You can connect Insider One data to Snowflake to analyze customer engagement events together with your internal datasets. This integration allows teams to query Insider One event data directly in Snowflake and combine it with other sources, such as CRM, purchase, or product data, for analytics and reporting.
This guide covers the following topics:
Why connect Insider One and Snowflake
Customers interact with brands across multiple channels, including email, SMS, push notifications, web push, WhatsApp, OnSite messages, in-app messages, loyalty programs, recommendations, and referrals. Each interaction generates event data that can be analyzed to better understand customer behavior and engagement.
The Insider One → Snowflake Secure Data Share allows you to access Insider One event data directly in your Snowflake environment. Because the integration uses Snowflake Secure Data Sharing, the data becomes available without exporting, copying, or replicating it between systems. This allows you to query Insider One events and combine them with other datasets such as purchase history or CRM data.
Best Practices
The following best practices explain how to work with Insider One event data in Snowflake and use it for analysis, reporting, and advanced data workflows.
Activate Your Unified Customer View
To start using Insider One data in Snowflake, you first need to activate the Insider One → Snowflake Secure Data Share. Once enabled, your Snowflake account receives access to raw event data generated in Insider One across supported channels.
Available data includes:
A shared dataset One live dataset (for example:
DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE) that contains engagement events such asEVENT_NAME,TIMESTAMP,INSIDER_ID, and channel attributes.Direct access to Insider One event data without requiring exports, ETL pipelines, or replication.
A one-way, read-only data share between Insider One’s Snowflake account and your Snowflake account.
Why it matters:
When Insider One engagement data is available in one place, your teams can analyze performance across channels using a consistent dataset. This helps marketing, data, and analytics teams align on shared definitions and reporting, and reduces the need for separate exports or duplicated data sources.
Action: Contact the Insider One team to enable the Secure Data Share in your Snowflake account, or navigate to Snowflake Marketplace Listing and click Get.
Combine Insider One Data with your internal datasets
Once Insider One event data is available in Snowflake, you can combine it with other internal datasets, such as orders, CRM data, loyalty data, or product catalog information.
This allows teams to answer questions such as:
Which channels generate the highest engagement or conversion rates for specific user cohorts?
How does messaging frequency affect conversions or unsubscribe behavior?
How do users engage when they receive messages across multiple channels?
Example query: Monthly Email Delivery Frequency
Use the query below to analyze monthly open-rate trends and evaluate email engagement patterns.
WITH EmailActivity AS (
SELECT
A_EMAIL,
DATE_TRUNC('MONTH', "TIMESTAMP") AS MonthYear,
SUM(CASE WHEN EVENT_NAME = 'email_delivered' THEN 1 ELSE 0 END) AS Delivered,
SUM(CASE WHEN EVENT_NAME = 'email_open' THEN 1 ELSE 0 END) AS Opened
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE EVENT_NAME IN ('email_delivered', 'email_open')
GROUP BY A_EMAIL, MonthYear
)
SELECT
MonthYear,
COUNT(*) AS Active_Recipients,
SUM(CASE WHEN Opened > 0 THEN 1 ELSE 0 END) AS Openers,
ROUND(SUM(CASE WHEN Opened > 0 THEN 1 ELSE 0 END) * 100.0 / COUNT(*), 2) AS Open_Rate
FROM EmailActivity
GROUP BY MonthYear
ORDER BY MonthYear;
Make data accessible across teams
When Insider One event data is available in Snowflake, it can be used by different teams across the organization for analysis and reporting.
For example:
Marketing teams can visualize channel performance in tools such as Tableau, Looker, or Power BI.
Product and data science teams can build predictive models such as churn prediction, propensity scoring, or look-alike modeling.
Finance and operations teams can analyze how campaigns influence revenue and retention by joining Insider One event data with sales datasets.
Because the integration uses Snowflake Secure Data Sharing, all teams can access the same governed dataset without exporting or duplicating data.
Action: Create shared dashboards using Insider One engagement metrics to enable consistent reporting and reduce manual requests for analysis.
Measure and Optimize Engagement
Querying Insider One events in Snowflake allows teams to analyze how different messaging channels perform and how users interact with campaigns.
For example, you can evaluate:
Which segments respond most frequently to SMS campaigns
How engagement correlates with purchases or other conversion events
Which users become inactive and may require re-engagement through other channels
Example query: User-Level SMS Performance
Use this query to identify users with the highest SMS engagement rates.
