Exploring the Opportunities of the Emojis in Brand Communication: The Case of the Beer Industry

Abstract

This study shows that emojis are a significant element in brand communications, which still requires attention from researchers. Specifically, it describes the use of emojis by the four companies with the largest audiences on Twitter in the Spanish beer industry. Through a correspondence analysis, we found that those emojis were not a mere occasional resource within a message but rather a differentiating element for brand positioning. Likewise, we analyzed the existing relationship between the way in which they were used and the engagement generated. In this regard, we concluded that communications using emojis aimed at customer service and care, as well as those used in positive contexts and for emphasis, were the ones related to higher user engagement. We discuss herein the practical implications of these findings for businesses.

Keywords

emojis brand communications engagement social conversations digital communications

Emojis are frequently used as a language for interpersonal and group communication in social networks (Vidal, Ares, & Jaeger, 2016). In an attempt to increase the engagement of their audience companies, institutions and organizations have adapted their digital messages to include resources such as emojis in their communications with customers (Arya, Sethi, &Verma, 2018). Emojis facilitate emphatic communication between people and therefore can play an important role in the business world and have a positive effect on building interpersonal relationships (Das, Wiener, & Kareklas, 2019). They can be an excellent communication tool for creating market-company relationships in relational marketing. In addition, companies tend to develop a language similar to the one employed by customers, which “humanizes” the brand (Hede & Watne, 2013).

In spite of this growing trend in the use of emojis, research in this field still has a long way to go. In fact, the way in which the brands use them can be a good instrument for company differentiation. This is where this article intends to make a contribution. Specifically, the focus of our study is on how brands use emojis. That is, whether they use them merely as just another resource within their messages to establish an emotional link with their target audience or whether they go further and even design their own style in order to differentiate themselves from their competitors. If the creation of a particular style is confirmed, then an additional objective of the study will be to determine whether any of these styles provide a higher degree of engagement.

Given the heterogeneity of the different business sectors and cultural contexts, it was necessary to limit the scope of the study. According to Markman and Oshima (2007), emojis should be interpreted within their cultural context. Therefore, our study was limited to only one country. We also decided to analyze the use of emojis in brand communications in the food and beverage industry as it is a field that has appealed to a greater number of researchers (Jaeger, Vidal, Kam, & Ares, 2017; Vidal et al., 2016). We specifically focused on the beer industry because the brands are very active in social media (Alianzo Social Analytics & Influence Tools, 2015). Nevertheless, studies have to date considered emojis to be merely an additional traditional communications resource and not something that is used for differentiation (Jaeger et al., 2017; Mostafa, 2013).

Likewise, we focused on the social medium Twitter because it is widely used by society to express opinions. So much so that, at a world event such as the Olympic Games in Rio de Janeiro 2016, Twitter developed specific emoticons of the flags for each country. The world of academia has also taken notice of its popularity as a channel for expression, and several authors have used it as a source of data in various settings (Mostafa, 2013; Vidal et al., 2016).

Theoretical Basis

The lack of nonverbal features of expression or of personal impressions in 2.0 discourses forces users of digital communications to develop new ways of expressing themselves (Derks, Fischer, & Bos, 2008). Users have been resorting to different types of language resources to qualify their views and feelings, such as punctuation marks, asterisks, or brackets (Darics, 2014). In light of this, mobile and digital chat platforms began using the Unicode character set. This enabled them to turn these special characters, which were sometimes difficult to type and interpret by users, into graphic icons that gave rise to the present-day emojis (Novak, Smailović, Sluban, & Mozetič, 2015). In this study, we have considered the term emoji to mean animated or static icons that express emotions that are commonly used in instant messaging (Garrison et al., 2011; Tossell et al., 2012).

As shown in Table 1, existing studies on emojis could be classified into three areas of knowledge: (1) user behaviors and attitudes, (2) emotional and semantic analysis, and (3) conversational marketing. Studies on user behavior highlight that they are included in peer-to-peer communications and they are used more to establish friendly and positive conversations than for negative purposes (Das et al., 2019). Second, studies that focus on the emotional and semantic analysis of emojis are the most frequent. This is mainly due to the fact that their analysis makes it possible to interpret feelings from flat text in messages extracted from digital media (Sampietro, 2016a, 2016b). Finally, in the area of conversational marketing, there is already some evidence that emojis are being used by brands in conversations with their customers (Kayser & Bierwisch, 2016; Kwon & Sung, 2011). In short, we found that the common denominator of using emojis in all three cases is to establish emotional relationships between the actors participating in the communications.

