💡Prerequisite knowledge

We recommend that you review the Good Practice Segmentations guide to understand how the segmentation can be used with Discovery Real-Time Segments.

Segmentation Description

This segmentation divides your customers into 3 to 4 segments based on their geographical location.

You might need to adjust segments based on your unique customer base. For example, for an outdoor brand, the segments can be — mountain area, coast area, city area, and others.

Segment Examples

• 🏔️ Mountain explorer
• 🏝️ Coast explorer
• 🏙️ City explorer
• 🌐 All rounder

Does this Segmentation fit my brand

This segmentation is a good fit for your brand if

• You cover a wide range of geographies.
• You can easily generalize and correlate certain shopper preferences with the geographic area. For example, customers located in coastal areas have very different fashion preferences than the ones located in mountain areas.

Segmentation Evaluation

Segments Criteria - How are Segments Defined

The geo-location data comes from session events. We can divide this data into different groups using the session_start events.

For instance

• The 'City Explorer' segment aggregates the last session_start data of shoppers located in the largest cities where the customers are located.
• The 'Mountain Explorer' segment aggregates the last session_start data of shoppers located in mountain areas.
• The 'Coast Explorer' segment aggregates the last session_start data of shoppers located in coastal areas.
• The 'All rounder' segment includes the rest of the shoppers who don't fit into the other segments.

Custom Tracking Requirements

Custom tracking is not required for this segmentation.

📘

We recommend that each segment has a size of a minimum of 100,000 daily visitors. This ensures that segments are large enough for Bloomreach Discovery to learn and for the AB tests to get statistically significant results.