Yes to Data, But Only If It's High Quality

MANDELLI'S CURRENT RESEARCH FOCUSES ON HOW TO IMPROVE DATA QUALITY WHEN COLLECTING, INTERPRETING, AND USING THEM. BECAUSE THEY NEED TO BE MORE THAN JUST BIG TO CREATE VALUE

Both managerial and scientific literature on the subject of Big Data is now quite extensive. Yet the tone in general, especially in managerial literature, remains mostly emphatic, focusing on the potential and the wonders that can arise from this mine of information. "Speaking with executives during meetings for the SDA AI for Marketing course, it always emerged, however, that there are still many problems and challenges to be faced when handling and interpreting data," observes Andreina Mandelli, Professor of Digital Marketing. She is describing the genesis of the in-depth research that has already been published in two volumes, one of which is Big Data Marketing, edited by Egea. This research is now also included in the paper Big Data and Artificial Intelligence Quality in Customer-Centric Marketing, written with SDA colleagues Chiara Piancatelli and Alessandro Arbore.
 
"The priority issue is the quality of data for BDAI marketing, because they need to be more than just 'big' to create value." The focus of current research has therefore become how to improve quality when collecting, interpreting and using this data. What kind of analysis should be performed, with what methods? And what managerial skills are needed to transform information into real benefits? "If a manager makes the decision, for example, to launch a promotion based on a recommendation suggested by predictive analytics but fails to fit it into a broader customer relationship strategy, this information will likely not translate into long-term value for the customer or for the company because there is a lack of quality in the process,” says the professor.
 
Therefore, while BDAI marketing represents a new way of applying data and knowledge to marketing, it is also important to question how to choose, manage and transform data to provide valid decision support, encouraging managers to go beyond the forecasts offered by algorithms in order to understand the deeper reasons for changes. "In this research, we have confirmed that it is not easy to transform the potential of Big Data into effective actions because we must be aware of all the implications that this challenge entails also in terms of ethics, transparency, privacy, customer experience... In short, for a manager today it is essential to have a non-mechanistic orientation, because BDAI marketing is more than a powerful tool for thinking about market research, it is a completely new way of marketing. Advances in artificial intelligence and machine learning continually suggest different mixes of interpretive intelligences and sensitivities needed to grow a business. For this reason I also believe that research of this type can never be said to be truly over.”

by Emanuele Elli