Just about every move a person makes is collected as data. Paying with a rewards card, conducting online searches, and using social media are just a few of the ways in which data is collected about us everyday.
All of these sources feed what is called Big Data. According to Webopedia Big Data is “used to describe a massive volume of both structured and unstructured data that is so large that it’s difficult to process using traditional database and software techniques.”
What does this really mean and what is it used for?
Getting to know your customers better through data has many pay offs. Today we are going to focus on marketing and how this data is used to better target customers.
One of the most basic ways this data can be used is through customization. Once a team has enough data they can predict what messages or products a person will most likely respond to or buy. They use this to tailor the messages they send you, the ads you see and the products you are suggested. But according to Forrester it’s not just about encouraging behavior:
“It is equally essential to anticipate customer behavior and be prepared with the most appropriate offer to which the customer is most likely to respond.”
Probably one of the best companies at using data to fuel sales is Target. Back in 2002 Target started working on a way to use the data they had to predict if a women was pregnant. They knew that most shopping was habitual with little to no conscious thought and that these habits were hard to change. But lucky for Target and retailers everywhere there are times during a person’s life when these habits are most likely to change. Moving to college, getting a new job or getting married are a few. But being pregnant is the holy grail. This is the time when shopping habits are most up for grabs and Target wanted to know first. Through lots of analysis and pattern uncovering they found a way based on certain products bought if a women was pregnant and at what stage. They used this to send customers targeted coupons relevant to their stage of pregnancy before any other retailer. And so they reshaped the buying habits of countless women.
A couple less creepy examples include Orbitz and Hollywood. Orbitz realized that Mac users tend to spend more on hotels per night than PC users so they started experimenting with showing Mac users pricier options. At the time of the article they were still in their early stages but had already experienced some favorable results.
Hollywood on the other hand wants to know the formula for a blockbuster. Gone are the days of gut instincts and pure creative power. Now they can use their data analysis to predict what people will enjoy and about how much money it will make. This information can be used to guide investment and marketing funds. As the article says “predictive analytics will be considered just as important as the producer, director, and actor who make a film a blockbuster.”
But don’t get the impression that everyone is a wiz at data analysis. As the definition above stated this stuff is BIG and hard to work with. Starbucks for one isn’t prefect at it. The company collects tons of data from their loyalty cards but is not yet using this data to its full advantage. The company is still struggling to make sense of it all.
Target aside, the Obama campaign may be one of the better groups at harnessing the power of data. The group had a massive database that helped them raise $1 billion and target the right message to the right voter securing them the reelection. As a part of their efforts they gave voters persuadability scores. They enabled them to know who was worth targeting and how to do it. In swing states such a Ohio they collected even more information. They had enough data to go and and see which voters were changing sides after debates and polls. In terms of media buying they had the data to run their own analysis rather than rely on consultants. Based on their own data they raised ad efficiency by 14%.
Big data can be intimidating but once controlled it can be your most powerful weapon. The future of marketing lies in the data, making decisions without it is a thing of the past.