Table 1.

Perspectives of Studies on Emojis.

Perspectives	Studies	Authors	Results by perspectives
User behavior	• Frequency by channel • Differences by sex • Differences by nationality	Derks et al. (2008)	• Women use more emojis than men. • Greater use in conversations between different sexes. • They are used in instant messaging to interrupt communication. • They are used more frequently in horizontal than in vertical communications. • Their frequency of use increases when writing from a smartphone instead of from a computer. • They are used more as a resource to express positive emotions and feelings than negative ones. • The emojis of objects are used to express positive emotions and joy. • Their use diminishes the seriousness of the conversation. • There are differences in use by cultural factor. • In the field of health, they are used by users with anxiety.
	• Frequency of use	Garrison et al. (2011); Tossell et al. (2012).
	• Uses of emoticons in smartphones	Qiao (2009)
	• Preference of emoticons, graphic, or animated emojis • Number and order of emoticons, profiles of emoticon users • Communications where they are used most	Donovan (2016); Park, Kim, and Lee (2014); Riordan (2017)
Emotional and semantic analysis	• Feelings generated by the use of emojis • Emotional contagion of emojis • Types of emojis	Kavanagh (2010); Sampietro (2016a, 2016b)	• Tweets with emojis are significantly more positive than those without them. • Feeling polarity varies depending on where the emoji is placed on the tweet. • Emojis are used as automatic tags that facilitate automated semantic analysis of emotions expressed in tweets containing emojis. 751 emojis have been classified by feelings. • The presence of emojis has a positive impact on the emotional perception of messages issued by users. • The main functions of emojis are to express irony, to trigger behaviors and sensations, to lessen the politeness of treatment, to soften the conversational tone, to express moods, to replace punctuation marks included at the end of sentences, to emphasize illocutionary force of a sentence, and to help order turns in a conversation. • Define an automatic method to extract the meaning of emojis (model ski-gram of vector space) in the context of the sentence where they appeared. • The meaning of emojis is maintained regardless of the language used.
	• Feelings in the use of emojis	Hogenboom, Bal, De Jong, and Kaymak (2013); Yus (2014)
	• Emoji sentiment ranking	Novak et al. (2015)
	• Emotional contagion on Twitter with emojis	Gruzd, Doiron, and Mai (2011)
	• Types of emoji functions	Wolf (2000)
	• Analysis of emojis on Twitter with vector space models • Automatic method to extract the meaning of emojis	Barbieri, Ronzano, and Saggion (2016)
Conversational marketing	• Use by brands of emojis in their communications, in different contexts	Arya et al. (2018); Darics (2014); Das et al. (2019); Kwon and Sung (2011); Skovholt, Grønning, and Kankaanranta (2014)	• Used in brand communications to express emotion and irony, modify illocutionary force of the utterance, and to punctuate the message. • Emojis creatively replace terms, help manage interactions, and play a sociopragmatic role. • Brand communications with emojis generate engagement.
Conversational marketing	• Spontaneous use by consumers to express their brand experiences	Köster and Mojet (2015)

Moreover, peers tend to have shared codes that are only understood by them, and the use of emojis is no exception. Consequently, brands look at how their consumers use them in order to establish emotional bonds and shared contexts with them (Barbieri et al., 2016). An emotion toward a brand in digital messages is expressed with feelings of admiration, empathy, respect, and trust (Ponzi, Fombrun, & Gardberg, 2011). It is measured using three dimensions: valence or polarity, intensity, and control (Scherer, 2005). Along these lines, Vidal et al. (2016), who analyzed emotions in digital conversations on Twitter, concluded that users express these emotions more with emojis and emoticons than with words. In fact, we found that the consumers of these brands usually include references to their emotions in 25% of their tweets. Specifically, they classify emoji emotion by (1) the valence extracted from a sample of tweets issued by consumers on food and beverage brands into positive, negative, and neutral and (2) the intensity of the emotion based on the emphasis given to the information expressed in words in the tweet and its location. In line with this, there are some papers available on communications with emojis for the beverage sector (Gmuer, Guth, Runte, & Siegrist, 2015; van Zyl & Meiselman, 2015). Specifically, emojis help simplify and automate semantic analysis of emotions in digital messages or conversations in the beverage industry where they are included (Jaeger et al., 2017; Riordan, 2017).

