Social Media for People in Suits #
Apart from social media platforms themselves, these media are also of high interest for other companies. Social media can be a valuable tool for companies to connect with their customers, promote their products or services, and build their brand.
For example, a recent study finds that consumer-posted photos are strong predictors of restaurant survival1. Interestingly, the informativeness of photos (e.g., the proportion of food photos) relates more to restaurant survival than do photographic attributes (e.g., composition, brightness).
Measuring success #
When is a company successful? As you can see from numerous unicorns, other factors are often important as well. Here we will focus mainly on what can be measured directly. A factor that cannot be measured is challenging to analyze.
Conversions and other Key performance Indicators #
Key Performance Indicators (KPIs) determine the general vision, such as a Macro conversion goal. However, conversions per se are often rare events. Conversion is the number of sales of a product compared to the number of people who visit a website to look at that product or the number of phone calls or sales visits made. Therefore, micro conversions such as likes, followers, and retweets are often used as KPI in social media. Micro conversions precede the achievement of the main goals. Each micro-conversion moves visitors down the conversion funnel. The following content defines micro-conversions, examples in a social media context and underlines the importance of micro-conversions.
A micro conversion is an action that can bring the user closer to the macro conversion. Users take these small actions during their customer journey. They are the individual funnel steps that lead to a macro conversion2. Micro conversions can be divided in two groups:
- Process milestones that lead directly to a macro conversion such as comparing different products (e.g., adding products to the online basket).
- Secondary actions that do not directly result in a macro conversion but can sometimes represent future macro conversions. For instance, sharing content, commenting, liking.
Micro conversions lay the groundwork for the primary goal. The micro-conversions move potential clients toward an outcome. Indeed, they are essential. These user engagements increase users’ purchase intention3. They can help a visitor to adapt and reduce hesitations or objections if they arise. In some cases, it takes a lot of micro-conversions to achieve a macro conversion. They might not affect today, but they easily could tomorrow. Micro conversions can increase awareness of the company. Usually, people only share content that they like a lot. If users share the product image or texts, it means they are already interested. Posting interesting, useful, or viral content can increase reach and attract new people for low or even no pay.
In addition, micro-conversions can be a sign of social proof. They make users more loyal and more likely lead to a macro conversion. In practice, these small engagements primarily work not immediately but in the long term. For example, researchers conducted a field experiment on acquired Facebook page likes and found them positively affect offline customer behavior4. The results demonstrate the value of likes beyond the Facebook activity itself. Another research analyzing daily data for 45 brands in 21 sectors shows that brand fan following improves brand awareness, purchase intent, and customer satisfaction5. Tracking micro conversions allows companies to understand the mindset of their customers. Collecting the data about micro-conversions might be particularly useful for identifying user paths. They also should be tracked and quantified to know user interactions and retention. It explains the customer journey to a macro conversion. Moreover, it helps to turn potential clients into paying clients.
We consider micro-conversion as a way of additional communication between companies and users. When companies have a broader view of users’ behavior, they can get more valuable insights into keeping users engaged6. Visualization of micro-conversions data helps analyze how micro-conversions work and how to take advantage of them. Due to changing the process of micro conversions and applying different strategies, companies can create a better customer experience. A better understanding of the customers and critical information about the audience obtained by micro-conversion analysis improve lead nurturing. Therefore, micro-conversions play a crucial role in the overall customer journey and should deserve companies’ attention.
Online Chatter - Let the people talk! #
Online chatter refers to the discussions, conversations, and other forms of communication that take place on the internet, often in social media or forums. This can include anything from casual conversations between friends to more formal debates and discussions on specific topics.
Electronic word-of-mouth (eWOM) is a specific type of online chatter that refers to the communication of information and opinions about products, services, or brands that takes place on the internet. The communication channel (the “medium”) shapes the message such that we express things differently online than offline7. Nevertheless, eWOM can be a powerful influence on consumer decision-making, as people often rely on the opinions of others when evaluating products or services. Notably, eWOM plays an increasingly important role in shaping consumers’ behavior and preferences89.
In order to effectively manage eWOM, it’s important for companies to monitor online conversations about their brand and products, and to respond to any negative eWOM in a timely and appropriate manner. This might include addressing any concerns or complaints raised by customers, providing accurate and transparent information about the company and its products, and thanking customers for their positive feedback.
