But did you know in two days’ time we see data equivalent to the span of time from our beginnings to 2003?
So you finally finished collecting all your data and you have, if not terabytes, petabytes. Now what? The answers to your questions, like “What are my consumers saying about our retail stores?” or “Am I going to get sick if I take public transportation on a Monday?” is there. All the answers are there, but how do you ask the right questions to get the answers you want.
Here’s where analytics comes into play. Analytics solutions help companies capture massive amounts of disparate data and then quickly convert it into powerful intelligence. Intelligence that can answer your business questions and give you a better idea about, about well anything your data could say.
So how do you get started with these two powerful technologies? You need to ask three crucial questions.
What’s my baseline?
Like most things in life, you need to get a baseline, to find out how you’re doing. How can you do this? Take a look at your company KPI’s for your department and business overall. Spend time learning and understanding them. What do you need to succeed?
What pushes my business?
After identifying and understanding your KPI’s, you need to understand how you get to that KPI. How does your business succeed? What are the factors involved? Is it people, or visits, or games purchased?
Do I know my customers and their needs?
Your data’s greatest potential can be in unlocking the secrets to your customer. But until you start utilizing big data and analytics, you need to create a basic framework on who these people are. You need to understand how they use your product, why they buy it, what marketing messages they respond positively too, and so forth.
By taking the time to understand these three things, your baseline, your business, and your customer, you will be equipped to utilize big data and analytics to dig deeper and ask even more right questions. Make sure your employees, no matter their level and regardless of their department, understand that they need to ask the data the right questions. Make sure they’re trained, if they’re not – well that’s a whole other post.Comments