The themes that explain these perceived emotions are generally very similar (Ponzi et al., 2011). These can be broken down into areas such as products and services offered (e.g., the quality-price ratio, innovation, warranties, brand image, or customer focus); innovation, work (references to employer brand or being a good place to work), social and environmental responsibility, corporate governance (e.g., corporate ethics), leadership (comments about managers), and finance (mentions of financial performance or solvency). In addition, all these issues are defined by an emotional component such as admiration, respect, trust, reliability, or empathy. In turn, this component may have positive, negative, or neutral valence and intensity scales (Scherer, 2005).

To a lesser extent than emotions, users and brands use emojis for other functions such as creative replacement of terms, to help manage interactions, or to play a sociopragmatic role. In this sense, Vidal et al. (2016) contemplated a series of emojis used by consumers to discuss themes related to products in the food and beverage industry, for example, linked to food (pizzas, hot beverages, hamburgers, wine) or the place where drinks were being consumed (party, birthday, restaurants, etc.). Brands attempt to detect the themes that are most relevant for establishing bonds with each stakeholder and adjust their brand communications accordingly in order to promote greater engagement with their audiences and help build long-term relationships (Helm, 2007).

Engagement can be defined as a psychological state that occurs as a result of interactive and co-creative experiences of customers or consumers with specific brands, actors, objects, or events (Hollebeek, Glynn, & Brodie, 2014). Social networks are the ideal environment for the social and interactive behavior of customers (Okazaki, Díaz-Martín, Rozano, & Menéndez-Benito, 2015), as shown in the state of customer engagement report (Econsultancy, 2013). In turn, Arya et al. (2018), in their recent study, found that brand communications with emojis in social media help generate engagement. Likewise, Kayser and Bierwisch (2016) consider that Twitter is the ideal platform to generate engagement, and they provide several reasons for this. First, due to the functionalities it provides its users through tweets, hashtags, @-messages, retweets, and follower relations. Second, because it is used to spread information about users. And, finally, the growing utilization of this medium by businesses and politicians to reach consumers and citizens, respectively.

There is no generally accepted consensus on the concepts that should be used to measure engagement (Hollebeek et al., 2014). Agostino and Sidorova (2016, p. 42) state that “engagement measures the ability of an organization to establish dialogue and interactions with social media users and is based on the quantification of responses to social media posts.” Dolan, Conduit, Fahy, and Goodman (2016) state that to measure brand engagement properly, the context where it is generated needs to be considered, taking into account the perceived contingency achieved. That is, the messages received depend on the messages sent, which leads to a thread of interdependent communications (Sundar, Bellur, Oh, Jia, & Kim, 2016). Based on the concepts of commitment, involvement, and participation, Muñoz-Expósito, Oviedo-García, and Castellanos-Verdugo (2017) proposed a comprehensive metric that operationalizes engagement on Twitter. This metric contemplates, among other indicators, the number of likes or favorites and the number of retweets.

In short, there is an interest by researchers to analyze how brands establish relationships with their customers through the use of emojis in their communications. However, we have found no empirical evidence in high-impact publications indicating whether they are being used with their own specific style, which would allow them to differentiate themselves from their competitors, and whether there is a relationship between this style and higher engagement. Specifically, to bridge these research gaps, the two questions addressed by this article are as follows:

Research Question 1: Can brands position themselves based on their communications with emojis?

Research Question 2: Are there some communication styles with emojis that generate more engagement than others?

Methodology

To achieve our objective, we decided to apply the technique called netnography. This type of methodology is gaining popularity in social science research, and it is increasingly being recognized by researchers for its usefulness in the study of users and brands in digital environments (Arvidsson & Caliandro, 2016). The three phases in this methodology are (1) identification of the study objective, (2) collection and analysis of information using technical means, and (3) content analysis to identify major characteristics.

