Tapestry Personalizer

Tapestry Personalizer is a user experience personalization engine built on your visitor data. With Personalizer, you can boost your engagement by improving your users’ and visitors’ experiences. Personalizer captures critical behavioral signals from users that indicate their content preferences, based on similar individuals. Once a user’s content preferences have been defined, personalized content recommendations are sent from Personalizer to your CMS, where optimal content selections are then served to individuals, leading to increased engagement with your site or app.

Personalizer Components

Data Collection

Site/App behavior
Media targeting and interaction
First-party information

Audience Construction

Heuristic – Define rules to target pre-defined audiences
Algorithmic – Propensity models, look-alike audiences, etc. (See Tapestry Profile)

Personalizer-CMS Connectivity

Personalizer-CMS Connectivity
Content prioritization

Implementation Process

1

Evaluation of metadata

Evaluate and analyze your users’ behavioral data to ensure the highest performance results by the recommendation engine.
2

Close Gaps & Implement Changes

If needed, implement and close data and other infrastructure gaps.
3

Integration of Models

Train recommendation models and integrate them with your site or app to create customized content lists for each user.
4

Insights, Reports & Strategy

Using our reporting dashboard, you will be able to gain insights about your content and users, ensuring maximized user engagement.
5

Always on Testing

Always-on testing and learning mean that models will become smarter over time and keep up with individuals’ changing traits and behaviors.