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A study of Unilever’s online consumer-brand engagement in Portugal

Authors: Augusto, Manuel Pereira;

A study of Unilever’s online consumer-brand engagement in Portugal

Abstract

The consumption of online social media is growing around the world. In 2020, Facebook registered a record of 2.5 billion monthly active users. Consumers all around the world are increasing their online presence, especially in social networks as Facebook, where they communicate and look for advice from other consumers in ways that firms are finding harder to control or predict. Some brands have taken advantage of the potential of these platforms, trying to understand how to connect with their consumers online, how to measure those efforts and how to improve its consumer-brand engagement. This in-company project is elaborated within the scope of Unilever. Its purpose is to analyze the company’s Brands consumer-brand engagement. In this project, we evaluate and compare Unilever Brands’ engagement performance in Facebook, by understanding which brands and topics are generating more positive or negative engagement and by analyzing which communication patterns lead to more positive sentiments from consumers. To test the hypothesis created, a Text Mining and Sentiment Analysis were performed to over 7000 interactions between the brands and its consumers on Facebook, crosschecking this data with the communication patterns and assessing which ones lead to a higher sentiment score. Results show that Facebook Brand Posts communicating the Brands’ Purpose, a Product Innovation, and a Game/Challenge lead to more positive sentiments from the consumers. A plan to integrate a Sentiment Score Analysis in the Brands’ strategy is included, based on the results gathered from this project.

O consumo de redes sociais online está a crescer em todo o mundo. Em 2020, o Facebook registou um record de 2,5 mil milhões de utilizadores mensais ativos. Os consumidores estão a aumentar a sua presença online em todo o mundo, especialmente em redes sociais como o Facebook. Algumas marcas têm aproveitado o potencial destas plataformas, tentando entender como conectar-se com seus consumidores online, como medir esses esforços e como melhorar o seu envolvimento com os consumidores. Este projeto de empresa é elaborado no âmbito da Unilever, com o objetivo de analisar o envolvimento online das marcas Unilever com os seus consumidores. Neste projeto é avaliado e comparado o desempenho do envolvimento das marcas Unilever na rede social Facebook, analisando que marcas e tópicos geram um envolvimento mais positivo ou negativo e analisando quais são os padrões na comunicação das marcas que levam a sentimentos mais positivos por parte dos consumidores. Para testar as hipóteses criadas, é feito um Text Mining e uma Análise de Sentimentos a mais de 7000 interações entre as marcas e os consumidores no Facebook, cruzando esses dados com os padrões de comunicação e avaliando quais deles levam a senitmentos mais positivos. Os resultados mostram que os posts que comunicam o Propósito das marcas, Inovações de produto e um Passatempo geram sentimentos mais positivos dos consumidores. No final, é desenhado um plano para integrar uma análise de sentimentos na estratégia das marcas, com base nos resultados obtidos neste projeto.

Country
Portugal
Keywords

Sentiment analysis, Domínio/Área Científica::Ciências Sociais::Economia e Gestão, Text mining, Unilever, Online consumer-brand engagement, Árvore de decisão -- Decision tree, Análise de sentimentos

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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