To undertake our study, we chose the Twitter communications of four Spanish beer breweries, which represent 40% of total Spanish production (Ministry of Agriculture and Fisheries Food and Environment, 2017), and are leading brands, with a clearly commercial profile and neither craft beers nor aimed at a niche market. This study was limited to brand communications in Spain for two reasons. First, to focus on the context of a single country because interpreting the meaning of an emoji in a message may vary according to the culture (Markman & Oshima, 2007). And second, as pointed out by the Socioeconomic Report of the Beer Industry in Spain (Ministry of Agriculture and Fisheries Food and Environment, 2017), the socializing nature of beer consumption in Spain, plus the fact that use is moderate and normally accompanied by food, the famous Spanish “tapas,” gives the brands an image of closeness, which favors an open dialogue with the people. Precisely, the four brands analyzed have the largest audience and a popularity of more than 60% (number of followers minus number following) on Twitter (Alianzo Social Analytics & Influence Tools, 2015).

To obtain data, we located the official accounts of these brands and collected tweets issued by the companies during the period analyzed, 26 June to 14 September 2017. This collection was conducted using the tool twDocs, a web application that helps save tweets and search results conducted on Twitter. As a result, we obtained a total of 5,012 tweets. Once the data were collected, we cleaned up the database. It should be noted that at present there is still an ongoing debate on whether automated data analysis methods are capable of completely replacing intervention by a human evaluator (Kirilenko, Stepchenkova, Kim, & Li, 2018). For this reason, to clean the tweets we combined automatic data extraction, using the abovementioned software, with traditional human interpretative analysis. In this first phase, human intervention consisted of selecting, from among all tweets, only those pertaining to communications posted by brands from their official accounts. Finally, we ended up with a total of 4,278 net communications, of which 3,430 had no emojis and 848 did, so our study focused on the latter.

Given that the extraction of tweets did not show emojis as a pictogram, but as a series of text characters, it was necessary to convert them to Unicode, which facilitates the semantic and quantitative processing of tweets with emojis. Once the conversion was completed, we prepared the final working database, with the net tweets of each brand and emojis as pictograms.

Next, we conducted a content analysis of the tweets with emojis to establish major categories for the different variables related to them and their significance. Following the recommendations by Vidal et al. (2016), who suggested that the text where emojis appeared should be taken into account to correctly interpret their meaning, we established the emoji context within the tweet. We are aware that there is a certain level of subjectivity in these interpretations. To diminish this, an interpretation was agreed on after the context analysis was carried out by four investigators with different profiles. Moreover, in order to identify the themes addressed by brands in their communications, we followed the model by Walsh and Beatty (2007). However, an initial search showed that not all of the issues included in the model showed up. The fact that we collected data for our study from a social network and did not use a structured survey, which was the case in these models, can explain these differences. Based on this content analysis, we identified the relevant characteristics and separated them into categories, which are the major variables, and their corresponding attributes.

To process the data, we conducted a descriptive study in order to learn how brands use emojis in their communications. Next, to ratify the existence of significant differences in the way in which each company uses them, we conducted a simple correspondence analysis, which helped us draw a positioning map based on the attributes identified in the qualitative study. Finally, we studied the engagement generated by each brand through their communications with emojis. To confirm whether the engagement generated by the brands was different, we conducted a Z test. This helped determine whether there were significant differences in the proportion of favorites and retweets between companies that was not just a question of randomness.

Results

On completion of the content analysis, we defined 5 categories and 11 attributes. The categories were (1) presence, (2) variety, (3) emotions, (4) use, and (5) themes. Presence and variety were characterized by a single attribute each, which we called “Recognition” and “Heterogeneity,” respectively. Emotions, use, and themes were classified using three attributes each. The emotional appeal component was split into categories depending on whether they expressed “Positive,” “Negative,” or “Neutral” ideas; the use component into “Emphatic,” “Replacement,” or “Mitigation”; and the general themes into “Product” if they expressly mentioned products, “Customer support” if the content was related to customer service communications, or “Social dialogue” if the aim was establishing a social dialogue between the company and the customer on different social topics.

