Data Mining in Social Media Marketing

Relevancy (in Advertising) Now that we've discussed what data mining is, how it works, and the good and bad sides of it, let's talk about how it works in terms of advertising. The word 'relevancy' is pretty broad, but it is a good way of describing the relationship between advertisements and data mining. The concept of relevance is fundamental to information retrieval (Bookstein 1979); if an advertisement does not appeal to a person, they are not going to click on it, and therefore the business is losing customers, in a sense. There are four criteria that are considered in order to assess document relevance: aboutness (the quality or fact of relating to or being about something) , coverage (the extent to which something deals with or applies to something else) , appropriateness (the quality of being suitable or proper in the circumstances) , and reliability (the quality of being trustworthy or of performing consistently well) (Pereira, Dragoni, Pasi 2009). . Relevance is a central concept in human communication, and it is a term we use constantly and loosely. Think about the last time you told a friend about something, and then later on that day, you saw an advertisement for that exact same thing. It makes you think for a second, is this company stalking me? Psychologists have said that the Baader-Meinhof phenomenon is responsible for this (Bellows 2006): the illusion in which a word, a name, or other thing that has recently come to one's attention suddenly seems to appear with improbable frequency shortly afterwards. This phenomenon is very similar to something called synchronicity : the experience of having a highly meaningful coincidence (Bellows 2006). That feeling that businesses are stalking you is actually the work of data mining. By the process of gathering information, they are able to make advertisements more relevant to individual consumers.

Advertising has multiple roles in that it is not only used to make customers aware of what they are offering, but also as a tool to build a strong image for brands to catch the attention of more customers (Zulfiqar, Shah). Advertising also influences consumer tastes and preferences and enhances differentiation of products. This causes consumers to become more loyal to specific brands, even to the point where they will choose that product even if a similar one is cheaper (Zulfiqar, Shah). You see this a lot in athletics, for example. While there are many brands out there for athletic wear (Nike, Adidas, Under Armor, Reebok, etc.), one dominates above the rest: Nike. They're also one of the most expensive. But if you start to pay attention to advertising in the athletic brand world, Nike also seems to dominate there, making their advertisements relatable (example: Want It All ad) to their audiences, therefore indirectly making them more appealing. Making advertisements relevant to the target audience[s] means bringing in more business for the company, so relevancy is very important in the advertising world. Data Mining and Relevancy So how do 'data mining' and 'relevancy' connect? According to Christen (2015), most current applications of data mining are still on the phenomenological level; in other words, they refer purely to behavioral data and their correlations with socio-demographic factors ??” for example, whether specific income-classes have a specific shopping behavior ??” and usually do not involve information on biological or psychological behavioral mechanisms (Christen 2015). Companies mine a cross section of personal data that includes almost everything that we post, share, or search for online (back to the creepy factor). They use this data to separate different types of people into groups that they then can target with specific advertisements and brand imagery.

Advantages and Disadvantages It is difficult to evaluate data-mining practices; code, algorithms, and methodologies are often proprietary and we do not always know how they work (Kennedy, Moss 2015). However, it simply takes common sense to see the advantages of data mining in advertising. A normal user sees hundreds of thousands of advertisements a day . If a company uses data mining to tailor their ads to reach more specific groups, they could increase their chances of business. Although the audience they're reaching may be slightly smaller due to data mining, they would be reaching people that their advertisements are more relevant to, therefore bringing in more customers. The 'creepy' factor comes back into the disadvantages again; while customers would more than likely appreciate advertisements that hold their interest, it could get to the point where it's just a little too personal. Target Advertising Target advertising is a concept to describe how companies use relevancy in their advertisements to reach the audience they are intending that particular advertisement for. Many people are aware of Internet trackers, but not of the extent that these trackers actually reach. Some users even believe that smartphone microphones pick up conversations and that's why we see ads for things we talk about. Many websites have denied this, but people still believe it. Google is the number one website that uses trackers to collect data and information; they have trackers on 76 percent of websites, while Facebook watches us on 23 percent of sites (Kwiatkowski).

Every year, advertising gets more and more invasive, and people get more and more wary of what's actually going on behind their social media profiles. Social media marketing should be understood as a direct two-way communication between brands and customers, and not as the passive consumption of advertisements (Maurer, Wiegmann 2010). Facebook has actually been criticized by experts who argue that social network sites for marketing purposes are useless because people use Facebook to stay in touch with friends and not as an information source (Maurer, Wiegmann 2010). In reality, however, more and more businesses are taking to Facebook for advertising purposes because Facebook happens to be the most populated social media site. An average user sees dozens of advertisements while scrolling through their Facebook feed, whether they're videos, photos, or posts by a business page that their friend has shared. Combining data mining, relevancy, and target advertising could change the marketing world in the future, making advertisements more relevant to specific groups. Conclusion People want advertisements that are relevant to them, and that contain things that they would actually be interested in. At the same time, however, the same people don't want the government, businesses, or even other people getting too much information from them.

There is a fine line between what is considered right and wrong when it comes to the mining of private information. But what is right, and what is wrong? Based on the research that I have done, and the information that I have gathered, I have come to a conclusion that there, in fact, is no right or wrong way to mine data. There is also no way to avoid crossing the line of ethics and morality, because there is no right or wrong answer. The majority of people will not agree on what is 'right', and they will argue about what is 'wrong'. That being said, it is possible for companies mining data to improve the ways that they gather that information. While they may not always be able to decide what information they receive , they can make decisions about what information they actually use . By taking the nature of their advertisement into consideration, and also considering the group of people that the particular advertisement is directed towards, companies can make moral decisions that will affect how their advertisement is perceived, and the amount of successful business that the advertisement brings them.

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