An algorithm to make long-term income predictions for brand growth or decline based on long-term data. Works even for young brands when historical data is not available.

Key features:

• Utilization of historical data from “parent” brands to make predictions.
• Incorporation of data science and statistical analysis techniques.
• Building predictions for various target metrics based on time series data.

The developed solution enables brands to make accurate long-term predictions relying on a wide range of historical data, thereby enhancing business growth and continuously updating predictions for improved accuracy and relevance.