Data and Analytics Overview

Overview

The MessageGears platform is designed to leverage your customer data where it lives. Whether the data is in a cloud-native data warehouse (such as Snowflake, BigQuery, or Redshift), or a more traditional platform (like SQL Server, MySQL, Postgres), the platform is designed to connect to the database directly, query customer attributes to support marketing campaigns, and stream campaign activities and results directly back into your data sources, eliminating data silos and synchronization requirements.

Segmentation

Data is used for a number of purposes in the platform. A common use case is segmentation: 

• You can establish base Audiences for common marketing scenarios (for example, give me a list of all users opted in for Push).
• Then use these audiences for further segmentation using Blueprints (for example, target those users who are opted in for Push who have made a purchase in the last 30 days).

User Profile

You can also use our User Profile Lookup to:

• Query your users, search for specific users.
• View historical campaign results for the user you've specified.

Personalization

Data can also be used in our native campaign channels (email, SMS, push, in-app messaging) to drive rich, dynamic personalization. MessageGears offers an incredibly robust set of configuration options to allow users to personalize messages. A few examples of common data elements and situations are:

• Using conditional logic to drive Campaign Personalization.
• Using our Hosted Data and External APIs to drive advanced campaign personalization.

Analytics

Once you have activated your campaigns, analyzing the results is the best way of creating an effective marketing strategy.  Dashboards are a hub of information displaying the recent activity of Accelerator. Within MessageGears Analytics, there are four different levels of reporting, each giving you a deeper insight into campaign performance on an Account level, Campaign, Individual Job and any Experiments you might be running.