Research showed that information dissemination is dominated by WOM rather than by advertising10. In particluar, interesting products get more immediate WOM but, contrary to intuition, do not receive more ongoing eWOM overall11. In contrast, products cued more by the environment or are more publicly visible receive more eWOM right away and over time.
The level of personality similarity between two social media users has a positive impact on the likelihood of a subsequent purchase from a recipient of a eWOM message after exposure to the WOM message of the sender8. In particular, exposure to eWOM messages from similar users in terms of personality, rather than dissimilar users, increases the likelihood of a postpurchase. In addition, WOM originating from users with low levels of emotional range affects similar users, whereas for high levels of emotional range, increased similarity usually has the opposite effect8.
The likelihood that followers who are exposed to eWOM will subsequently make purchases increases with the geographical proximity of followers to users12. There is an explanation why geographical distance still plays a role in WOM online is social identification: Since consumers can develop a sense of social identity based on their physical location, information about users’ physical proximity could trigger social identification with others online.
Contrary to popular belief, controversial things are not necessarily more likely to be discussed13. Controversy drives discussion at low levels, but additional controversy decreases the likelihood of a debate beyond a moderate level of controversy13. Two countervailing processes drive the controversy-conversation relationship: Controversy increases interest but simultaneously increases discomfort.
Negative publicity can increase purchase likelihood and sales by increasing product awareness14. Consequently, negative publicity has differential effects on established versus unknown products14.
The Dangers of Social Media: The Online Firestorm #
A social media crisis is a situation in which a company or organization experiences negative attention or backlash on social media platforms, often as a result of a mistake, controversy, or negative event. In these situations, the intense emotions and feelings of the people involved can quickly escalate, leading to a rapid spread of those emotions and a strong response from others.
While eWOM and online firestorms are both related to the sharing of information and opinions online, there are some key differences between the two. eWOM is typically more measured and rational, as it involves people sharing information and opinions based on their personal experiences with a product or service. Online firestorms, on the other hand, are often more emotional and reactive, as they are typically triggered by a specific event or stimulus that provokes a strong response from people.
Online firestorms can have a significant impact on the people and organizations involved, as they can lead to public backlash, damage to reputations, and loss of support or customers15. They can also have broader consequences, as they can fuel political polarization and social division.
In order to effectively manage a social media crisis, it’s important for a company to have a plan in place to address the situation quickly and effectively. This might include:
- Monitoring social media channels for early warning signs of a crisis.
- Responding to the crisis as quickly as possible.
- Apologizing and taking responsibility for any mistakes that may have led to the crisis.
- Providing accurate and transparent information to the public.
- Taking steps to correct the problem and prevent similar issues from happening in the future.
Firms need to be able to handle online firestorms and negative eWOM in online brand communities. First, potential firestorms should be detected16. Brand community managers should consider complainers’ message formulation beyond what is said and their relationship with other community members. Second, firestorms should be prevented16. Unlike in a traditional service recovery setting, prevention depends on satisfying both the complainant and the brand community. Third, if all else fails, some possible damage should be mitigated16. Rather than consistently posting the same message, managers should vary the use of empathy and explanation to reduce the further virality of negative eWOM messages.
If these methods prove unsuccessful, a new strategy can be employed, called the escalation strategy17. A successful application of the escalation strategy involves:
- Framing of one’s positioning and the opposing side in ways that accentuate the ideological fault-line between the brand and its detractors
- Launching counterattacks that directly infuriate brand critics.
These communicative behaviors motivate and guide brand supporters to:
- Launch own distributed counterattacks in defense of the brand, resulting in consumer-to-consumer interactions across the ideological fault line that further deepen the opposition between both sides
It typically takes years to build a brand with positive brand perceptions, so gaining information about immediate consequences and long-term effects of social media firestorms on consumers and brands is crucial. The results of firestorms can last years after their occurrence18. The key characteristics that enable managers to predict the developments and consequences of a firestorm span both trigger characteristics, which they can evaluate when the first tweet or post appears, and firestorm characteristics, which unfold over time. Managers can develop warning systems based on the illustrative summary of research findings. With such warnings, they can allocate resources to handle the most threatening social media firestorms more efficiently.
