Data mining is a huge buzz word in today’s digital world.  Love it or hate it, the ability to mine data has truly changed many industries for the better—but at what cost?  The question many experts and consumers are asking is—how far is too far when it comes to our privacy?  Is it ethical or legal to buy and sell the personal and private details of a consumer’s digital footprint, lifestyle, etc?  These are questions corporations and lawmakers face on a daily basis.  But data mining isn’t going anywhere, and artificial intelligence continues to refine itself.  So where did data mining begin, and where is it going?

Data mining is the process by which computers analyze large sets of data and use them to predict behaviors and future trends.  Companies use models, such as a set of examples or mathematical relationships applied to different situations, to make these predictions.  Through data mining, businesses can retain information about consumer behavior that could only otherwise be discovered and studied in focus groups, case studies, or other more time-consuming and expensive methods.  It is efficient and accurate, giving corporations and industries access to information they never had before.  Today’s data mining technology is highly advanced, but it wasn’t always as such. 

Data mining has evolved every decade since the 1960s, starting with its conception of data collection.  Data collection is self-explanatory, but it was initially enabled by computers, tapes, and disks, allowing businesses to retain information about simple concepts such as revenue totals or sales history.  The 1980s saw the birth of data access, which enabled industries to collect more minute details about their day-to-day business dealings.  This data could be stored and reviewed at another time through relational databases, which were also capable of establishing connections between data points.  This led to the invention of data warehousing which reports and analyzes data.  Data warehouses store current and historical data from multiple sources in one place and are used for creating analytical reports.  Data mining was developed from all of these technological advances. 

There are many specific uses of data mining for marketers.  One is market segmentation, which groups consumers into segments based on common characteristics, allowing companies to target them in advertising campaigns.  Similarly, direct marketing uses data mining to identify customers that will have the highest response rate probability to direct mail.  Another is “customer churn” which predicts and identifies customers who are most likely to leave the brand for a competitor.  For security purposes, data mining can be used as fraud protection to identify fraudulent transactions.  Interactive marketing and market basket analysis predict individuals’ interests, future purchases, and products they are likely to buy together.  Finally, trend analysis reveals the differences between typical customers from month-to-month.  In general, marketers use data mining to predict consumer trends and behaviors and discover unknown patterns between consumers and transactions. 

So how do companies access this data?  Is there some sort of data black market where corporations put consumers’ profiles into a basket and check out? A data Amazon?  Thankfully, for consumers like you and I, there is an entire professional (and not sketchy) industry focused on data mining.  The professionals who work in this industry, buying and selling data, are called data brokers.  Data brokers collect information from public records, online activity, and purchase history (to name a few) and then sell it to businesses who use it to influence marketing decisions.  Some of the largest data brokerage companies store data for more than 500 million consumers all across the world.  Data brokers also purchase data from specific companies who sell information, such as lists of consumers who belong to loyalty programs.  This purchased data is then sold to other companies who may use it to make decisions about their own loyalty programs.  The options, like the data, are endless.  Unless a consumer is living entirely off the grid it is safe to assume a company owns their data.  Luckily, some companies offer consumers opt-out options which prevent their personal data from being sold or rented. 

Although the opt-out option leaves consumers with some control over their data, legislators across the United States are fighting for more consumer privacy rights.  Recently in the news, Facebook made headlines after it was revealed that hackers sold the online identities of 267 million Facebook users for the price of $540.  The data was comprised of users’ email addresses, names, Facebook IDs, dates of birth, and phone numbers.  Although no passwords were stolen, users could easily fall victim to phishing and accidentally give away more serious private information.  Data breaches and insider trading like this happens every day, and law makers are using these examples to lobby for their constituents.

With new technology, data mining has come a long way since the early days of data collection.  As artificial intelligence becomes more prominent across all industries, data mining will continue to grow as a powerful tool for marketers and businesses alike.  Although it comes at a price to consumer privacy, new legislation offers protection and a nice compromise between personal security and business efficiency.  It will be interesting to see how this balance plays out between public and private interests.  For more information on data mining and other direct marketing techniques, order Corporate Communications Group’s Direct Mail Marketers Guide. 

By Marley Niesz