In the era of digital marketing, it is becoming increasingly challenging for organizations to position their brand uniquely and differentiate from competitive product lines. In order to achieve that, organizations target a set of humanlike qualities (or a personality) across all their marketing campaigns. This is known as brand personality.
For example, Red Bull portrays itself as courageous and uninhibited, while Nike represents itself as being athletic.
It is known to significantly influence consumer behavior as well as brand positioning.
These brand personality traits have been formalized in the famous Aaker 1997 brand personality paper  which outlined the five dimensions along with its characteristics – sincerity, excitement, competence, ruggedness, and sophistication.
In this article, we answer a few FAQs regarding consumer psychology, brand personality, and online reputation monitoring. Next, we explore each of these concepts in more detail as well as summarize the related works.
There is an excellent article on Medium by Felicia where she provides practical tips along with examples of brand personality w.r.t popular brands like Apple. I would highly recommend going through that article.
Q: Is it limited to a company. Do the company employees or an individual possess it.
Answer: Apart from companies, the employees, as well as individuals holding a position of responsibility, may have it. The following ICWSM 2016  paper analyzes user-generated content from Twitter and employee reviews from Glassdoor.
Q: Is it a new thing or an old concept in a new bottle. What has changed recently? Why is now an interesting time to study it?
Answer: No, it is an old field. More popular, is Online Reputation Monitoring, which deals with the user-generated content created by the different stakeholders like company representatives, company employees, and even the consumers. With the rise of the use of social media, these stakeholders share their experiences and provide reviews on different social media platforms like Twitter and Instagram (consumer reviews), LinkedIn (company representative’s reviews or testimonials), and Glassdoor (employee reviews).
Q: Do we encounter it in our everyday activities. If yes, then where.
Answer: With the recent advent of digital marketing and the prevalence of social media, companies are facing difficulting in monitoring the consumer’s perception of them. Usually, we know a company based on its products.
Q: Are there any definitions or formalizations for it.
Answer: Like the Big Five Human Personality traits (openness, conscientiousness, extraversion, agreeableness, neuroticism), we call this brand personality of a company. There are formalizations – some divide into 5 dimensions while some into 12 dimensions.
Brand Personality and Brand Consistency in-depth
Answers are taken from our WebSci 2019  and TWEB 2021 paper , slides, and paper details are provided in references)
In our WebSci 2019 full conference paper , we model brand personality by analyzing the corporate website postings of Fortune 500 companies and then develop a set of independent, trait-specific classifiers known as the Final Linear Classifier Set (FLCS). They observe that a deep learning model (fastText) trained on limited labeled data, suffers from overfitting issues and performed very poorly.
In our TWEB 2021 journal paper , we further introduce a notion called brand consistency that measures the ability of an organization to maintain a consistent brand personality over time across multiple content categories.
They use FLCS to first generate weak labels for unlabeled website postings, and then use it for performing a large-scale characterization study.
Related Works on Brand Personality in terms of Consumer Psychology models
We have earlier defined brand personality as a set of humanlike qualities or a personality that a company wants to maintain in its promotional materials.
Relation with human personality and effect of the company website on brand personality
Digman et al.  formalized this concept of human personality into the Big Five personality traits which are extroversion, neuroticism, agreeableness, conscientiousness, and openness.
Muller and Chandon  study the impact of visiting a company website on the brand image and particularly on the brand personality since companies strategically place verbal or non-verbal cues in the websites to evoke specific emotions from their users.
Chen and Rogers  develop a scale to measure the website personality, using a combination of human personality and brand personality attributes.
Douglas et al.  proposed a ‘Website Emotional Features Assessment Model’ that is based on website features – site activation, site affection, site confidence, site serenity, site superiority, and site surgency.
From the user’s perspective, a recent study by Still  found that the visual hierarchy of a webpage depends on the position, color, and text style of each webpage element and not size.
From the Consumer Psychology literature
Schmitt et al.  proposed a consumer psychology model of brands, which specifically focuses on the unique characteristics of the brands in contrast to the earlier ‘general information processing’-based models. It primarily identifies that consumers have different levels of psychological engagement with brands due to their individual needs, motives, and goal.
Brand personality belongs to the middle layer out of the 3 levels of engagement (the innermost level is object-centered and functionally driven, and the outermost layer represents the social interaction and community perspective of a brand), where the brand is seen as personally relevant to the customer.
This model also distinguishes among different brand-related issues associated with brand personality.
First, is the integrating process where brand information is combined into an overall brand concept, brand personality, and relationship with the brand. Secondly, the connecting phase is where the customer forms an attitude toward the brand, becomes personally attached to it, and gets connected in a brand community.
What is Online Reputation Monitoring (ORM) and how is Brand Personality different from it?
