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Forecasting success via early adoptions analysis: A data-driven study
Innovations are continuously launched over markets, such as new products over the retail market or new artists over the music scene. Some innovations become a success; others don’t. Forecasting which innovations will succeed at the beginning of their lifecycle is hard. In this paper, we provide a da...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720712/ https://www.ncbi.nlm.nih.gov/pubmed/29216255 http://dx.doi.org/10.1371/journal.pone.0189096 |
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author | Rossetti, Giulio Milli, Letizia Giannotti, Fosca Pedreschi, Dino |
author_facet | Rossetti, Giulio Milli, Letizia Giannotti, Fosca Pedreschi, Dino |
author_sort | Rossetti, Giulio |
collection | PubMed |
description | Innovations are continuously launched over markets, such as new products over the retail market or new artists over the music scene. Some innovations become a success; others don’t. Forecasting which innovations will succeed at the beginning of their lifecycle is hard. In this paper, we provide a data-driven, large-scale account of the existence of a special niche among early adopters, individuals that consistently tend to adopt successful innovations before they reach success: we will call them Hit-Savvy. Hit-Savvy can be discovered in very different markets and retain over time their ability to anticipate the success of innovations. As our second contribution, we devise a predictive analytical process, exploiting Hit-Savvy as signals, which achieves high accuracy in the early-stage prediction of successful innovations, far beyond the reach of state-of-the-art time series forecasting models. Indeed, our findings and predictive model can be fruitfully used to support marketing strategies and product placement. |
format | Online Article Text |
id | pubmed-5720712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57207122017-12-15 Forecasting success via early adoptions analysis: A data-driven study Rossetti, Giulio Milli, Letizia Giannotti, Fosca Pedreschi, Dino PLoS One Research Article Innovations are continuously launched over markets, such as new products over the retail market or new artists over the music scene. Some innovations become a success; others don’t. Forecasting which innovations will succeed at the beginning of their lifecycle is hard. In this paper, we provide a data-driven, large-scale account of the existence of a special niche among early adopters, individuals that consistently tend to adopt successful innovations before they reach success: we will call them Hit-Savvy. Hit-Savvy can be discovered in very different markets and retain over time their ability to anticipate the success of innovations. As our second contribution, we devise a predictive analytical process, exploiting Hit-Savvy as signals, which achieves high accuracy in the early-stage prediction of successful innovations, far beyond the reach of state-of-the-art time series forecasting models. Indeed, our findings and predictive model can be fruitfully used to support marketing strategies and product placement. Public Library of Science 2017-12-07 /pmc/articles/PMC5720712/ /pubmed/29216255 http://dx.doi.org/10.1371/journal.pone.0189096 Text en © 2017 Rossetti et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Rossetti, Giulio Milli, Letizia Giannotti, Fosca Pedreschi, Dino Forecasting success via early adoptions analysis: A data-driven study |
title | Forecasting success via early adoptions analysis: A data-driven study |
title_full | Forecasting success via early adoptions analysis: A data-driven study |
title_fullStr | Forecasting success via early adoptions analysis: A data-driven study |
title_full_unstemmed | Forecasting success via early adoptions analysis: A data-driven study |
title_short | Forecasting success via early adoptions analysis: A data-driven study |
title_sort | forecasting success via early adoptions analysis: a data-driven study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720712/ https://www.ncbi.nlm.nih.gov/pubmed/29216255 http://dx.doi.org/10.1371/journal.pone.0189096 |
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