By Adam Fraser.
There has been lots of discussion about Big Data in recent months. Everyone seems to be talking about it, including marketers.
If you want to get technical and big data geeky, the definition of big data is:
Data that is difficult to collect, store or process within the conventional systems of statistical organizations. Either, their volume, velocity, structure or variety requires the adoption of new statistical software processing techniques and/or IT infrastructure to enable cost-effective insights to be made.
So how big is the data in our universe at present? Here are a few sample facts to give you a general sense:
- As far back as August 2010, Google’s Eric Schmidt stated that we now create more data every 2 days than we did from the beginning of time to 2003
- Estimates re the Internet of Things show there will be 50 billion interconnected devices within the next 5-10 years (all transmitting data)
- 100 hours of video are uploaded to YouTube every minute and 6 billion hours of video are watched every month
- Facebookhas 1.35bn monthly active users, storing more than 300 petabytes of data from its users
- Approximately 200 billion tweets per year are sent on Twitter
By the time you read this no doubt all these numbers will have increased again and there are many more mindblowing stats on how much data we now create. Case closed – the pool of data to analyse out there is ‘big’.
Marketers are chomping at the bit to discuss the multiple possible use cases for this vast data pool. Yet we still live in a world where Facebook itself cant judge the sentiment of photos uploaded by its users. I still regularly get newsletters from brands that don’t seem to know or acknowledge my actual status as a customer. When I call financial institutions it’s clear multiple customer databases don’t talk to each other – old phone numbers, old addresses etc on different departments’ systems.
Examples are all too common of brands not delivering the right message at the right time. Not doing the basics analytics well. Not joining the dots from disparate pieces of customer information. If the foundations aren’t there, attempts to jump into more complex big data analytics are unlikely to be immediately effective.
There is no question that big data analytics can produce significant benefits and insights for organisations following the correct business processes and asking the right questions. But marketers may want to focus on effectively using the “small data” they have first, before super-sizing to the larger unstructured pools.