Table 2 summarizes the way in which we measured each category, given that their different nature requires a different approach, as well as the results obtained. This measurement was done in absolute numbers and in percentages, as these percentages are precisely the basis for the correspondence analysis. Thus, to measure presence and, in short, brand recognition, we have considered the number of tweets that the beer brands have posted using emojis, in relation to the total number of tweets sent. To measure variety, as the attribute heterogeneity, we counted how many times each emoji appeared in all tweets and then counted how many different emojis were necessary to make up at least 50% of the total. As the base to calculate the percentage, we took into account the number of different emojis used by each brand. Finally, to measure emotions, use, and themes, we considered the number of times the emoji appeared in these contexts in relation to the total number of tweets with emojis. For these three categories, we needed to consider that the percentage obtained could be higher than 100%, since a tweet could have more than one emoji.

Table 2.

Number and Percentages of Emojis in Brand Communications.

Categories and attributes (% tweets with emojis; 100% = 848)	Brand 1 (34.67)	Brand 2 (25.47)	Brand 3 (22.76)	Brand 4 (17.10)
Presence
Recognition	294 (9.3)	216 (62.8)	193 (32.7)	145 (50.0)
Variety
Heterogeneity	17 (48.6)	2 (18.2)	5 (31.3)	4 (21.1)
Emotions
Positive	191 (65.0)	69 (31.9)	302 (156.5)	85 (58.6)
Neutral	1 (0.3)	21 (9.7)	29 (15.0)	19 (13.1)
Negative	2 (0.7)	0 (0.0)	1 (0.5)	0 (0.0)
Use
Emphasis	124 (42.2)	71 (32.9)	211 (109.3)	63 (43.5)
Replacement	39 (13.3)	14 (6.5)	32 (16.6)	27 (18.6)
Mitigation	19 (6.5)	22 (10.2)	4 (2.1)	2 (1.4)
Themes
Products	115 (39.1)	10 (4.6)	57 (29.5)	37 (25.5)
Customer support	77 (26.2)	87 (40.3)	250 (129.5)	88 (60.7)
Dialogue	24 (8.2)	12 (5.6)	25 (13.0)	16 (11.0)

Note. Percentages appear in parentheses. Presence: Number of tweets including an emoji (Percentage base: Total number of tweets, with or without emojis); Variety: Number of different emojis representing at least 50% of total emojis (Percentage base: Number of different emojis used by each brand); Emotions: Number of times emoji appears in all tweets with emojis (Percentage base: Total number of tweets with emojis); Use: Number of times emoji appears in all tweets with emojis (Percentage base: Total number of tweets with emojis); Themes: Number of times emoji appears in all tweets with emojis (Percentage base: Total number of tweets with emojis).

Presence of Emojis in Brand Tweets

We found that emojis today are still an incipient resource in brand communications since, in general, there are more tweets without them than those that use them. Nonetheless, their use is very unequal. Brands 2 and 4 are using emojis in 50% or more of all the tweets they post. In contrast, Brand 1, although it has the highest number of tweets with emojis, used them in only 9.3% of the cases.

Variety of Use of Emojis

The various emojis that are included at least 50% of the time by brands in a tweet, are those shown in Figure 1. When comparing the behavior of each brand, we find that the variety of emojis used is not uniform across the industry. The four beer brands do have in common that the most frequently used emoji is , but its frequency of use varies significantly between brands. On the other hand, we find that Brand 2 bases most of its communications on emojis and , present in more than 50% of the cases. In contrast, Brand 1 uses a greater variety of emojis in their tweets, while Brands 3 and 4 have an average variety.

Emotions of Emojis

In the four brands analyzed, the emojis used were included in text messages expressing positive feelings. The ones indicating positive emotions most frequently used by the brands are , , , , , and , with a valence that initially seems to match the pictograms. However, the use of emojis to communicate negative emotions is very limited. In fact, we find no emojis used for this purpose in Brands 2 and 4. There are only three emojis used to communicate only negative emotions, which are and , both used by Brand 1, and , used by Brand 3. All these referred essentially to poor experiences in social contexts, for example, poor sports results of sponsored teams. It should be noted that emoji is used in brand tweets for the three types of feelings, that is, positive, negative, and neutral, which reinforces the need to consider the context of the message to interpret the intended emotion of each emoji.

