How do we apply professional marketing standards to the use of Big Data?
Big Data – Buyer Beware
Controversy broke out in the USA in 2012 when it became public knowledge of Target’s advanced analysis of their customers buying habits. They analysed Big Data among shoppers to help the company figure out how to exploit them (Duhigg, 2012). Target’s analysis of its customers’ buying habit revealed habits such as:
- When someone marries, he or she is more likely to start buying a new type of coffee
- When a couple move house, they’re inclined to purchase a different kind of cereal.
- When they divorce, increased chances are they’ll start buying different brands of beer.
What one person may call “Cool” another would call “Creepy”. It gets stranger – Target moved on to build a “pregnancy-prediction model”. Imagine the reaction when a Minneapolis father discovered that his teenage daughter was pregnant after he found out she had received coupons for baby clothes and cots from Target.
Big Data is a new weapon for marketers. While the good old days of data analysis examined past performance to understand sales, marketing, operations and finance, it has limited predictive abilities in terms of forecasting what customers will do next. On the other hand, Big Data can be used to predict not only what the customer will do next but why (Oracle, 2012). This is a game changer for marketers. Big Data draws on ‘live’ data sets from social network sites, software logs, cameras and other mobile devices. Data is collected and analysed computationally to reveal patterns, trends and associations relating to society and human behaviour. Big Data’s potential is huge, but marketers need to start questioning assumptions, values and biases of this new wave of information.
The major ethical dilemma for the modern marketer is how do we apply professional standards to the use of Big Data when consumers are unaware their information is being used for multiple uses, profits and other gains?
In 2006, a Harvard based project gathered information on student users of Facebook that was released into the public domain, and the privacy of the individuals was consequently compromised (Boyd & Crawford, 2011).
Facebook and other social networking sites are the test case for the ethical use and storage of Big Data. And users should be asking:
- Is the information I post actually publicly available?
- Do you need my consent to use my information?
- What are my rights to privacy and protection?
- How are users of Big Data (sociologists, political scientists, economists, mathematicians etc.) held accountable for their use of Big Data?
While Facebook and Target have arguably compromised the privacy of their customers for their drive for profit, modern marketers need to look beyond the dollars and consider the ethical responsibility that comes with the collection and use of Big Data. While the governance of Big Data lags behind its collection and application, marketers need guidelines to inform practice now. When looking to develop data strategies, marketers need answer some simple questions (Shandrow, 2014):
- If I don’t have time to get anything from my customers but their money, do I really need to collect data from them, too?
- What types of personal data should I collect and why?
- What types of transactional data should I collect and why?
- What are the best ways to collect customer data?
- How should I organize and store it?
- How can I best protect my customers’ personal and financial data?
- How can I be sure what I’m doing is legal?
- Should I sell my customer’s information to third-party marketers?
- What’s the best way to benefit from the customer data I collect?
- What are some common mistakes to avoid?
Legislation always lags behind technological change. The way in which organisations, and marketers, balance innovation and Big Data will be challenging. Rather than relying on personal value systems, conversations, even if they are uncomfortable, need to be held on policies on data privacy, customer identification and data ownership.
At the end of the day, there is a huge opportunity to develop brand loyalty around honesty and transparency in the use of Big Data.