Gathering Leads and Qualifying Your Database
Is Not as Hard as You Think
We all know that successful 1:1 print marketing requires good data, but it’s not just having data that determines success. It’s what you do with that data once you have it.
Success starts with gathering data that will have the greatest impact on your campaign. That means data mining. While the phrase “data mining” strikes fear into the hearts of many marketers, it doesn’t have to. Nor does it have to be expensive or scary. In this article, we’ll take a look at the basics of data mining and create a hypothetical scenario for an effective 1:1 campaign.
Another theme in this article is that success is dependent not just on what happens during the campaign, but after the campaign, as well. Marketers must be willing to sit down and take a hard look at the results and work the lessons back into the next program.
In this article, we’ll look at seven different yardsticks from which you can choose to evaluate success. Remember, good data just gets you off the starting blocks. It’s what you do once you are in the air that matters.
In order to produce a successful 1:1 printing campaign, all you have to have is a great database, right? Not quite. Producing a successful 1:1 print campaign starts with having a great database, but even once you have the data, you have to figure out what to do with it. Often, that means data mining.
Data mining. The very phrase strikes fear into the hearts of marketers. The ability to connect the dots to reveal buying habits and other customer behaviors is something many people see as complex, expensive and within the reach of only the largest companies. In reality, data mining is well within the grasp of any sized marketer.
There are three steps to data mining:
• Know what data is available.
• Ask questions about that data.
• Look for useful relationships.
The first step is simply to understand the field headings in your database. What data are you capturing?
Most databases have basic information like name, address and purchase history. Are you also capturing information such as age, gender and home ownership? If so, this tells you the types of queries you can run.
Running queries sounds complicated, but it 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. You might then want to refine your search, sorting by age, income or gender. This allows you to cross-sell products more appropriately.
Look at Everything
The great thing about data mining is that sorting is free. Run every sort you can think of. Is there a relationship between hardwood flooring and gender? How about income? Look at everything. You might find that data you once thought irrelevant, such as the date of purchase, has more relevance than you think. During one data mining exercise, for example, one retailer discovered that its sales of sporting good products spiked on the third Saturday of the month. Can you guess what it did? It created a 1:1 personalized campaign offering staggered incentives based on spending level for purchases— you guessed it—made on the third weekend of each month. Revenues soared.
Make the Most of What You Have
Every business has a database program, so make the most of it. Even basic software like Microsoft Excel or Microsoft Access provides some data mining capabilities. Or you might want to purchase add-on data mining modules or third-party software. If you have customer information in multiple databases, you might also want to combine them into a single, comprehensive database for use in marketing. Even if you don’t, you can often extract useful information from even one or two databases. Don’t overlook outsourcing. Graphic Center, Inc. specializes in this process. Costs can be very reasonable. So get curious. Take a few hours to run a variety of sorts just to see what you can find. That curiosity could make a big difference to the bottom line.
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