Macro

Macroeconomic data includes indicators that reflect broader economic conditions, such as unemployment rates, consumer confidence indexes (CCI), consumer price indexes (CPI), interest rates, currency exchange rates, happiness indexes, or GDP growth. These factors can significantly influence consumer behavior and business performance—for instance, high unemployment might reduce willingness to purchase non-essential goods like new cars, while rising interest rates could affect borrowing and spending.

Often sourced from public databases (e.g., government statistics, World Bank, OECD), financial reports, or third-party providers, this data enables Alviss AI to model external economic impacts on your KPIs. By incorporating macroeconomic indicators, you can isolate cyclical or structural effects in attributions, simulations, predictions, and optimizations, leading to more robust strategies that account for market conditions beyond your control.

Data Requirements

The Macroeconomic 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 indicators were collected.
• 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 collection date in ISO 8601 format (YYYY-MM-DD).
• Indicator (string, required): The name of the macroeconomic indicator (e.g., "Unemployment", "Happiness", "CCI", "Interest Rate").
• Value (float, required): The value of the indicator (e.g., 0.212). Use consistent units (e.g., rates as decimals or percentages; specify in metadata if needed). Handle missing values with NaN or blanks—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 indicator, date, etc.).

• Wide Format (Useful for spreadsheets): Columns represent different indicators, 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., monthly data if the project is set to monthly granularity). Mismatched granularity will cause upload errors.
• Data Quality: Source from reliable providers and check for revisions or updates, as macroeconomic data is often preliminary and revised later. 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.
• Indicator Selection: Choose relevant indicators based on your industry (e.g., CCI for consumer goods, interest rates for finance). Use clear, consistent naming for easy model integration.

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