How to build a revenue prediction model with CARTO & BigQuery

Sales forecasting and revenue prediction have become increasingly important to retailers during the past two years as store owners have had to rapidly react to evolving consumer behaviors.

For example, understanding what consumers will buy, how much, and when can be used by retailers to optimize revenue by avoiding over or under-stocking key product lines. Historical sales data has been traditionally used to create such a forecast but retailers also need to consider the location aspect within their analysis, especially when it comes to decisions around site selection.

This year, retailers in the US will open more stores than they close for the first time since 2017 (source) with ‘retail’s recovery going faster than anyone imagined’.