It’s also important for a company to have a team in place that is trained to handle social media crises and to work together effectively to address the situation. This might include individuals from marketing, PR, and customer service, among others.
Another term for such situations with is often used in research is “online firestorm”. In German-speaking countries, this term is also often referred to as a “shitstorm”. Even though online firestorms are a new phenomenon, their dynamics are similar to how rumors are circulated. However, the most crucial difference and the essential characteristic that led to the terminology are the levels of aggression involved15. When a focal firm undergoes an online firestorm, nonfocal firms offering similar products or services can suffer from a negative spillover effect19. However, they can also benefit from customers switching from the troubled firm, which we call the competitive effect19.
Example: One of the first-ever examples of massive customer outrage was created as early as 2004. A biker found out that the Kryptonite Evolution 2000 lock that was supposed to be one of the safest on the market could be opened easily with a pen. The video that showed the whole effort was posted on an online biker forum and soon became very popular, attracting more than two million views in only one week.
Online Reviews #
Online reviews are evaluations or assessments of a product or service that are written by customers and published on the internet. They can be found on a variety of websites, including online retailers, review websites, and social media platforms. Online reviews can be helpful for consumers who are considering purchasing a product or using a service, as they provide insight into the experiences of others and can help customers make informed decisions.
Online reviews can also be helpful for businesses, as they provide feedback on their products or services and can help businesses improve. However, businesses should be aware that online reviews can also be negative, and it is important to handle negative reviews in a professional and constructive manner. Often, a single scalar value cannot capture the information embedded in product reviews20. Instead, reviews are by nature unstructured and multifaceted20.
It is important to note that online reviews should not be the only factor that you consider when making a purchasing decision, as they may not always be accurate or unbiased. It can be helpful to read a variety of reviews and to take them into consideration along with other factors, such as the reputation of the business, the quality of the product or service, and the price.
Consumers use the identity-descriptive information of reviewers to supplement or replace product information when making purchase decisions and evaluating the helpfulness of online reviews21. As a result, people rate reviews containing identity-descriptive information more positively, and the prevalence of reviewer disclosure of identity information is associated with increases in subsequent online product sales21. Moreover, shared geographical location increases the relationship between disclosure and product sales, thus highlighting the vital role of geography in electronic commerce21.
The high volume of reviews published for single products makes it harder for individuals and manufacturers to locate the best reviews and understand the actual quality of a product. Factors such as subjectivity, informativeness, readability, and linguistic correctness in online reviews influence sales and perceived usefulness22. In contrast to purely subjective or objective reviews, those with a mixture of objective and highly subjective sentences are negatively associated with product sales22. At the same time, ratings with mixed-objectivity levels are rated more informative (or helpful) by other users22.
Segmenting-targeting-positioning #
Segmenting, targeting, and positioning (STP) is a marketing strategy that involves dividing a market into smaller groups of consumers with similar needs or characteristics, selecting one or more of these segments as a target market, and then designing a marketing mix (product, price, promotion, and place) that will appeal to the needs and preferences of the target market.
By using STP, companies can effectively target specific groups of consumers and create marketing campaigns that are tailored to their needs and preferences, resulting in more effective and efficient marketing efforts.
Segmentation #
Segmenting involves dividing the market into smaller groups of consumers based on characteristics such as demographic, geographic, psychographic, or behavioral factors. For example, a company might segment the market for sports shoes based on age, gender, or level of athletic ability. Ultimately, any type of segmentation aims to identify high-yield target markets that are likely to meet growth potential, profitability, or other specific goals. In turn, these segments can be targeted (see next chapter).
Following the core idea that segmentation enables a better understanding of consumer behavior and thus allows a better focus on the target group, several studies were have been employed to achieve segmentation of online or social media customers. For example, Vellido et al. (1999) investigated consumers’ opinions on online purchasing and online vendors that seem to consist of the underlying dimensions control and convenience, trust and security, affordability, ease of use, and effort/responsiveness23. Then, these dimensions are used to specify seven segments (e.g., unconvinced, cost-conscious, complexity avoiders). Another approach is to use customers’ motivations to use the internet (e.g., fact collectors, entertainment seekers) for segmentation24. Alternatively, companies can perform a cluster analysis based on factors like Internet convenience, perceived self-inefficacy, or Internet distrust25.
