Why Is It Crucial to Have Accurate Prospect Data

By Chris Zawisza

prospect data

There has never been a time in history when sales and marketing were so data-driven. While in the past salesmen used to show off their Rolodex as a visual representation of the relationships they had built, sales teams are now looking outside their own networks to get the best prospect data. Of course, not all prospect data is good. In a recent Demand Metric study, it was reported that only 40% of B2B organizations have highly accurate data. Therefore, there are two different kinds of sales teams.

The first kind of sales team puts a great deal of time and effort into the gathering, researching, and correcting of their prospect data. The second kind treats data as an afterthought. They tend to work with outdated or incomplete prospect data. I don’t have to tell you that the first kind of sales team will outperform the second kind in almost every situation, purely because of their data policies.

You wouldn’t be an effective salesperson if you didn’t want to outperform your competition so the issue of data is probably leaving you with a couple of big questions:

Why is it so crucial to have accurate prospect data and what aspects of your sales process will it affect?

In sales, you need to be able to identify your potential buyers with accuracy so that you will be able to contact them in an efficient way. For that reason, accurate prospect data is essential to getting the best results from your outbound campaign. Unfortunately, not all data providers are created equal. Some less scrupulous actors will sell prospect data that is 6 months old, a year old, or even older. So why is that a problem?

Think about your office. Even in those that have low turnovers, you will still see a number of people coming in and out of the company over the year. And of course, high turnover offices will see waves of people regularly changing their jobs. According to the Bureau of Labor Statistics, the average American will have 12 jobs throughout their career with most working at the same place for less than 5 years.

What these statistics mean is that your average company will potentially have a much different lineup each year. Because of these circumstances, older data is usually at best 70% accurate. There are a few ways in which you will run into problems if 30% of your prospect data is bad.

The most immediate and obvious implication of poor data is that you are not getting 100% of the prospect data that you paid for. Imagine you bought a sandwich at a deli and when it was handed to you, you found that somebody had bitten off a third of your sandwich. While the thought of that would put off most sandwich buyers, the other implications of bad prospect data would put off any sales person.