How to Gather Smart (Not Big) Data
Everyone has heard a lot about big data. Whether it has been through articles, blogs or conferences, it's been almost ad nauseam. But there's really no such thing as big data. There's no such thing as small data or medium data either. There's just data. And you're either really good at using it or you're not.
I had an interesting thing happen to me not too long ago. I signed up for a popular deal-of-the-day website and provided all of the personal profile information requested. I was curious to see how it was going to use my info to market to me. I gave my age, gender and location. I also gave my interests--triathlons, running, skiing, and digital marketing. The following day, I received my personalized email offer--a discounted pole dancing class at a women-only studio. I was flattered, but uninterested and subsequently unsubscribed from the service. Here was a company that had mounds of data to leverage, but couldn't get it right.
The 5 Question Framework for Smart Data
We now have access to more data than ever before. The good news is that the data provides access to a wealth of insights. The bad news is that the insights are rarely waiting at the surface, so having the quantitative foundation to know how to use the data is key.
Everyone is looking for an edge, looking for a way to outshine their competitors. It comes down to asking the right questions and using data to provide the answers. If you can leverage data to answer those questions more effectively and faster than your competitors, you win. You have to look at what the data is telling you, which actually may lead you to more questions that will need answering.
When I ask people to give me the five most important questions they'd answer to improve their business or a marketing campaign they're working on, I am often surprised at the poor quality of questions I hear. It's not always easy coming up with the right questions.
If you're not sure where to start, use the 5 question framework that I apply when working with clients.
- What are your goals?
- What is your budget?
- How are you performing against both?
- What are you going to do about it?
Imagine you asked the above questions and the answers led you to another question, which for the sake of this example is, "What is my cost per new customer?" Initially, this may seem like a straightforward question.
The first step would be taking your marketing dollars invested, which you probably have a clear idea of, and divide it by your total new customers. However, in order to get to your total new customers, you need to first identify whom that includes and excludes: Is it someone who has never made a purchase? Or is it someone who might have previously made a purchase, but hasn’t purchased within the past five years? Who are my existing customers? What are my total transactions both offline and online?
In order to answer these additional questions, you'll need to dive into a myriad of different data sources. And in order to navigate, explore and maintain all of this data, you need to invest in an infrastructure that will provide you the technology and resources to most effectively utilize the data.
It's not until I can answer the additional questions that I can get to my total new customers and filter that back into the denominator of my initial equation, marketing dollars invested divided by total new customers. As the example illustrates, it may not always be as easy as it appears to answer business questions.
Every day you need to be asking yourself what you can do differently relative to your competition. If you can gather smart data, rather than big data, and make it actionable, you will beat your competition. I'm not saying that managing data is easy--it's difficult. But difficult is good. If something is difficult for you, then it’s difficult for your competitors, and there's a big chance they won’t make those investments. Ultimately, if you're able to take advantage of the data, you're going to increase relevancy for your customers and outrun your competition.