SELECT
INSIDER_ID,
A_PHONE_NUMBER,
SUM(CASE WHEN EVENT_NAME = 'sms_delivered' THEN 1 ELSE 0 END) AS Delivered,
SUM(CASE WHEN EVENT_NAME = 'sms_click' THEN 1 ELSE 0 END) AS Clicked,
ROUND(
SUM(CASE WHEN EVENT_NAME = 'sms_click' THEN 1 ELSE 0 END) * 100.0 /
NULLIF(SUM(CASE WHEN EVENT_NAME = 'sms_delivered' THEN 1 ELSE 0 END), 0),
2
) AS CTR
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE EVENT_NAME IN ('sms_delivered', 'sms_click')
GROUP BY INSIDER_ID, A_PHONE_NUMBER
ORDER BY CTR DESC;
Example query: Multi-Channel User Overview
Use the query below to:
Identify users who engage across multiple messaging channels
Analyze the distribution of engagement across SMS, email, and push notifications
Build dashboards that visualize multi-channel engagement patterns
SELECT
INSIDER_ID,
COUNT_IF(EVENT_NAME LIKE '%delivered%') AS Total_Delivered,
COUNT_IF(EVENT_NAME LIKE '%click%' OR EVENT_NAME LIKE '%open%') AS Total_Engaged,
COUNT_IF(EVENT_NAME LIKE 'push_%') AS Push_Events,
COUNT_IF(EVENT_NAME LIKE 'email_%') AS Email_Events,
COUNT_IF(EVENT_NAME LIKE 'sms_%') AS SMS_Events
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE "TIMESTAMP" >= DATEADD('day', -30, CURRENT_DATE())
GROUP BY INSIDER_ID
ORDER BY Total_Engaged DESC;
Use Insider One data for AI, personalization, and growth
When Insider One event data is available in Snowflake, teams can use it to build predictive models and advanced analytics workflows. Combining engagement data with datasets such as purchases, CRM records, or loyalty information allows teams to analyze customer behavior and generate predictive insights.
Common use cases include:
Churn prediction → Identify customers whose engagement levels are decreasing across messaging channels.
Send-time optimization → Train models to determine the most effective delivery windows for campaigns.
Offer personalization → Combine engagement signals with purchase data to determine the next best offer or action.
Customer lifetime value analysis → Evaluate how multi-channel engagement relates to repeat purchases and long-term customer value.
Action: Use Insider One event data in Snowflake to support use cases such as look-alike modeling, customer lifetime value forecasting, or predictive re-engagement strategies.
Use Cases for Insider Data in Snowflake
The following examples demonstrate how Insider One event data in Snowflake can be used to analyze campaign performance, user engagement, and customer behavior.
Identify Email Campaigns with the Highest Unique Engagement
This analysis shows which email campaigns generated the highest number of unique user clicks during the last 30 days. It helps you evaluate campaign performance and compare engagement levels across campaigns.
Example query
SELECT
A_CAMPAIGN_ID,
A_CAMPAIGN_NAME,
COUNT(DISTINCT A_EMAIL) AS Unique_Clicks
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE EVENT_NAME = 'email_click'
AND "TIMESTAMP" >= DATEADD('day', -30, CURRENT_DATE())
GROUP BY A_CAMPAIGN_ID, A_CAMPAIGN_NAME
ORDER BY Unique_Clicks DESC;
You can extend this analysis to:
Identify your highest-performing campaign and reuse winning elements (subject line, CTA, creative).
Slice by audience or channel to understand who responded and why.
Compare results by send day, send time, or promotion type.
Extend the query to also calculate opens, deliveries, and CTR for a deeper view.
Join with purchase data to see which campaigns translated into a revenue lift.
Analyze messaging frequency and engagement
This analysis examines how messaging frequency relates to user engagement. By combining Insider One event data with other datasets in Snowflake, such as lifetime value or churn indicators, teams can evaluate how send frequency affects engagement levels.
