How to sort the wheat from the chaff.

When I was growing up, my choices of TV channels were limited. I had the small variety of cobbled together commercial choices offered by CBN8/CWN6 (in what is still the most complicated name for a TV channel in the history of TV) and the cricket on ABC (complete with graphics that would have embarrassed a Space Invaders programmer). That was it. Fast forward to today and we have 22 free to air digital channels in addition to hundreds of Pay TV channels which all pale into insignificance with the almost limitless number of channels available with On-Demand services. Now, despite my wife’s complaints that I sometimes try and watch several channels at once (I hate watching ads) the reality is that you can only watch one channel at a time. With limitless choices, we are still only able to sit back and absorb or enjoy one channel at a time.

And therein lies a challenge we all face with big data. We now have access to an incredible amount of information. In the same way as we have way too many channels to watch, the question has often been posed if we have too much data. Well therein lies the secret of how to handle ‘Big Data’. Every day the world is creating an additional 2.5 quintillion bytes of data. Most of that data is useless to me. Some of it is priceless. How do I sort the wheat from the chaff? How can I harness all that data to help my business and, specifically, to improve my marketing?

The real point here is that mining our own data is where we can gain the best value. Data mining can sound like an incredibly complicated thing but take the example of Troy Adams from Betta Computer Services. Troy collects very specific information about clients to show they care. How large is the business? What is the birthday of the owner? What football team do they follow? Most importantly, Troy engages all of his staff to help with the process. In casual conversations with clients, his engineers might find out some specific information and then use that data to personalise their offering.

And ultimately, that is what ‘Big Data’ is all about. Personalising the offering to make the client feel as if an offer is targeted just at them. Echoing Troy’s comments, I always have on file what type of coffee a client drinks. Then when I turn up to a consultancy meeting, I have a coffee in hand that I know the client prefers. As far as the client is concerned, I simply remembered his preference (if I do it right). The database backing me up should appear seamless.

In a similar vein, Hendrik Kruizinga from Crucial Cloud Hosting focuses his data collection around existing clients and using that data in a way that enhances their experience with them. They focus more on profiling and client feedback rather than mining large data blocks.

Netsurit’s Neil Smith looks at the big data phenomenon differently. Neil sees it as a perfect way to grow their business. By using social Media (specifically Facebook and LinkedIn) Neil can gain background information on organisations and find key decision makers. The real key here is to work out methods to determine attributes of potential clients – such as appetite for risk, IT maturity and the like rather than just the pure traditional demographics.

As Jamie Warner from eNerds puts it, it is one thing to mine the data. Then you need to use it effectively. The key here is to develop specific marketing campaigns to match up to identified opportunities. In Jamie’s example this can be as simple as partnering with a key vendor to market hardware solutions to clients with hardware that is over three years of age or targeting clients with older versions of Windows Server to help guide those clients through the process of upgrading or designing an entirely new solution – quite possibly incorporating the cloud.

Just the term ‘big data’ implies, well, BIG! But don’t be fooled. Some resellers have told me that they don’t really deal with ‘big data’ because their focus is on small businesses. ‘Big data’ is not about big business. All resellers need to focus on maximising the data available to them to ensure their customers feel special. The number one reason a clients will leave your business is perceived indifference and if you aren’t mining all the data available to make your clients feel special, I can guarantee there is someone else out there who will.

Let me know what special ways you mine your data at

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