With March Madness in full swing and spring beginning, myriad marketers find themselves amped to kick their demand campaigns into high gear. If that sounds like you, cast your bracket aside and take the guessing mentality (as "informed" as you think it may be) off the table. Instead, channel your inner Nate Silver by using data as the basis for your marketing success.

Data-driven marketing is the prevailing force in B2B—but with marketers ingesting more and more data from various resources, keeping data organized (and interpretable) can be overwhelming. I think we'd all agree that our leading scorer is the marketing database that drives our lead generation, nurturing, and engagement programs. But as we rush to employ new data sources, technologies, and channels of communication, the management of that database often gets overlooked.

At the same time, that database is more dynamic than ever. New input from diverse channels (all with varying degrees of data elements and stages of completion) arrive every second. Data is taken from your online forms, the latest tradeshow list, content syndication partner... the list goes on.

The reality is that managing this data is not just a marketing issue. Managing data is a company issue. If you are not on target with who you are reaching out to and uninformed about the context of the conversation, you're wasting your time, your sales team's time, and (most importantly) the prospect's time. They won't buy from you—or if they do, it might not be a profitable sale.

So, how do you avoid the traps set by a havoc defense and advance to the next round?

According to an Aberdeen Group report (email registration required), companies with best-in-class marketing data management practices require 64 responses to acquire a customer compared to the industry average of 349. Take your blended average CPL and try it at both of those multipliers for a fun exercise in quantifying the results. It’s a remarkable improvement and proves your marketing programs just need to be fueled with better data.

Here are some steps for getting started.

Evaluate the state of your data

Doing so allows you to gain insight into where gaps and opportunities exist for improving your data. Does your data match your target profiles? Are you missing information? Is what you have accurate? Find your pain points.