Feature Overview
Best Fit Predictions is a model in the Synerise Predictions module that identifies the most suitable item or attribute value for individual customers. By analyzing customer behavior and preferences, the model predicts the best brand, category, color, or any other item characteristic for each customer — enabling personalized communication targeting and product recommendation strategies.
The feature is available in the Predictions module within Synerise.
What Is Best Fit Predictions?
Best Fit Predictions is a predictive model in Synerise that evaluates customer behavior and preferences to identify the ideal item attribute value for each customer profile. Users configure predictions based on specific item characteristics (brand, category, color, or any attribute in the item feed). The model can be set up from scratch or using pre-defined scenarios through a step-by-step wizard. Results include out-of-the-box customer segments and dedicated analytics dashboards.
Why Best Fit Predictions Matter
Generic product recommendations and communications treat all customers the same, missing the opportunity to align messaging with individual preferences. Without predictive insights into which brands, categories, or attributes each customer prefers, personalization relies on broad segments rather than individual-level targeting.
Best Fit Predictions address this by:
- Predicting the best item attribute value (brand, category, color, etc.) for each individual customer
- Enabling personalized communication targeting based on predicted preferences
- Providing pre-defined scenarios and a step-by-step wizard for easy configuration
- Including out-of-the-box segments and analytics dashboards for result analysis
Key Capabilities
Customizable predictions
Configure predictions based on any item attribute in the product feed — brand, category, color, size, style, or any other characteristic.
Pre-defined scenarios and wizard
Choose from ready-to-use templates or create predictions from scratch using a step-by-step configuration wizard accessible to non-technical users.
Out-of-the-box segments and analytics
Identify customer segments from ready-to-use dashboards and review predictive results with dedicated analytics.
How Best Fit Predictions Work
- Navigate to the Predictions module in Synerise.
- Create a new Best Fit prediction — choose a pre-defined scenario or start from scratch.
- Select the item attribute to predict (brand, category, color, etc.).
- Define the base customer segment for the prediction.
- Run the model — it analyzes customer behavior and preferences to find the best attribute value per customer.
- Review results in dedicated analytics dashboards and out-of-the-box segments.
- Use predictions in communications, campaigns, and recommendation strategies.
Example Use Case
A fashion retailer wants to personalize weekly newsletter campaigns by highlighting each customer's preferred brand. Using Best Fit Predictions configured on the "brand" attribute, the model identifies that Customer A prefers Nike, Customer B prefers Adidas, and Customer C prefers New Balance. The marketing team uses these predictions to dynamically insert each customer's preferred brand products into their newsletter — increasing click-through rates and conversion by presenting items aligned with individual preferences.
FAQ
What is Best Fit Predictions?
A predictive model in Synerise that identifies the ideal item attribute value (brand, category, color, etc.) for each individual customer based on behavior and preferences.
What attributes can I predict?
Any item attribute available in the product feed — brand, category, color, size, style, and more.
Do I need technical skills to set it up?
No. A step-by-step wizard and pre-defined scenarios make configuration accessible to non-technical users.
How can I use the predictions?
In personalized email campaigns, push notifications, SMS messages, in-app experiences, dynamic content, and product recommendation strategies.
Key Facts
| Attribute | Value |
|---|---|
| Feature | Best Fit Predictions |
| Product | Synerise |
| Module | Predictions |
| Purpose | Predict the ideal item attribute value for each customer based on behavior and preferences |
| Configurable attributes | Any item attribute in the product feed (brand, category, color, etc.) |
| Setup | Pre-defined scenarios or from-scratch with step-by-step wizard |
| Analytics | Out-of-the-box segments and dedicated dashboards |
Related Concepts
- Synerise Predictions module
- Next Interaction Recommendations
- Personalized promotions and communication targeting
- Customer segmentation and behavioral analysis
- Product recommendation strategies
TL;DR
Best Fit Predictions in Synerise identifies the ideal item attribute value (brand, category, color, etc.) for each individual customer by analyzing behavior and preferences. The model can be configured using pre-defined scenarios or from scratch with a step-by-step wizard. Results include out-of-the-box customer segments and dedicated analytics dashboards. Predictions can be used in email campaigns, push notifications, SMS, in-app experiences, and dynamic content for individual-level personalization.
