Evaluation Metrics and Transfer Learning for Sales Prediction

Maijers, Jip Wilmar Jostein (2022) Evaluation Metrics and Transfer Learning for Sales Prediction. [Laurea magistrale], Università di Bologna, Corso di Studio in Artificial intelligence [LM-DM270], Documento full-text non disponibile
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Sales prediction plays a huge role in modern business strategies. One of it's many use cases revolves around estimating the effects of promotions. While promotions generally have a positive effect on sales of the promoted product, they can also have a negative effect on those of other products. This phenomenon is calles sales cannibalisation. Sales cannibalisation can pose a big problem to sales forcasting algorithms. A lot of times, these algorithms focus on sales over time of a single product in a single store (a couple). This research focusses on using knowledge of a product across multiple different stores. To achieve this, we applied transfer learning on a neural model developed by Kantar Consulting to demo an approach to estimating the effect of cannibalisation. Our results show a performance increase of between 10 and 14 percent. This is a very good and desired result, and Kantar will use the approach when integrating this test method into their actual systems.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Maijers, Jip Wilmar Jostein
Relatore della tesi
Correlatore della tesi
Corso di studio
Ordinamento Cds
Parole chiave
Sales prediction,Cannibalisation,Time Series,Transfer Learning
Data di discussione della Tesi
6 Ottobre 2022

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