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.
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.
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.