Use of Emojis

In relation to the use of emojis in beer brand communications, they are generally used to emphasize their digital conversations and, second, to replace words on Twitter. They are also used frequently to overcome delicate situations in the brand’s conversation with users or society. Once again, we found that each brand uses emojis differently. Brand 3 is the one that used emojis most frequently for emphasis. Brand 1 tends to use them to replace words. And Brands 1 and 2 resort to them for mitigation, to counteract controversial or negative themes in beer brand-consumer conversations.

Figure 1.

Emojis amounting to at least 50% of total by brands.

The Themes of Emojis

The themes of the emojis used by the leading brands in the industry focused primarily on corporate themes rather than social ones. The corporate themes addressed include products and services, for example, product promotions, sweepstakes, launches, or information about product lines. Customer support communications were essentially related to customer inquiries or questions. In relation to social themes, the most relevant are emojis empathizing with beer brand tweets related to social events, such as sports, events such as International Beer Day, and even as part of social phenomena such as the video game Pokemon GO.

Emojis related to the product and service offerings used most frequently are , , and . This last emoji is used to encourage consumption of lemon beer products. Nevertheless, in every case in this category, the aim was to use an emoji as a graphic icon to replace or reinforce the theme discussed. For example, the emoji , from sports equipment, is used to talk about a football match. In the area of customer service, the emojis most frequently used are , , , and . These emojis, although they are very different, seem logical for they help emphasize moods or soften negative news, while the emoji was also used to replace the product or emphasize it. The emojis most used in general social themes were and . However, others were used specifically for some social topics. Thus, for special dates, the emojis and were used, the latter basically as an apology for forgetting a date. Finally, also within social themes, for celebration of successful events related to sports, the most common ones were and .

When we analyzed the themes addressed by each brand using the emojis, we found that they were different. Specifically, Brand 3 is the one most focused on customer service with emojis, and which addresses social themes. Meanwhile, although Brands 2 and 4 also focused their communications on customer support, they did not do so with as much intensity as Brand 3. Brand 1, however, focuses more on products.

Brand Positioning According to Communication Style Using Emojis

To design the positioning map, we used the percentages of the various attributes calculated previously. There is a statistical dependence between the rows and columns in the correspondence table, that is, there are significant differences in the way in which brands communicate when they use emojis (χ² = 215.118; p < .001). In the model proposed, there are three dimensions. The first dimension explains 53.1% of the model’s total inertia. Dimensions 2 and 3 explain 37.3% and 10.0%, respectively. Given that the first two dimensions explain 90.4%, we decided to remove the third dimension from the analysis. The fact that there were only two dimensions means the data are represented in a two-dimensional space, which facilitates interpretation, and since there is no optimal number of dimensions to be represented, this is a decision left to the researchers, based on the characteristics of the study (Doey & Kurta, 2011).

On the other hand, the type of map on which the analysis is based can vary depending on the typology, with each one having its own strengths and weaknesses. Although it has been noted that the interpretation of the results from symmetric and asymmetric maps are very similar and often lead to the same conclusions (Rojas-Méndez & Hine, 2017), in this article we decided to be cautious and produce both types of maps. The results were consistent, so we decided to follow the recommendations of Greenacre (2017), who stated that symmetric maps are the best choice by default. Figure 2 shows the symmetric map.

To interpret the similarities and differences in the brand profiles, it is necessary to look at their position in relation to the types of emojis used. The brands grouped near an attribute indicate a certain use of emojis, which is proportionally greater than that of the other brands. However, not only is proximity essential, we also have to take into account the importance of each factor for each type, with those having a squared cosine of the rows (SCR) closer to 1 being more important (Greenacre, 2017).

Based on this, we found that the four brands differed from one another. Brand 1 presented a relatively higher proportion of emojis with a negative connotation (SCR Factor 1 = 0.921), related to company products (SCR Factor 1 = 0.688) and, also used a greater variety of emojis in their communications (SCR Factor 2 = 0.561), with the two first categories being important for Factor 1, and variety being significant, especially for Factor 2, which has less explanatory power in the map. Brand 2 stood out in the use of emojis with neutral comments (SCR Factor 1 = 0.950), as well as in their use for recognition of users (SCR Factor 1 = 0.799), with both characteristics having an SCR for the row points close to 1, especially in the first case. Brand 3 had a relatively higher proportion of the use of emojis as a way of providing customer support (SCR Factor 2 = 0.714), in positive comments (SCR 2 = 0.570), and for emphasis (SCR Factor 2 = 0.691), the three characteristics having a significant weight in the vertical dimension, especially the first one. Finally, Brand 4, with a less defined positioning, showed a significant proportion of emojis used for dialogue and replacement, although these are not significant characteristics in any of the two dimensions analyzed.

