Grouping

Overview

The Grouping field provides a flexible way to categorize or segment data beyond standard geographic dimensions like Country and Region. It acts as a placeholder for any natural grouping relevant to your business, such as product lines, customer segments, sales channels, store locations, or custom hierarchies. This allows for more granular analysis, enabling filtering in dashboards like Effect and Activities, and forms part of the Modeling Combination for targeted modeling.

Unlike Region, which can benefit from ISO 3166-2 alignment for integrations (e.g., with Weather), Grouping has no enforced standards, offering complete freedom to tailor it to your operational structure. If no additional segmentation is needed, default to "all" for simplicity.

Data Requirements

• Type: String (free text; no restrictions on format, length, or content).
• Validation: Only the following characters are allowed: 0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZåäöüøæÆÄÅÖÜßØ()_+-

For ungrouped or aggregated data:

• Use "all" to indicate no further segmentation.

Examples

• "Product Line A": Grouping by product categories.
• "Enterprise Customers": Segmenting by customer type.
• "Online Channel": Distinguishing sales channels.
• "Store-123": Granular tracking of individual stores or outlets (e.g., as a sub-layer below regions).
• "all": Default for nationwide or unsegmented entries.
• "Holiday Campaign": Custom grouping for seasonal promotions.

Best Practices

• Business Alignment: Define groupings based on how your organization structures data (e.g., align with CRM categories or inventory systems) to maximize relevance in modeling and reporting.
• Consistency: Use uniform naming across all files (e.g., always "Store-123" instead of varying "Store123" or "Location 123") to enable accurate filtering and aggregation.
• Granularity: Leverage for finer detail than regions (e.g., individual stores within a state) or broader custom layers (e.g., "B2B" vs. "B2C"). Combine with Region for hierarchical views.
• Default Usage: Stick to "all" if segmentation isn't needed to simplify datasets and reduce complexity.

Common Issues and Troubleshooting

• Inconsistencies: Variant spellings (e.g., "Prod A" vs. "Product A") can scatter data—standardize during preparation.
• Over-Segmentation: Too many unique groupings may dilute insights; consolidate similar ones (e.g., group small stores into "Regional Outlets").
• Blanks vs. "all": Blanks may cause optional field issues; prefer "all" for clarity and consistency.
• Modeling Impacts: Inconsistent groupings can affect Modeling Combinations; test small datasets first.

For related fields, see Country or Region. If using ISO-like formats for regions, consider extending similar practices here for internal consistency, though it's not required.