While most of marketers and marketing companies are walking into the Big Data era, the most important thing we need to keep in mind is that data is just a mess of numbers until it is being processed, and analyzed. We need mathematicians who understand data to create models, technicians who understand analytical tools to proceed with coding, and insightful communicators to draw insights and conclusions from mathematical terms.
Big Data and appropriate marketing analytics not only can provide cost efficient consumer data for finance department to understand transactions, but also can help marketing department to understand consumers and their behaviors, which in turn, will provide personalized services to our customers. Retargeting, as one of the most often suggested methods to lead customers back to site for a call to action, has used supports from big data and marketing analytics.
Big data is becoming a monitor that can trace most of activities for most people who has internet connections. With appropriate use, it can provide very insightful information on a customer includes behaviors, subconscious activities and interests. Some are even unknown by the customers themselves. This is also why so many marketing departments are trying to buy customer information from third company or utilize analytic tools to obtain insights from its internal database. Comparing to traditional marketing methods, Big data has made nowadays marketing more of Science than Arts.
Big data is easy to obtain and are available through a wide variety of sources, such as social media, purchase transactions and internet activity. However, the challenges are not obtaining the data, but are processing the data and generating useful information.
We should also keep in mind the three big Vs while analyzing the data:
- Volume: Amount of data being processed; whether it is enough to draw significance.
- Velocity: The flow of data being processed; the speed which data are generated.
- Variety: platforms and types of data being processed; whether they are representable in diversity.
At the same time, we need to make sure that the data are coming from trusted sources, so that they can provide representable and trusted conclusions.
Again, Big Data is the useful cloud above us that can monitor our behaviors and activities, but it is not the brains inside us. Marketers can use Big Data to monitor and observe activities among consumers, but through only big data, we won’t be able to know what is driving those activities.
“People don’t want a drill, they want a whole”. This statement by professor Theodore Levitt tells us: Through big data, we will be able to know that consumers want a drill, but still, big data can’t tell us that they want a whole.
Therefore, Big Data is extremely useful in helping us marketers to scientifically draw conclusions, but Big Data itself is not the conclusion. Marketers, we have to think.