/metric exists in the data.
- A single CSV is a point-in-time snapshot: only build trend cards if there is a
  usable date column or multiple periods have been uploaded.

Dashboard title: Outreach Sales Engagement Overview

Sections:
1. Executive summary (KPI cards): Prospects enrolled; Reply rate; Meetings booked;
   Bounce rate; Opt-out rate; Opportunities created.
2. Funnel: Enrolled → contacted → replied → meeting; opportunities created.
3. Sequences: Open and reply rate by sequence; reply rate by step; positive-reply
   rate.
4. Deliverability: Bounce rate by mailbox; opt-out rate; delivered vs. sent.
5. Activity: Emails and calls by rep; tasks completed; accounts touched.

Filters: Sequence, Rep, Mailbox, Date range.

Reuse the models Metabase auto-created from uploaded CSVs, or (for a warehouse)
create reusable models: modeled_outreach_prospects, modeled_outreach_sequences,
modeled_outreach_mailings, modeled_outreach_calls, and
modeled_outreach_opportunities.

Output: Build the dashboard if you have permission; otherwise provide the exact
questions, SQL, model definitions, and layout. Include caveats for any metric
that cannot be calculated from the available data. Reconcile totals against
Outreach's own analytics. Keep it practical, dense, and executive-readable.

Both based on delivered mailings, so bounces don't distort them.

-- Open and reply rate by sequence (delivered as the base)
SELECT
  s.name AS sequence,
  COUNT(*) FILTER (WHERE m.status <> 'bounced')            AS delivered,
  ROUND(100.0 * COUNT(*) FILTER (WHERE m.opened_at IS NOT NULL)
    / NULLIF(COUNT(*) FILTER (WHERE m.status <> 'bounced'), 0), 1) AS open_rate_pct,
  ROUND(100.0 * COUNT(*) FILTER (WHERE m.replied_at IS NOT NULL)
    / NULLIF(COUNT(*) FILTER (WHERE m.status <> 'bounced'), 0), 1) AS reply_rate_pct
FROM modeled_outreach_mailings m
JOIN modeled_outreach_sequences s ON s.id = m.sequence_id
WHERE m.sent_at >= CURRENT_DATE - INTERVAL '90 days'
GROUP BY s.name
ORDER BY delivered DESC;

Distinct prospects with a booked meeting over the last 90 days.

-- Meetings booked by rep over the last 90 days
SELECT
  u.name AS rep,
  COUNT(DISTINCT mt.prospect_id) AS meetings_booked
FROM modeled_outreach_meetings mt
JOIN modeled_outreach_users u ON u.id = mt.owner_id
WHERE mt.booked_at >= CURRENT_DATE - INTERVAL '90 days'
GROUP BY u.name
ORDER BY meetings_booked DESC;

A deliverability guardrail; watch mailboxes creeping up.

-- Bounce rate by mailbox
SELECT
  m.mailbox,
  COUNT(*)                                              AS sent,
  COUNT(*) FILTER (WHERE m.status = 'bounced')          AS bounced,
  ROUND(100.0 * COUNT(*) FILTER (WHERE m.status = 'bounced')
    / NULLIF(COUNT(*), 0), 2)                           AS bounce_rate_pct
FROM modeled_outreach_mailings m
WHERE m.sent_at >= CURRENT_DATE - INTERVAL '90 days'
GROUP BY m.mailbox
ORDER BY bounce_rate_pct DESC;