Weather

Weather data includes meteorological indicators that may influence consumer behavior or business operations, such as precipitation, wind speed, temperature, snow, humidity, or sunshine hours. These factors can affect demand in weather-sensitive industries (e.g., precipitation impacting outdoor retail sales or wind affecting energy consumption).

Often sourced from public APIs (e.g., OpenWeatherMap, national meteorological services) or third-party providers, this data allows Alviss AI to model environmental impacts on KPIs like sales or visits. For instance, it can quantify how heavy rain reduces foot traffic, helping to isolate seasonal or climatic effects in attributions, simulations, predictions, and optimizations. By incorporating weather, models can adjust for external variables, improving accuracy in forecasting and strategy planning.

Data Requirements

The Weather 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., "UKR" for Ukraine), 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).
• 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 weather indicator (e.g., "Precipitation", "Wind", "Snow", "Temperature").
• Value (float, required): The value of the indicator (e.g., 2.0 for mm of precipitation). Use consistent units (e.g., mm for rain, m/s for wind; specify in metadata if needed).

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 indicator per 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., daily weather if the project is set to daily granularity). Mismatched granularity will cause upload errors.
• Data Quality: Source from reliable providers and check for anomalies (e.g., extreme values). 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 business. 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.