Big data is the term marketers are using for the next logical step in reaching customers who are most likely to buy. Driven by big sites, such as Google, Facebook and Amazon, marketers know there is gold in those petabytes of purchase and search data. Mining that data effectively is a task that has everyone looking for a better mousetrap.
A recent article on big data in the Wall Street Journal offered insight into the challenge. In the 1980s, Wal-Mart had the biggest commercial data warehouse in the world with a whopping 180 terabytes. Today, Facebook’s user content makes up more than 100 petabytes of stored photos and video. Analyzing that data generates about 500 terabytes of new information per day.
Linking obvious purchase data is the low hanging fruit. If you have bought a dog and an eating bowl for your dog, you will most likely need a leash, a dog brush and a flea collar. Linking your purchase with your social media behavior is the hard part. With that information, marketers hope that they can perhaps send you a flea collar for free, then encourage you to brag to your social media friends that your flea collar is the best ever.
We’ve been assembling big data in the relatively small niche of the $600 billion foodservice industry since 2006. Because we have handled coupon redemption data on foodservice operators for a variety of manufacturers, we’ve entered a variety of data on them. For example, we have captured their essential data (name, address, e-mail), but we have also captured what they purchased, in what quantities and the name of distributor who sold it to them. In this way, we can support a food manufacturer’s push in cooperation with a distributor, or encourage an additional purchase (e.g. we saw that you purchased spaghetti sauce – how about some pasta?).
Understanding the data that you have and being able to slice it for clients requires a deep understanding of the markets where you play and some level in sophistication in outbound and inbound marketing. We will have more in a later post on how you do just that.