Have you heard the term big data before? Many of us don’t really know what it means, or we have a vague understanding of it. Big data, by definition, is the collection of large amounts of data that can be analyzed to uncover trends, patterns, or associations. A vital characteristic of this type of data is the very high volume that is collected, which can produce terabytes or even petabytes of data. To some of us, those sound like mythical measurements, but in fact, some organizations gather tons of data on their customers and keep it on servers. The variation in the data collected is also a characteristic of big data; it could be structured or unstructured data.
How It’s Used
The truth is that we encounter big data everywhere and might not even realize it. Are you a loyal member of an airline frequent flyers club? Imagine that you are; every time you attach your membership number to your flight reservations, the airline tracks the transactions you have with them. Did you upgrade your seat or buy inflight entertainment? If you did that, transactional data is used to send you future offers on the same services. Company’s like airlines then use the information they’ve collected on millions of their customers to make business decisions or sales forecasts. For instance, they can determine when and where each loyalty member travels most often and push off-season fare promotions, or they can figure out if most customers pay for seat assignments and increase the service fee.
Big data can be collected from social media, online website engagement, and transactional data, and there are numerous benefits to using it. But smaller companies are less likely to gather big data because they have less volume and velocity of it collected. But that doesn’t mean you can’t apply the best practices of big data and use the information you’ve collected to personalize customer experiences by following their behavior and stages in the customer journey.
For more information on the difference between data points and insights, take a look at my previous blog post here.