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SQL Insights

Create bespoke reporting data models to extract deeper insights, optimize strategies, and adapt analytics to meet specific business needs with Data Distiller’s SQL Insights. Use the SQL Insights capability to enhance transparency and gain operational insights from your ÃÛ¶¹ÊÓƵ Experience Platform data across dimensions such as profiles, audiences, campaigns, journeys, entitlements, and consent. This capability provides a versatile, adaptive solution to tailor your organization’s reporting data models to align with your specific business needs.

To visualize your SQL Insights you can use query pro mode to conduct complex analysis with custom SQL queries and transform your data into easily interpretable charts. Use query pro mode to create bespoke insights and visulaizations on your dashboards and cater to both technical and non-technical audiences by downloading your insights as CSV files.

This document covers the use cases, essential capabilities, and required steps to develop an SQL insights dashboard with Data Distiller.

Prerequisites

This tutorial uses user-defined dashboards to visualize data from your custom data model within the Platform UI. See the user-defined dashboards documentation to learn more about this feature.

Getting started

The Data Distiller SKU is required to build a custom data model for your reporting insights and to extend the Real-Time CDP data models that hold enriched Platform data. See the packaging, guardrails, and licensing documentation that relates to the Data Distiller SKU. If you do not have the Data Distiller SKU, contact your ÃÛ¶¹ÊÓƵ customer service representative for more information.

SQL Insights use cases use-cases

Below are common use cases that can be effectively addressed through SQL Insights in Data Distiller.

Profile and audience usage transparency usage-transparency

Challenge: How to break down Key Performance Indicators (KPIs) by specific criteria like business units, loyalty status, or Customer Lifetime Value (CLTV).

SQL Insights Solution: Data Distiller enables the extension of reporting data models in ÃÛ¶¹ÊÓƵ Experience Platform, facilitating the addition of custom profile attributes such as CLTV or loyalty status.

Consent anomaly tracking consent-anomaly-tracking

Challenge: How to apply audience overlap and size trendline reports to customized consent attributes for channels like email, SMS, and phone.

SQL Insights Solution: The reporting data model can be extended to track changes in consent preferences over time. This involves building additional fact and dimension tables to trend consent preferences and scheduling incremental data refresh.

Optimize audience segmentation strategy optimize-audience-segmentation-strategy

Challenge: How to integrate Machine Learning (ML) model-generated propensity scores into their audience KPI reports.

SQL Insights Solution: Data Distiller allows the inclusion of propensity scores from custom ML models, facilitating the calculation of aggregate scores at the audience level. This data can then be reported alongside standard KPIs.

Audience expansion audience-expansion

Challenge: How to acquire more than just profile counts in audience overlap reports and attain additional demographic data or preferences to guide audience expansion strategies.

SQL Insights Solution: By extending the reporting data model, users can incorporate additional profile attributes, enriching the audience overlap report with relevant demographic data and preferences.

Key capabilities for generating SQL Insights key-capabilities

The illustration below highlights several essential capabilities for generating SQL Insights. These capabilities include:

Steps to create SQL Insights steps-to-create

To develop a SQL Insights dashboard within Data Distiller, follow the step-by-step instructions below.

Next Steps

By reading this document, you now have a better understanding of the use cases, essential capabilities, and necessary steps to develop an SQL insights dashboard with Data Distiller. To continue learning about creating bespoke reporting data models, see the reporting insights data model guide.