Example query
WITH Activity AS (
SELECT
INSIDER_ID,
COUNT_IF(EVENT_NAME LIKE '%delivered%') AS Total_Sends,
COUNT_IF(EVENT_NAME LIKE '%click%' OR EVENT_NAME LIKE '%open%') AS Total_Engagements
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE "TIMESTAMP" >= DATEADD('day', -30, CURRENT_DATE())
GROUP BY INSIDER_ID
)
SELECT
CASE
WHEN Total_Sends <= 2 THEN 'Low Frequency'
WHEN Total_Sends BETWEEN 3 AND 6 THEN 'Optimal Frequency'
ELSE 'High Frequency'
END AS Frequency_Bucket,
COUNT(*) AS Users,
ROUND(
AVG(Total_Engagements * 100.0 / NULLIF(Total_Sends, 0)),
2
) AS Avg_Engagement_Rate
FROM Activity
GROUP BY Frequency_Bucket
ORDER BY Users DESC;
Compare Engagement Between Loyalty Members and Non-Members
By combining Insider One engagement events with loyalty program data stored in Snowflake, your teams can analyze how loyalty members interact with campaigns compared to non-members.
This type of analysis can help answer questions such as:
Do loyalty members engage more frequently than non-members?
Which channels generate the most engagement among loyalty members?
Do loyalty members interact with more products or campaigns during their sessions?
Example query
WITH EngagementSummary AS (
SELECT
INSIDER_ID,
COUNT_IF(EVENT_NAME LIKE '%delivered%') AS Deliveries,
COUNT_IF(EVENT_NAME LIKE '%open%' OR EVENT_NAME LIKE '%click%') AS Engagements,
MAX("TIMESTAMP") AS Last_Engagement
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE "TIMESTAMP" >= DATEADD('day', -30, CURRENT_DATE())
GROUP BY INSIDER_ID
)
SELECT
CASE
WHEN c.LOYALTY_STATUS = 'Member' THEN 'Loyalty Member'
ELSE 'Non-Member'
END AS Cohort,
COUNT(a.INSIDER_ID) AS Users,
AVG(Engagements) AS Avg_Engagements,
ROUND(
AVG(Engagements * 100.0 / NULLIF(Deliveries, 0)),
2
) AS Avg_Engagement_Rate,
MAX(Last_Engagement) AS Most_Recent_Engagement
FROM EngagementSummary a
JOIN CUSTOMER_PROFILE_TABLE c
ON a.INSIDER_ID = c.INSIDER_ID
GROUP BY Cohort
ORDER BY Cohort;
You can extend this analysis to:
Compare engagement across channels such as email, SMS, push notifications, or WhatsApp.
Join the dataset with order data to analyze conversion differences between members and non-members.
Build dashboards that track engagement across lifecycle stages such as new, active, repeat, or lapsed users.
Predictive segmentation and AI analysis
Insider One behavioral event data stored in Snowflake can also support predictive modeling and advanced segmentation. Data science teams can combine Insider One engagement data with loyalty, purchase, or support datasets to build models using tools such as Snowpark, Databricks, or Cortex.
Users can be segmented based on engagement intensity, recency, or channel activity. These segments can then be exported to Insider One or other systems for campaign execution or personalization workflows.
Example query
SELECT
INSIDER_ID,
MAX("TIMESTAMP") AS Last_Engagement,
COUNT_IF(EVENT_NAME LIKE '%click%' OR EVENT_NAME LIKE '%open%') AS Engagements,
COUNT_IF(EVENT_NAME LIKE '%delivered%') AS Deliveries,
ROUND(Engagements * 100.0 / NULLIF(Deliveries,0), 2) AS Engagement_Rate
FROM DATA_PRODUCT_SAMPLE_DATA.DATA_PRODUCT_SAMPLE_DATA_TABLE
WHERE "TIMESTAMP" >= DATEADD('day', -90, CURRENT_DATE())
GROUP BY INSIDER_ID;
You can extend this analysis to:
Label users as Active, At Risk, or Dormant based on engagement recency.
Export segments to Insider One for predictive re-engagement or personalization campaigns.
Use the dataset in machine learning workflows for churn prediction or lifetime value analysis.
Next Steps
Enable your Insider One → Snowflake Secure Data Share in your Snowflake account. Contact the Insider One team if you need assistance with the setup.
Run the example queries in this guide to explore the available Insider One event data.
Connect your BI or analytics tool to Snowflake to visualize engagement metrics and share insights with internal teams.
Work with the Insider One team and your Snowflake account manager to identify additional reporting or analytics use cases.