Data Mining: Big Brother or Better Business?

This post was originally published on the UCD Michael Smurfit Digital Marketing Strategy Blog

Edward Snowden famously said, “I don’t want to live in a world where everything that I say, everything I do, everyone I talk to, every expression of creativity or love or friendship is recorded.” The topic of privacy has never been more closely discussed or followed in the age of digital prowess and social media. Internet users are becoming increasingly cautious of the type of information they share online because they feel like they are constantly being followed. This can be attributed to a concept called data mining — explained by Investopedia as the process of “using software to look for patterns in large batches of data” so that businesses can learn about their customers and target them more specifically via online advertisements to increase sales.

The Role of Data Mining in Marketing 2.0

The process of data mining, as explained by Alice Marwick, starts with the placement of a digital cookie, or a small text file, on a user’s computer when visiting a website. Third-Party Cookies track all online activities, including what websites users visit and in what order. This data is then used to track personal preferences and to deliver targeted content advertising, in order to convert casual browsers to customers. Bernard Marr discusses how data mining is already causing massive change in the marketing industry. Last year a poll by market research firm GfK found that 62% of marketers said it had already “fundamentally changed their role” and 86% said they would continue to use data mining in the future. Companies collect two types of data:

1) Structured Data — Users’ age, gender, location and purchase history. This accounts for 20% of the data shared online.

2) Unstructured Data — Users’ Facebook posts, tweets, pins, tags, likes and shares. Majority of the data mined by companies for advertising falls in this category.

The benefits of data mining for companies is huge. As Marr discussed, they range from Netflix being able to target viewers with suggestions based on the type of movies they watch, to retailers using their CCTV footage to determine consumer behaviour based on algorithms. Businesses are also working to anticipate their consumers’ needs before they have even been acknowledged by themselves, for example Amazon’s foray into “anticipatory shipping”. This involves predicting what products their customers will buy based on their purchase history and delivering it to them before they even place the order. This means that companies will need to collect a lot more data about their customers to strategically grow their own business and channel in sponsored content.

The Consumer’s Love-Hate Relationship with Data Mining

Considering the type and extent of online data that companies collect, it’s not shocking that consumers feel that their privacy is being invaded. The backlash is further fuelled by the fact that social networking sites don’t clearly divulge the amount of users’ personal data that they provide to their biggest competitors. Internet rights groups argue that the average internet user is not adequately educated of the potential dangers of sharing information on social media, including fraud and identity theft. Wisniewski and team examined the topic of whether our social norms around privacy are evolving naturally, or if instead they are being shaped by the messages we receive from social networking sites telling us how we should view privacy. “Does emphasizing sharing and de-emphasizing the risks in doing so cause us to make different choices? This issue is an important ethical one. All marketing is intended to persuade, but most often involves the exchange of tangible items — money for goods — and not the disclosure of personal information, which can have extensive implications users don’t always recognize.”

Optimistically, it has been revealed in a study conducted by consulting and IT giant Infosys that consumers will share personal information to get better services in the retail industry, but 75% of those interviewed felt that most marketers miss the mark when it comes to targeting consumers with the right ads. While 78% of consumers said that they were more likely to purchase from a retailer who targeted them with the right ads, only 16% were willing to share their social media information for this purpose.

Bridging the Gap and Creating Trust

The onus rests on companies who conduct their businesses online to ensure that users don’t turn against them, but at the same time work to gain their trust and increase the percentage of people willing to share their information online. Data mining presents a tricky issue. If done correctly, it can be used by companies to increase sales by conducting more targeted advertising campaigns, and consumers can benefit as well because ads are more tailored to their liking. But if companies and advertisers are not cautious and sensitive to the data they collect, there could be an increase in government legislation around the laws of data mining to protect public interest. Developing and using the right metrics to target consumers, and educating them on the benefits of data mining, can be highly effective in strengthening relationships between businesses and their patrons. Transparency remains the key to gaining consumers’ trust.