TY - JOUR
T1 - Analytical model to measure the effectiveness of content marketing on Twitter
T2 - the case of governorates in Colombia
AU - Guzmán Ordóñez, Anabel
AU - Arroyo Cañada, Francisco Javier
AU - Lasso, Emmanuel
AU - Sánchez-Torres, Javier A.
AU - Escobar-Sierra, Manuela
N1 - Funding Information:
Funding was provided by Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS) (Grant no. 860).
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2023
Y1 - 2023
N2 - Twitter as a marketing tool has led to a growing interest in measuring the effectiveness of content marketing on this platform. However, there has yet to be a comprehensive analytical model to measure the effectiveness of public content marketing (PCM) accurately and reliably. A literature review determined the gaps between preliminary studies and constructing a new model to measure the content effectiveness, considering variables related to interactivity and performance of digital content marketing (DCM) strategies. For this reason, this study aims to build an analytical model that determines which content characteristics improve the effectiveness of Twitter accounts, taking as a case study the governorates of Colombia. Within the methodology for data mining, CRISP-DM was used, which allowed the cleaning, processing and analysis of all data collected from the accounts of Colombian governments. The results allowed to establish factors that have yet to be considered to measure the Engagement Rate per Post (ERP) and have a critical load on users’ interactivity with the content, such as the tweet type, emojis, dates, the type of media, sentiment associated with the post and emotions. With the model, it was possible to identify the variables that improve the ERP and their impact on the effectiveness of the content.
AB - Twitter as a marketing tool has led to a growing interest in measuring the effectiveness of content marketing on this platform. However, there has yet to be a comprehensive analytical model to measure the effectiveness of public content marketing (PCM) accurately and reliably. A literature review determined the gaps between preliminary studies and constructing a new model to measure the content effectiveness, considering variables related to interactivity and performance of digital content marketing (DCM) strategies. For this reason, this study aims to build an analytical model that determines which content characteristics improve the effectiveness of Twitter accounts, taking as a case study the governorates of Colombia. Within the methodology for data mining, CRISP-DM was used, which allowed the cleaning, processing and analysis of all data collected from the accounts of Colombian governments. The results allowed to establish factors that have yet to be considered to measure the Engagement Rate per Post (ERP) and have a critical load on users’ interactivity with the content, such as the tweet type, emojis, dates, the type of media, sentiment associated with the post and emotions. With the model, it was possible to identify the variables that improve the ERP and their impact on the effectiveness of the content.
KW - Content marketing
KW - Engagement
KW - Government
KW - Machine learning
KW - Social media
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=85168620570&partnerID=8YFLogxK
U2 - 10.1057/s41270-023-00243-5
DO - 10.1057/s41270-023-00243-5
M3 - Artículo
AN - SCOPUS:85168620570
SN - 2050-3318
VL - 12
SP - 962
EP - 978
JO - Journal of Marketing Analytics
JF - Journal of Marketing Analytics
IS - 4
ER -