Sales Prospecting — namely Aaron Ross’ Predictable Revenue approach — seems to be back in vogue these days. This makes me happy because I’m a big fan of the strategy.
In my experience, these programs live and die based on the quality of your data and how you organize it into a process — particularly your prospect data. Sales prospecting is definitely a garbage-in, garbage-out type thing. If you don’t have a decent list, then you almost certainly won’t get the results you want.
For example, I’ve heard plenty of stories about people dumping a list of contacts from a resource like Data.com or Hoovers.com and getting absolutely nowhere because none of the data is accurate. The email addresses don’t work, the prospects have moved on to other jobs, etc.
Instead, I recommend doing the work to identify each prospect one at a time. It is slow, tedious work — but totally worth it. By investing in up-front research, you effectively pre-qualify your prospects such that you know your effort to contact them is worthwhile and that the performance data from the program is reliable in that it is not overly skewed with incomplete or inaccurate data.
Moreover, a well-developed prospect list is an evergreen asset. You’re effectively building a database of your entire target market (or at least strategic segments of your target market) that you can revisit over and over with marketing offers. Direct prospecting not working? Try inviting prospects to a webcast. You get the idea…
If you’re really, really good — you can significantly improve the quality of your prospecting efforts by collecting social graph data related to your prospects. By mapping prospect relationships early in the sales process, you can uncover referral opportunities and warm conversation starters.
For example, you might think about starting your data collection efforts by working through your existing customers’ LinkedIn profiles and then asking for an introduction. You’ll have a much better chance at getting Joe’s attention if you can mention your shared connection with Jane.
I’ve used a few methods / processes to collect prospect data (name, company, title, email address, phone) in the past. I’ll share a few in another post soon.