Marco Appetito

Aubay Italia S.p.A.

Digital Innovation & Enterprise Architecture Competence Center Director at Aubay Italia S.p.A.
In Aubay Italia, since November 2002, I had been involved in to digital transformation activities for all market segment and primarily for the banking, insurance and telco market.
I manage a continuous research over different interest areas with the main objective of mediate Aubay expertise, technological innovation, offering models and market needs.
I worked on projects related to different topic as AI solution, mobile technology, new architecture solutions (mixed approach based on SOA, ESB and Message based solution), new communication model (based on social, multichannel, collaboration environment), new approach (cloud environment) and so on.
Previous Experience at Aubay Italia as Head Nearshore and R&D Labs and Professional Service Manager in Software Area.

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Speeches di Marco Appetito

Saper leggere e catalogare i risultati di un'indagine NPS attraverso l'uso dell'intelligenza artificiale

Alongside the traditional measurement of Customer Satisfaction is placed the Net Promoter Score-NPS-which is an indicator that measures the proportion of "promoters" of a product, brand or service, compared to "detractors". The number can go from-100 (all are detractors) to + 100 (all are promoters). The NPS is based on a single application to be submitted to those who have used the service: How likely would you recommend this product/service/site to a friend or colleague? Associated with this question, often, there is the possibility of compiling a 'verbatim': that is a justification at its own discretion where the respondent is totally free to write what he wants. Very useful, perhaps even more than the probability, is the interpretation of verbatin that in some way is read and managed, but when their number becomes relevant, a manual cataloging is beyond that very expensive in terms of time and resources, even Error-prone. The artificial intelligence is supportive: through the use of semantic analysis you can build Machine Learning that automatically receive verbatim input and output the sentiment and category, thanks to which the data can Be later managed and understood.

Lingua speech: Italian

Topics

Sessione

Towards data driven companies


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Promosso e organizzato da

Roma Tre
Maker Faire

Con il contributo scientifico di


Con il patrocinio di

Autorità Garante della Concorrenza e del Mercato

Main partner

Google
Google
Arrow
IBM
Acea

Bronze partner

Mathwork
PVT Group
Erwin
Alan Advantage
Cerved
Algorand
Algorand

Evento accreditato pressoOrdine Dei Commercialisti

 

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