Let’s break it down into three simple steps.
1. Find out what’s in
there.
The first step is to understand the field headings in your
database. Most databases have basic information like name, address and purchase
history. Are you also capturing information such as age, gender and home
ownership? What data do you actually have?
2. Ask questions.
Knowing what data you have tells you the types of queries you can
run. Running queries simply means asking questions of the data. If you are a
retailer you might ask, “Which customers purchased hardwood flooring last
month?” If you know that these customers are also likely to purchase area rugs
and floor conditioning products, this gives you a great start.
3. Look for
relationships.
The next step is to run data sorts. Is there a relationship
between hardwood flooring and gender? How about income? Are customers more
likely to purchase hardwood flooring at different times of year than others?
Even basic software like Microsoft Excel or Microsoft Access
provides sorting capabilities. Or you might want to purchase add-on data mining
modules or third-party software. If you need to outsource, there are plenty of
companies that specialize in this process for very reasonable costs.
Get Curious!
So get curious. Take a few hours to run a variety of sorts just to
see what you can find.
Once you know what’s in your data, you’ve asked questions of your
data, and discovered relationships within the data, it’s time to act on what
you find. That curiosity could make a big difference to the bottom line.
Jeff Lampert
Director of Marketing & Business Development
We keep moving forward, opening new doors and doing new things because we're curious and curiosity keeps leading us down new paths.
Walt Disney
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