Disaggregating sales prediction: a gravitational approach

Silveira Netto, Carla Freitas and Bahrami, Mohsen and Brei, Vinicius Andrade and Bozkaya, Burçin and Balcısoy, Selim and Pentland, Alex Paul (2023) Disaggregating sales prediction: a gravitational approach. Expert Systems with Applications, 217 . ISSN 0957-4174 (Print) 1873-6793 (Online)

Full text not available from this repository. (Request a copy)


Whenever companies plan to enter new geographical areas, they need disaggregated sales in each location. To make such predictions, sales time series or final customers’ data in geographical disaggregation are necessary. However, for most companies, such datasets are unavailable or impractical. The manuscript has two main goals. One focal problem is how to disaggregate an aggregate sales prediction with no historical proportions. The other is how to improve spatial models using Point of Interest (POI) data. To solve these problems, we combine two literature streams — spatial marketing and sales forecasting — and propose a new hybrid probabilistic approach: Gravitational Sales Prediction (GSP). Our approach uses POI data to estimate area attraction, customer stocks, and flows to predict sales proportions. We later use these proportions to disaggregate an aggregate forecast. GSP is validated using sales data from two countries and more than ten economic segments. When compared to a strong benchmark that relies on past sales proportions, GSP exceeded expectations by achieving not only a similar performance to the benchmark but also outperforming it in some locations. It showed the most promising results in the middle level of aggregation. The result is a powerful and flexible approach that can be embedded in any decision support system.
Item Type: Article
Uncontrolled Keywords: Forecast disaggregation; Gravity models; Sales prediction; Spatial marketing
Divisions: Sabancı Business School
Depositing User: Burçin Bozkaya
Date Deposited: 25 Apr 2023 12:21
Last Modified: 25 Apr 2023 12:21
URI: https://research.sabanciuniv.edu/id/eprint/45417

Actions (login required)

View Item
View Item