Distribution

Distribution data tracks metrics related to your company's physical or operational presence for selling and distributing products or services, such as the number of stores, sales agents, offices, or partners. This information is crucial for Alviss AI to model how your distribution network influences sales, market coverage, and overall business performance.

Examples of distribution metrics include the count of retail outlets, authorized dealers, or online fulfillment centers. Sourced from internal operations data, CRM systems, or supply chain reports, this data allows Alviss AI to incorporate distribution as a driver in attributions, simulations, predictions, and optimizations. For instance, it can quantify how expanding your agent network affects demand or revenue, enabling data-driven decisions on resource allocation and growth strategies.

Data Requirements

The Distribution Data file must include the following columns (headers). All columns are required unless marked as optional:

• Country (string, required): A three-letter country code per ISO 3166 standard (e.g., "SWE" for Sweden), indicating where the distribution metrics apply.
• Region (string, required): The region within the country (e.g., "all" for nationwide or a specific ISO 3166-2 code like "SE-AB" for Stockholm County in Sweden).
• Grouping (string, optional): For additional segmentation, such as product categories, demographics, or sales territories (e.g., "all" if not applicable).
• Date (date, required): The start date of the period for the distribution metrics in ISO 8601 format (YYYY-MM-DD).
• Product (string, required): The name or identifier of the product associated with the distribution (e.g., "Health").
• Channel (string, required): The distribution channel (e.g., "Agents", "Stores", "Offices").
• Value (integer, required): The count of distribution units (e.g., 90). Use whole numbers; handle missing values with blanks or zeros—Alviss AI will flag inconsistencies during upload.

Supported Formats

Data can be uploaded in long (tidy) or wide (pivoted) format. Choose based on your data pipeline:

• Long Format (Recommended for flexibility): Each row represents a single observation (one value per product, channel, date, etc.).

• Wide Format (Useful for spreadsheets): Columns represent combinations of Product and Channel, with rows as dates. The first few rows define fixed attributes (e.g., Country, Region).

Best Practices

• Consistency: Ensure dates align with your project's periodicity (e.g., weekly data if the project is set to weekly granularity). Mismatched granularity will cause upload errors.
• Data Quality: Check for outliers, missing values, or inconsistencies before upload. Use the Activities dashboard to visualize and validate post-upload.
• Granularity Alignment: All data in a project must match the chosen periodicity (set during project creation). For details, see Projects.
• Channel and Product Tracking: Use clear, consistent naming for Channel and Product fields to enable easy filtering and comparison across segments.

For uploading instructions, see Upload Data. If you encounter issues, contact support or refer to the API for programmatic uploads.