The Syntasa Audience Module empowers businesses to create, manage, and activate dynamic customer segments with precision and agility. By combining behavioral, demographic, and transactional data, this module enables marketers to build audiences tailored to specific campaigns, personalize experiences, and drive measurable outcomes.
Below, we break down the core components of the Audience Module—Data Layer, Attributes, Audiences, and Audience Sync—and explain how they work together to turn raw data into actionable insights.
Data Layer - The foundation
The Data Layer is the backbone of the Audience Module, but it operates exclusively within the Syntasa environment. Before configuring the Data Layer, data must first be ingested into Syntasa’s production database using Syntasa’s native applications. These applications enable seamless data ingestion from external sources such as databases, cloud storage (e.g., AWS S3, Google Cloud) etc. Once the data is securely stored in Syntasa’s production database as structured datasets, it becomes accessible to the Data Layer. Without a properly configured Data Layer, Attributes and Audiences cannot function, as they rely on its structured tables and dependencies to pull relevant data. To learn more about Data Layer, visit Data Layer Documentation
Attributes - The Building Blocks
Attributes are the criteria used to define audience characteristics. Think of them as individual traits or behaviors—such as purchased in the last 30 days or visited a specific webpage—that collectively shape audience segments.
Examples of some common attributes are:
- E-commerce actions (i.e. cart add, cart remove, checkout, purchase)
- Viewed product information (i.e. brand, price, category)
- ML and rules-based model scores (i.e. raw scores, percentiles, categorized)
- Key online behaviors (i.e. purchased within last 30 days, opened multiple accounts in previous 12 months, abandoned cart yesterday, more than two site visits per day)
- Key offline behaviors (i.e. in-store purchase last 14 days, visited a sales rep last three months, called support last 30 days, returned an item last six months)
- Third-party user traits
Once attributes are created, Attributes are executed to validate their logic, and results are stored in dedicated tables for seamless integration into Audiences. To learn more about Attributes, visit Attributes Documentation
Audiences - Dynamic Segmentation
Audiences are customer segments built by combining multiple Attributes with logical operators (AND, OR, NOT). For example, an Audience could target users who abandoned their cart (Attribute 1) AND opened a promotional email (Attribute 2).
Examples of some common audiences are:
- Users that interacted with HP laptops and did not purchase in the last seven days.
- Any customer with a lifetime value greater than 1 million that have active IRA and College Savings accounts.
- Subscribers that have been signed up for premium channels for more than 12 months.
- Customers that have searched for products online and purchased from a sales rep in the last 30 days.
- Visitors that have visited a property within the last 14 days, did not make a purchase in the last 14 days and have ML model score showing a high propensity to purchase an Apple product.
After Audience execution, Audience membership lists are stored in results tables, which detail qualifying users and their associated metrics. These tables serve as the source for activation or further analysis. To learn more about Audience, please refer Audience Documentation
Audience Sync: Activation
Audiences deliver real value only when activated across external platforms. Syntasa’s Audience Sync feature enables seamless integration with tools like Google Ads, Facebook, CRM systems, and more by syncing audience data in real time. Through configurable Sync Apps, users can define destination platforms, mapping rules, and sync schedules to ensure that audience data remains fresh and actionable. Behind the scenes, Sync processes manage the logic to select defined audiences and push them to downstream APIs, including DSPs, A/B testing tools, and analytics dashboards.
Common integration examples include Facebook, Google Analytics, Adobe Analytics, Nielsen, Yahoo!, Tableau, Looker, Adobe Core Services, Adobe Target, and Airship, empowering teams to use audience data effectively for campaigns, retargeting, and personalization.
To learn more about Audience Sync, please refer Audience Sync Documentation
In nutshell:
- Data Layer ingests and structures raw data.
- Attributes define granular traits from this data.
- Audiences combine Attributes into segments.
- Audience Sync pushes these segments to downstream systems such as Facebook, google etc. .