Figure 2.

Positioning map according to the communication strategy using emojis.

In summary, the positioning map indicates that the use of emojis in the communication style of Brand 3 is for customer service, they are used in a positive way, and they are used to emphasize messages. This use is contrary to the use made by Brand 1, which employed emojis many times in relation to company products and, also, with a negative meaning. Brand 2 used them in a more neutral manner and with the main objective of brand recognition. However, Brand 4 has no clear differentiation from the other brands in its communication style with emojis.

Engagement Generated in Brand Communications

After analyzing the feedback of these communications, we found that several of the tweets with emojis were retweeted and/or marked as favorites. This means that brands are generating engagement among the users who chat with them. Specifically, Brands 2 (47.5% favorite and 49.7% retweeted) and 3 (62.9% favorites and 41.2% retweeted) did so most. In contrast, Brand 1 shows very low percentages (5.8% favorites and 4.8% retweeted), although it is the one using emojis most frequently, with Brand 3 at an intermediate level (31.2% favorites and 37.1% retweeted). When we conducted the Z test to compare the proportion of tweets marked as favorites, we found that these had significant differences when comparing brands in pairs. Yet there were fewer differences in the proportion of retweets, with Brand 3 being similar to Brands 2 (Z score = 1.723; p > .05) and 4 (Z score = 0.763; p > .05).

Discussion

A combined reading of results shows that this is a very new initiative in beer brand communications and that it is still in the early stages. The fact that only two brands used them in their communications at least in half of the tweets they posted indicates that it is still a somewhat novel way of communication and not yet well established in the industry. When companies do introduce them, the emojis used are quite varied. This variety can be explained by the fact that there are no set patterns for their use and that each brand uses different emojis without the pictograms having any predetermined meanings. This implies that when researchers analyze emojis, it is necessary to examine the text and the context of the message in which they are included (van Zyl & Meiselman, 2015; Vidal et al., 2016).

As for how brands use emojis in their communications, our results do not differ from what researchers have attributed to them in general. Emphasis, replacement of words, and toning down controversial or negative messages are the most common uses found in our study, and these have also been evidenced in research in this area from a conversational marketing perspective (Köster & Mojet, 2015; Skovholt et al., 2014). The results of this study also confirm the widely held belief found in the literature that emojis are used essentially to communicate positive emotions (Das et al., 2019; Donovan, 2016; Riordan, 2017; Sampietro, 2016b). However, the specific emojis that are used to communicate these emotions have not been defined. In fact, we found that each brand used different types to express the same valence and intensity of the same emotion. The explanation is that regardless of the emotion to be communicated, these elements reinforce the complicity or the polarity of the emotion expressed in the brand tweets (Novak et al., 2015). This is the case of the emoji , which is used by companies to express the three types of emotional valence in their communications, whether it be positive, negative, or neutral.

We have not found in the literature to date a paper examining the themes used in emoji brand communications. This study includes primarily two major categories: corporate topics and social topics. The most significant themes in the corporate area are those referring to brand and, more specifically, the product and customer service. It should be noted that the emoji pictogram that clearly represents the product or service, which in the case of the beer industry is the emoji , is frequently used in the communications of all the brands in the industry (Novak et al., 2015; Vidal et al., 2016).

As opposed to many other studies that consider emojis to be just one more resource in social and brand communications (Riordan, 2017; Skovholt et al., 2014), the qualitative results indicate that they are used for something more than that. In fact, when the differences are examined by correspondence analysis, the basic hypothesis of this article is confirmed. The brands do use emojis differently, and they become an instrument for differentiation in their communication style, even if they do not necessarily do it consciously or as part of a predetermined strategy. Of the four brands analyzed here, only one does not show a clearly defined style.