Psychographic segmentation - The Dark Arts of Marketing #
Psychographic segmentation clusters previous, prospective, or current customers by personality characteristics. It starts by analyzing and grouping similar characteristics into segments. This grouping enables companies to target people who think the same way and aspire to similar interests. This process is crucial to position the same product differently for different types of people without making any essential changes to the product or service. Since social media data allows one to mine personal traits, psychographic segmentation is a common approach.
But how do companies obtain information about these people? The power of big data influences psychographic segmentation as it helps gather vast amounts of unstructured data about lots of different people, which can then be structured and manipulated to create segments. A textbook example of psychographic segmentation is the Facebook-Cambridge Analytica data scandal in early 2018, where Cambridge Analytica used the personal data of millions of people’s Facebook profiles without their approval. They used psychographic segmentation methods based on these massive amounts of personal data to launch individualized marketing campaigns for political advertising. Cambridge Analytica used all the data they had gathered to create models of people with similar political orientation and psychological characteristics and then aggressively displayed them on basically all social media platforms to influence the US presidential election.
Another successful example of psychographic segmentation usage is Porsche’s customized five-factor personality model that was used for their brand new “Every Day Porsche” marketing campaign. Since Porsche is a subsidiary of Volkswagen AG, it has access to a vast dataset containing large amounts of data of former and current Volkswagen customers to create five different psychographic segments. Combining usual demographic marketing methods with the brand new five-factor personality model lead to a 35% sales increase in Porsche 911’s in just 60 days.
The criticism on psychographic segmentation in combination with the usage of big data is obviously about data protection.
Targeting #
Target advertising is a form of advertising aimed at a specific target group (e.g., market segment) and is placed so that the advertisement is shown to precisely this user group. Context-related text advertising can reduce wastage in online advertising. In addition, the relevance of the ad is increased, as it is only shown to potentially interested people. Various methods are used to select the target group. Often the content environment serves as an orientation to whom ads are presented. Typical approaches are Content Targeting, Retargeting, Social-Media-Targeting and psychographic targeting. But, of course, there are also countless other types (even hybrid forms).
In the case of retargeting, service providers try to find lost customers on the Internet and offer products that customers have previously looked at online portals. In this way, an attempt is made to convey the same product to the user over weeks.
Targeting in STP involves choosing which segments to focus on and developing marketing strategies to appeal to those segments. A company might choose to target a particular segment based on factors such as the size of the segment, the potential for growth, the level of competition, or the company’s resources and capabilities.
In-class task: Reading exercise
Please read the article “The new dot.com bubble is here”. Afterwards we’ll discuss the following questions in-class:
- What are the implications?
- How does it affect companies on Social Media?
Downsides of targeting #
Is targeting always good? Targeting seems to be a perfect method to advertise more effectively. However, if the advertising is both content-appropriate and intrusive, it can hurt the effectiveness of the advertising26. Nowadays, firms are increasingly employing target marketing as it enables the company, among other things, to reach new customers more effectively, increase brand awareness, and in the long-term, increase sales. However, the following text aims at providing a compact overview of some of the possible downsides associated with target marketing.
Firstly, as the targeting method is gaining increased popularity, concerns of data and privacy protection arise. Firms are accumulating a large amount of relevant information about an Internet user by using cookies or other technologies. In doing so, companies collect data to analyze and target potential customers based on their needs and desires. The problem, however, is that Internet users have little or no knowledge and control about the private information firms have of them and how it is used. Moreover, if consumers have concerns about their privacy being invaded, reactance can occur as a result. This reaction is undesirable for marketers as customers do not act in an intended way by thus ignoring or resisting the ad27. Strengthening privacy rules could lead to a more effective performance of online advertising27. All these considered points emphasize the need for further data protection laws to better secure users‘ privacy. However, these new rules also need to provide a clear and sufficient guideline for advertisers as the existing laws are too elusive to follow and obey, which leaves consumers in a vulnerable position.