With the recent advent of digital marketing and the growing influence of social media, it has become more difficult for organizations to monitor such user-generated content that harms their brand image.
RepLab [11, 12] has provided shared tasks to address the ORM issues of entity resolution (resolving name ambiguity), topic detection (issues discussed by the entity), polarity for reputation, alert detection (issues that might harm the reputation of the entity), reputation dimensions classification and author profiling.
Spina et al.  address this reputation monitoring problem faced by experts by formulating it as a topic detection task. Saleiro et al.  developed an end-to-end, modular text-mining framework that may be adapted to different ORM tasks.
Mazloom et al.  performed a multimodal study (both text and image) on Instagram user posts and developed a popularity prediction model for brand-related posts. They found the visual and textual features to be complementary in predicting the post’s popularity.
Brand personality deals with the issues at the content-creation stage (performed by brand managers and content creators), contrary to the field of online reputation monitoring (ORM) which deals only with consumer-generated content.
I would love your feedback. Please mention your suggestions and clarifications in the Comments section.
- Soumyadeep Roy, Niloy Ganguly, Shamik Sural, Niyati Chhaya, and Anandhavelu Natarajan, Understanding Brand Consistency from Web Content, in Proceedings of the 10th ACM Conference on Web Science, WebSci 19, (Boston, MA, USA), pp. 245–253, ACM, 2019. (Full Paper) [DOI] [PDF] [Slides][Data]
- Xu et al. Predicting Perceived Brand Personality with Social Media, ICWSM 2016
- Jennifer L Aaker. 1997. Dimensions of brand personality. Journal of marketing research (1997), 347–356
- Soumyadeep Roy, Shamik Sural, Niyati Chhaya, Anandhavelu Natarajan, and Niloy Ganguly, An Integrated Approach for Improving Brand Consistency of Web Content: Modeling, Analysis and Recommendation, in ACM Transactions on the Web (TWEB), 25 pages, November 2020 (Journal) [arXiv][DOI][Slides-MS Thesis version][Code and Data] (Most recent work)
- John M Digman. 1990. Personality structure: Emergence of the five-factor model. Annual review of psychology 41, 1 (1990), 417–440. https://www.annualreviews.org/doi/pdf/10.1146/annurev.ps.41.020190.002221
- Brigitte Müller and Jean-Louis Chandon. 2003. The impact of visiting a brand website on brand personality. Electronic Markets 13, 3 (2003), 210–221. https://doi.org/10.1080/1019678032000108301
- Qimei Chen and Shelly Rodgers. 2006. Development of an Instrument to Measure Web Site Personality. Journal of Interactive Advertising 7, 1 (2006), 4–46. https://doi.org/10.1080/15252019.2006.10722124
- Alecia C. Douglas, Juline E. Mills, and Raphael Kavanaugh. 2007. Exploring the Use of Emotional Features at Romantic Destination Websites. In Information and Communication Technologies in Tourism 2007, Marianna Sigala, Luisa Mich, and Jamie Murphy (Eds.). Springer Vienna, Vienna, 331–340. https://doi.org/10.1007/978-3-211-69566-1_31
- Jeremiah D. Still. 2018. Web page visual hierarchy: Examining Faraday’s guidelines for entry points. Computers in Human Behavior 84 (2018), 352 – 359. https://doi.org/10.1016/j.chb.2018.03.014
- Bernd Schmitt. 2012. The consumer psychology of brands. Journal of Consumer Psychology 22, 1 (2012), 7 – 17. https://doi.org/10.1016/j.jcps.2011.09.005
- E. Amigo, J. C. De Albornoz, I. Chugur, A. Corujo, J. Gonzalo, T. Mart ´ ´ın, E. Meij, M. De Rijke, and D. Spina, “Overview of Replab 2013: Evaluating online reputation monitoring systems,” in International conference of the cross-language evaluation forum for European languages, pp. 333–352, 2013
- J. Carrillo-de Albornoz, J. Gonzalo, and E. Amigo, ´ RepLab: An Evaluation Campaign for Online Monitoring Systems, pp. 487–510. Cham: Springer International Publishing, 2019
- D. Spina, J. Gonzalo, and E. Amigo, “Learning similarity functions for topic detection in online reputation monitoring,” in Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’14, pp. 527–536, ACM, 2014
- P. Saleiro, E. M. Rodrigues, C. Soares, and E. Oliveira, “Texrep: A text mining framework for online reputation monitoring,” New Generation Computing, vol. 35, pp. 365–389, Oct 2017
- M. Mazloom, R. Rietveld, S. Rudinac, M. Worring, and W. van Dolen, “Multimodal popularity prediction of brand-related social media posts,” in Proceedings of the 24th ACM International Conference on Multimedia, MM ’16, (New York, NY, USA), pp. 197–201, ACM, 2016