Articoli taggati con ‘Audience Analysis’
Corporate Museums and design: Web communication strategies
Abstract The content of this article is the analysis of Web communication strategies used by corporate museums. The main goal of the research is to analyze the Italian corporate museum’s communication in order to first review the digital identity and the reach and engage operations used by them. Through several indicators, the study highlights both strengths and weaknesses of the online strategies used by those samples, which have been selected among Museimpresa partner museums operating in the commodities sector of design.
Museums’ visitors in Italy
In a country where cultural participation generates alarming negative numbers (in 2015, 68.3% of the Italian population has never entered a museum [1] ), it becomes crucial to understand the new public and study suitable strategies for a cultural proposal able to better reflect their interests. Indeed, although this percentage is on the rise compared to the trend of recent years, there is a kind of cultural impoverishment, which concerns not only the museum, but also publishing, theater, music and dance. The 88.3% of the total population of our country in 2015 has never attended a classical music concert, 78.8% have never seen a play, 51.9% have never read a newspaper, 56.5% has never opened a single book [2]. It has often been attempted to reduce analysis of public museum culture to a series of data, more or less accurate, more or less exemplary, rather than to a basic theory that you intend to demonstrate and posit as a significant idea and a related cultural marketing strategy. It will be to demonstrate, id est, with the data, the validity of an idea, sometimes deforming the correct reading and interpretation. What is sometimes forgotten is the exact opposite: the need to gather facts on a phenomenon under investigation, and then let the data talk, so that a sense can be drawn from their links and their possible interrelationships. In his “L’analyse des données”, Jean- Paul Benzecri, founder of a scientific discipline related to data analysis, wrote: «The model must follow the data, not vice versa [3] ». It is then the daunting task for the researcher to find a connection, if any, between numbers which may be sometimes discordant or present apparently low affinity.