Thus, Brand 1 is positioned with a great variety of emojis in its communications, referring primarily to items related to the product. Specifically, they are mainly used to replace words, which can explain the wide variety. They are also characterized by using them in comments with negative connotations, although this outcome should be interpreted with caution given the low frequency of emojis with a negative valence. Brand 2 is differentiated by the abundant presence of emojis in communications that, for the most part, do not evoke emotions. The aim when using them is, basically, to mitigate the content of the tweets. The positioning of Brand 3 uses emojis that communicate primarily customer support topics and that help emphasize and generate positive emotions. Brand 4, although it has the greatest proportion of emojis in its communications, does not differentiate itself from the other brands in any of the aspects analyzed.

Finally, even when Arya et al. (2018) stated that brand communications with emojis help generate engagement, the results of this study show that they do not always generate the same level of engagement and that it depends on the communication style used. Thus, Brand 3, which has the most clearly defined style toward customer service and care, generates the highest engagement. In addition, the messages have more positive emotions and the brand uses emojis for emphasis. These results are in line with those of Das et al. (2019). They concluded that the presence of emojis in marketing messages led consumers to experience a more positive impact resulting, then, in greater engagement, which in this case meant a higher purchase intention. In turn, Brand 2, which attempts to use emojis to reinforce its presence, is in second place in engagement. In contrast, Brand 1, with a great variety of emojis that focus on its products, is the one with the least engagement, even less than Brand 4, which shows no clear positioning.

Conclusions

This study shows that emojis are an element that should be taken into account in brand communications, even though they are still not used by companies as a usual resource in their digital brand communications. According to the results obtained, brands are using emojis differently in their customer communications, and they are no longer just a mere resource in a message, but rather a differentiating element for their brand positioning. Nonetheless, this study could not confirm that emojis are being purposefully used to achieve this positioning. In fact, there are various reasons that could explain the existing differences between the communication styles shown, for example, the personality of the people in charge of posting the messages online.

Emojis are frequently used for emphasis, to express positive feelings and to address corporate topics, and these are the communications that are liked and shared by their followers the most. However, it should be noted that this study is limited to the analysis of four brands in a specific sector, the beer industry, which, nonetheless, represent 40% of total production in Spain (Ministry of Agriculture and Fisheries Food and Environment, 2017). Likewise, from this study it cannot be concluded that having wide acceptance generates engagement beyond being marked as favorites or retweeted, since we have not looked at the communications posted by the followers in their Twitter profiles. It would be interesting in future research to analyze the existing alignment between the patterns of use of emojis in brand communications and in those of followers, as well as expanding this analysis to new beer brands and other sectors.

The evidence found could help companies reflect on whether designing a communication strategy using emojis is desirable. They could think about how to give long-term value to the brand by using them as a unique and differentiating element of their identity, and it could become what we could call a “brandemoji code.” If companies do not have a deliberate strategy to use emojis in their communications, they should consider designing one that gives them a long-term competitive advantage. They could thus develop a linguistic and semantic code using emojis with their own specific style, which would also help them spread its use. It could become a sort of corporate identity code in the conversations generated between the brand and its community, among the members in the community itself, and it could even spill over into other areas to be used by third parties.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This work was supported by the University of Malaga, Spain [grant Proyect Diagnosis and Positioning of SMIs].

ORCID iDs

Ana María Casado-Molina

María Mercedes Rojas-de Gracia

Author Biographies

Ana María Casado-Molina earned her PhD degree from the University of Málaga. She is a professor of the Department of Economics and Business Administration, University of Málaga (Spain). Her line of research consists on brand communication, reputation, and engagement.

María Mercedes Rojas-de Gracia earned her PhD degree from the University of Málaga. She is a professor of the Department of Economics and Business Administration, University of Málaga (Spain). Her research focuses on the study of consumer decision making and stakeholder behavior on social media.

Pilar Alarcón-Urbistondo earned her PhD degree from the University of Málaga. She is a professor of the Department of Economics and Business Administration, University of Málaga (Spain). She is working on the consumer and stakeholder behavior, the social image of the tourism destinations, and brand image.

María Romero-Charneco is a PhD student in the economics and business program at the University of Málaga and CEO of a start-up called Levelbots. Her research focuses on consumer behavior in chatbots, computer-mediated communication, and platforms of social recommendations.

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