Secondly, implementing focused targeted marketing strategies can raise skepticism and criticism about their ethical components. For example, there has been extensive media attention to the targeting of vulnerable consumer segments, i.e., children and young adults and the elderly, with potentially harmful products. These include, among others, fast food products, contraceptives, tobacco, and alcohol. The vulnerable consumer segments are said to be less likely to make rational and mature judgments. Therefore, the targeting of harmful products to these segments is considered inappropriate and may lead to increased media controversy resulting in a poor reputation of the firm and eventually lost sales. Hence, marketers must pay close attention to the ethics of their targeting strategies28.
Thirdly, coming from a different perspective, precise targeting may incur high costs for the firm as they have to develop differentiated marketing strategies for each identified segment. Moreover, another possible threat of targeting is a limited audience by a too-narrow focus on customers. Hence, there is an increased risk of missing the pursued consumer segment or, even worse, targeting the wrong customers.
Targeting campaigns may also prove unsuccessful due to an inappropriate selection of advertisements. For example, if a user chooses to hide its identity by disabling cookies, there is a lack of personal information that can be used for targeting. Nevertheless, even if the user provides enough information, it is possible that the data only reflects what they were previously attentive to and may not hold for current or future interests.
Positioning #
In marketing, positioning refers to the way in which a company or product is perceived by consumers in the marketplace. Positioning involves creating a unique and differentiated image for the product or service in the minds of the target market. It involves creating a unique and distinct image or identity for the company, service or product in the minds of consumers, and differentiating it from its competitors.
There are several steps involved in positioning a company or product:
- Identifying target customers: The first step in positioning is to identify the specific group of customers that the company or product is targeting.
- Conducting market research: Market research is used to gather information about the needs and preferences of the target market, as well as the competitive landscape.
- Defining the unique selling proposition (USP): The USP is the unique benefit or value that a company or product offers to customers, and is a key component of positioning.
- Developing a positioning statement: A positioning statement is a clear and concise summary of the unique value proposition of the company or product, and how it will meet the needs of the target market.
- Communicating the positioning: Once the positioning has been defined, the company will need to communicate it to the target market through marketing efforts such as advertising, branding, and public relations.
Effective positioning can help a company or product stand out in a crowded marketplace, and can be a key factor in its success.
Challenges #
While the challenges for users are (mostly) not associated with additional costs and constitute their core business for platforms, regular companies first had to set up departments for the social media agendas. However, the challenges are not only of a monetary nature, but require specialised personnel.
Social media boycott & buycot campaigns #
A social media boycott is a campaign in which individuals or groups of people decide to stop using a particular social media platform, often in protest of the platform’s policies or actions. A social media buycot, on the other hand, is a campaign in which individuals or groups of people decide to use a particular social media platform more actively in order to support it.
Both boycotts and buycots can be used as a form of activism, with the goal of influencing the policies or actions of the social media platform in question. Boycotts can be effective in drawing attention to an issue and potentially forcing the platform to make changes, while buycots can be used to show support for a platform and encourage it to continue its current policies or actions.
It’s important for companies and organizations to be aware of and prepared for social media boycotts and buycots, as these campaigns can have a significant impact on their reputation and bottom line. In order to effectively manage these campaigns, it’s important to have a plan in place to monitor and respond to them, and to be transparent and responsive to the concerns of users.
Example: In July 2020, the chief executive officer of Goya, a large Latin food brand, praised then president Donald Trump, triggering a boycott and a counter “buycott” movement supporting the brand.
A recent study by Liaukonytė, Tuchman and Zhu analyzed this “quasi-experiment”. Boycott-related social media posts and media coverage dominated buycott ones, but the sales impact was the opposite: Goya sales temporarily increased by 22%. However, this increase fully dissipated within few weeks. While there is a large sales increases (56.4%) in heavily Republican counties there is no boycott effect in heavily Democratic counties or among Goya’s core customer base (i.e., Latino consumers).
Cancel Culture #
A phenomenon called cancel culture has gained more and more attention over the past years. It turned out to be quite an effective way for people in general and consumers, mainly to show their disagreement towards the actions of public figures, organizations, or companies.
If something is canceled, it is ended, voided, no longer wanted. People withdraw their support. In the case of cancel culture, it is a massive movement with thousands of people. The aim is to draw attention to the person’s or company’s bad behavior, call them out publicly, boycott their work, take away their power through unfollowing their social media platforms. Any form of abandonment is desired.
