Integrate Apollo with Snowflake

The account_stages table contains account stage values.

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The accounts table includes Apollo account IDs and the minimum fields needed to join account activity to other Apollo and CRM data.

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The activity_log table contains prospecting activity per contact in Apollo, including stage changes, sequence events, and account reassignments.

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The contact_campaign_statuses table shows one row per contact per sequence. Use this table to understand whether contacts are active, paused, finished, or failed through bounces or spam blocks in a sequence. To report on contact status by sequence, aggregate rows in this table rather than relying on sequence-level summary fields.

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The contact_stages table contains contact stage values used to resolve contact stage IDs into readable names.

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The contacts table includes Apollo contact IDs and the minimum fields needed to join contact activity to other Apollo and CRM data. This table does not include contact email addresses or phone numbers.

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The conversations table contains conversation intelligence data, including Apollo-calculated metrics such as talk duration, user, and meeting information.

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The email_message_events table contains email engagement events, such as opens, clicks, replies, bounces, and unsubscribes.

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The email_messages table contains email activity generated through Apollo.

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The id_mapping table maps Apollo record IDs to CRM record IDs for cross-system reporting. This table may be blank if you don't have a CRM integration connected to Apollo.

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The job_change_events table contains detected job changes for contacts.

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The labels table contains label definitions available in Apollo.

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The meeting_identified_events table links meetings to prospecting activities for attribution reporting.

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The meetings table contains meeting activity and booking information.

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The opportunities table contains Apollo deal records and key deal attributes.

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The opportunity_pipelines table contains deal pipeline definitions.

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The opportunity_stages table contains deal stage definitions.

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The phone_call_outcomes table contains call outcomes used in Apollo with the dialer.

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The phone_calls table contains dialer and call activity data.

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The sequence_steps table contains individual steps within Apollo sequences.

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The sequence_templates table contains email templates used in Apollo sequences.

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The sequence_touches table contains records of sequence touch activity across contacts in a sequence.

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The sequences table contains Apollo sequence definitions and performance metrics.

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The tables_status table contains refresh and synchronization information for shared tables.

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The tasks table contains task creation, completion, and due date information.

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The users table contains Apollo user information and is useful for resolving user IDs throughout the shared dataset.

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Use the sequences table to compare sequence performance across delivered emails, opens, clicks, replies, bounces, and unsubscribes.

SELECT
  _id AS sequence_id,
  name,
  stats_unique_delivered,
  stats_unique_opened,
  stats_unique_clicked,
  stats_unique_replied,
  stats_unique_bounced,
  stats_unique_unsubscribed,
  ROUND(stats_unique_replied / NULLIF(stats_unique_delivered, 0) * 100, 2) AS reply_rate
FROM sequences
ORDER BY stats_unique_delivered DESC;

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Use contact_campaign_statuses to understand how many contacts are active, paused, finished, or failed in each sequence.

SELECT
  emailer_campaign_id,
  status,
  failure_reason,
  COUNT(*) AS contacts
FROM contact_campaign_statuses
GROUP BY
  emailer_campaign_id,
  status,
  failure_reason
ORDER BY contacts DESC;

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Use email_message_events to count opens, clicks, replies, bounces, and unsubscribes. For open and click reporting, filter out likely bot activity with self_caused = FALSE.

SELECT
  type_cd,
  COUNT(*) AS events
FROM email_message_events
WHERE actual_created_at >= DATEADD(day, -30, CURRENT_DATE())
  AND (
    type_cd NOT IN ('open', 'click')
    OR self_caused = FALSE
  )
GROUP BY type_cd
ORDER BY events DESC;

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Use tasks to track completed tasks and on-time completion.

SELECT
  user_id,
  COUNT(*) AS completed_tasks,
  COUNT_IF(completed_at <= due_at) AS completed_on_time
FROM tasks
WHERE status_cd = 'completed'
  AND completed_at IS NOT NULL
  AND due_at IS NOT NULL
GROUP BY user_id
ORDER BY completed_tasks DESC;

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Use phone_calls and phone_call_outcomes to summarize call results by outcome and sentiment.

SELECT
  pco.name AS outcome,
  pco.sentiment,
  COUNT(*) AS calls
FROM phone_calls pc
LEFT JOIN phone_call_outcomes pco
  ON pc.phone_call_outcome_id = pco._id
WHERE start_time >= DATEADD(day, -30, CURRENT_DATE())
GROUP BY
  pco.name,
  pco.sentiment
ORDER BY calls DESC;

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Use meetings to count meetings booked from emails and phone calls.

SELECT
  COUNT(*) AS total_meetings,
  COUNT_IF(in_response_to_emailer_message_id IS NOT NULL) AS meetings_from_email,
  COUNT_IF(in_response_to_phone_call_id IS NOT NULL) AS meetings_from_call
FROM meetings
WHERE created_at >= DATEADD(day, -30, CURRENT_DATE());

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Use conversations to report on conversation volume, duration, processing status, and recording details by user.

SELECT
  user_id,
  COUNT(*) AS conversations,
  ROUND(AVG(duration), 2) AS avg_duration_seconds,
  ROUND(AVG(longest_customer_monologue_duration), 2) AS avg_longest_customer_monologue_duration,
  COUNT_IF(state = 'insights_generated') AS conversations_with_insights,
  COUNT_IF(is_private = TRUE) AS private_conversations,
  COUNT_IF(failure_code IS NOT NULL) AS failed_conversations
FROM conversations
WHERE start_time >= DATEADD(day, -30, CURRENT_DATE())
GROUP BY user_id
ORDER BY conversations DESC;

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