Data isn’t perfect. Neither is your prospecting.

By Will Rotondi

For those who have tried email prospecting and walked away disappointed, it was often because they treated it like they would sales: in other words, like a numbers game. I should send x number of emails and get y number of responses, they might say. So might you. When that doesn’t happen, or the responses aren’t to their expectations, they lose faith.

It’s not just math that will get in your way. It can also be your data.

If there’s anything we’ve learned about prospecting, it’s that:

  1. Getting data isn’t hard. Getting accurate data is.

Whether we’re talking about Millennials and their propensity to job-hop, or the fact that certain industries already have a high degree of turnover, there’s no way to guarantee that the data you purchase still accurately reflects who’s working at a particular company. (Not to mention that companies also re-brand, merge, declare bankruptcy, or go through any number of internal changes, regardless of whether they keep their own staff.)

That’s not to say that all data is inaccurate – simply to temper your disappointment when you see that most is. Instead, use it as a guidepost for the industries you want to target – and, where possible, don’t purchase email addresses with that data. Find and verify those later.

  1. Sales math and prospecting math are two different things.

Sales success is measured in deals closed. Prospecting success is measured in conversations generated. But not all conversations will lead to deals, and that’s where sales reps get frustrated – especially when they try to pre-vet a prospect before they’ve even gotten them on the phone.


It takes just as much time, if not longer, to get a prospect to convert to a lead in your normal sales cycle. Give them time to learn about you just as you’re learning about them (whether they’re a fit or not, or ready to buy from you or not), so that when the time is right, you’re who they choose.

more insights