Following, let us focus on why these movements happen. From an overall perspective, cancel culture movements often empower traditionally oppressed groups. Especially controversial, unacceptable, or highly problematic statements to sexism, heterosexism, homophobia, racism, bullying and related issues have shown to be the starting point of cancel culture movements.
Example: By looking at the recent example of Netflix, we analyze how the movement originated and became viral. In 2020 Netflix found itself in the firing line of an online shitstorm regarding the award-winning film called “Cuties”. Netflix released a controversial poster showing the 11-year-old cast members in provocative poses. Maimouna Doucore’s debut feature is a coming-of-age drama about an 11-year old Muslim girl focusing on her inner conflict between the traditional Muslim culture and the open Western culture. Hundreds of people showed their disappointment on social media platforms about Netflix featuring this film. Hashtags like #boycottnetflix, #cancelnetflix. #cutiesischildabuse got viral. Twitter comments like the following were posted: “You know something is wrong when a movie about 11-year old girls is rated MA 15+“ by Eric Asollan on Aug 22, 2020, at 9:38 AM. People were emotionally involved and initiated a petition to have “Cuties” removed from Netflix. The participation was overwhelming. More than a quarter of a million signatures were raised. Netflix apologized for releasing the inappropriate poster. However, the poster does not represent the film, and therefore it will not be removed from the streaming website. Despite the official apology, Netflix lost a massive number of subscribers and a moral reputation. This controversy completely overshadows the movie “Cuties” and subsequently lost a massive number of viewers.
When confronted with a cancel culture, it is essential to be fast with your reaction. Non-reacting allows detractors to continue posting unattended. There are different reaction strategies. These include ignoring, censoring, counterstatements, content bumping, and changing behavior. The first two strategies showed to be least effective in controlling a social media movement. The vitality of tweets increased, and user comments became harsher. Counter-stating often leads attackers to intensify their movement because they disagree with the arguments. More effective strategies included an apology combined with the possibility of discussion and sometimes a counterstatement.
Practical assignment III #
SQL-prerequisites: Like-Operator, Casting
In line with the previous assignments, the following questions refer to a table called youtube_tweets (please import it as we did in the first session).
Use the DuckDB Shell to answer the following questions:
- How many tweets contain the phrase “helene fischer” (case insensitive)?
- How many tweets contain the christmas tree emoji (🎄)?
- How to get for each day the proportion of tweets written by verified accounts sorted ascending by the day?
Please submit your SQL-query as well as a short and precise textual answer via Learn@WU.
References & further reading #
- Slides: The Company
- He, S., Hollenbeck, B., & Proserpio, D. (2022). The market for fake reviews. Marketing Science.
- Babić Rosario, A., De Valck, K., & Sotgiu, F. (2020). Conceptualizing the electronic word-of-mouth process: What we know and need to know about eWOM creation, exposure, and evaluation. Journal of the Academy of Marketing Science, 48(3), 422-448.
- Liaukonyte, J., Tuchman, A., & Zhu, X. (2022). Spilling the Beans on Political Consumerism: Do Social Media Boycotts and Buycotts Translate to Real Sales Impact?. Marketing Science Frontiers.
Zhang, M., & Luo, L. (2022). Can consumer-posted photos serve as a leading indicator of restaurant survival? Evidence from yelp. Management Science. ↩︎
Lee, J., Podlaseck, M., Schonberg, E., Hoch, R., & Gomory, S. (2000). Understanding merchandising effectiveness of online stores. Electronic Markets, 10(1), 20-28. ↩︎
Choi, Y. (2019). Determinants of user engagement in social commerce. International Journal of Customer Relationship Marketing and Management (IJCRMM), 10 (4), 43-56. ↩︎
Mochon, D., Johnson, K., Schwartz, J., & Ariely, D. (2017). What are likes worth? A Facebook page field experiment. Journal of Marketing Research, 54(2), 306-317. ↩︎
Colicev, A., Malshe, A., Pauwels, K., & O’Connor, P. (2018). Improving consumer mindset metrics and shareholder value through social media: The different roles of owned and earned media. Journal of Marketing, 82(1), 37-56. ↩︎
Kolb, B. M. (2016). Marketing strategy for the creative and cultural industries. Routledge. ↩︎
Berger, J., & Iyengar, R. (2013). Communication channels and word of mouth: How the medium shapes the message. Journal of consumer research, 40(3), 567-579. ↩︎
Adamopoulos, P., Ghose, A., & Todri, V. (2018). The impact of user personality traits on word of mouth: Text-mining social media platforms. Information Systems Research, 29(3), 612-640. ↩︎ ↩︎ ↩︎
Babić Rosario, A., De Valck, K., & Sotgiu, F. (2020). Conceptualizing the electronic word-of-mouth process: What we know and need to know about eWOM creation, exposure, and evaluation. Journal of the Academy of Marketing Science, 48(3), 422-448. ↩︎
Goldenberg, J., Libai, B., & Muller, E. (2001). Talk of the network: A complex systems look at the underlying process of word-of-mouth. Marketing letters, 12(3), 211-223. ↩︎
Berger, J., & Schwartz, E. M. (2011). What drives immediate and ongoing word of mouth?. Journal of Marketing Research, 48(5), 869-880. ↩︎
Todri, V., Adamopoulos, P., & Andrews, M. (2022). Is distance really dead in the online world? The moderating role of geographical distance on the effectiveness of electronic word of mouth. Journal of Marketing, 86(4), 118-140. ↩︎
Chen, Z., & Berger, J. (2013). When, why, and how controversy causes conversation. Journal of Consumer Research, 40(3), 580-593. ↩︎ ↩︎
Berger, J., Sorensen, A. T., & Rasmussen, S. J. (2010). Positive effects of negative publicity: When negative reviews increase sales. Marketing Science, 29(5), 815-827. ↩︎ ↩︎
Pfeffer, J., Zorbach, T., & Carley, K. M. (2014). Understanding online firestorms: Negative word-of-mouth dynamics in social media networks. Journal of Marketing Communications, 20(1-2), 117-128. ↩︎ ↩︎
Herhausen, D., Ludwig, S., Grewal, D., Wulf, J., & Schoegel, M. (2019). Detecting, preventing, and mitigating online firestorms in brand communities. Journal of Marketing, 83(3), 1-21. ↩︎ ↩︎ ↩︎
Scholz, J., & Smith, A. N. (2019). Branding in the age of social media firestorms: How to create brand value by fighting back online. Journal of Marketing Management, 35(11-12), 1100-1134. ↩︎
Hansen, N., Kupfer, A. K., & Hennig-Thurau, T. (2018). Brand crises in the digital age: The short-and long-term effects of social media firestorms on consumers and brands. International Journal of Research in Marketing, 35(4), 557-574. ↩︎
He, S., Rui, H., & Whinston, A. B. (2018). Social media strategies in product-harm crises. Information Systems Research, 29(2), 362-380. ↩︎ ↩︎
Archak, N., Ghose, A., & Ipeirotis, P. G. (2011). Deriving the pricing power of product features by mining consumer reviews. Management Science, 57(8), 1485-1509. ↩︎ ↩︎
Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291-313. ↩︎ ↩︎ ↩︎
Ghose, A., & Ipeirotis, P. G. (2010). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE transactions on knowledge and data engineering, 23(10), 1498-1512. ↩︎ ↩︎ ↩︎
Vellido, A., Lisboa, P. J. G., & Meehan, K. (1999). Segmentation of the on-line shopping market using neural networks. Expert systems with applications, 17(4), 303-314. ↩︎
McDonald, W. J. (1996). Internet customer segments: an international perspective. Enhancing Knowledge Development in Marketing, American Marketing Association, Chicago, 338-344. ↩︎
Brengman, M., Geuens, M., Weijters, B., Smith, S. M., & Swinyard, W. R. (2005). Segmenting Internet shoppers based on their Web-usage-related lifestyle: a cross-cultural validation. Journal of Business Research, 58(1), 79-88. ↩︎
Goldfarb, A., & Tucker, C. (2011). Online display advertising: Targeting and obtrusiveness. Marketing Science, 30(3), 389-404. ↩︎
Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546-562. ↩︎ ↩︎
Smith, N. C., & Cooper-Martin, E. (1997). Ethics and target marketing: The role of product harm and consumer vulnerability. Journal of Marketing, 61(3), 1-20. ↩︎