Prospecting flow. How to avoid the death valley?

Prospecting, Valley of death, sales process, call flow
You do not have to walk through the valley of death when prospecting or following up.

Photo credit: Pacheco

Have you seen this slide that regularly goes around on LinkedIn presenting the amount of time a sales person needs to follow-up with a prospect to get a deal and how many sales people stops too quickly.

Sales, process, statistics, follow-up
So called “incredible statistics”

You can’t have missed it. It comes back over and over again and is coming from the so-called  “National Sales Executive Association”? Well, if you didn’t know already: it is a fake. The NSEA simply doesn’t exist. But this slide seems to make the point there is value in chasing to secure a sale. Is there some sort of ground beyond this fact? Are sales people who do chase, don’t hear back, carry on crossing what I call “the valley of death” courageously (it’s very silent in the valley of death….), are they the most efficient sales people? Or is it a myth. I think it is a myth. So, here is the prospecting flow I follow to make sure a lead or a prospect is a real one or one worth qualifying out:

1- Warm-up: To avoid going completely cold, I research the person I am going to contact and do some “social”. Not everybody is on Twitter but, if a prospect is, I look at his/her Twitter’s timeline and tend to RT one or two. My name is then known. It’s not strictly speaking a step in the prospecting flow but I find it can add value.

2- First contact: For large, complex sales, the objective in a first prospecting contact is not to sell. It’s about finding the right person and assessing if there is a problem that is aligned with those addressed. It can be done on email or phone call, with the usual debate about mail vs phone. Mail has the benefit of volume and giving analytics (is email opened, is it forwarded, what content is consumed, etc…), voice has the benefit of being more personal (people buy from people). And in a prospecting context, rather than in an active selling context, it’s usually easier to have a lead email address than her/his direct line. In terms of content, here are the guidelines I stick to.

3- Second contact: A follow-up. People are busy. The first email might have hit at a wrong time. So many things could make the first one unnoticed. No point making assumptions. The objective of the second follow-up is to assess if the recipient received the mail and is happy to do the introduction or take the call. If the person is on Twitter, I also do a RT or two.

4- Third contact: The start of the take-away. The lead person has received two emails, I might even know they’ve been opened (and even read). But no responses so far. No need to make any assumption again. It could be some timing issue. So I start to suggest I will close the file as there seems to be no pain felt within the target organisation.

5- Fourth and last contact: Closing the file. That’s the last step of the prospecting flow when I state I close the file and won’t contact again. I stress again the problem addressed by the service / product and that, if the person didn’t come back to me, it must be because none of these problems do exist within his/her organisation.

In a prospecting context, I believe in going slightly broad but being transparent (always a lot of value in transparency). Therefore it’s better to contact more than one person (when possible) and I share the colleagues I am also contacting. If the call/meeting is with a qualified prospect, it’s also important to have a similar process. So with a qualified prospect that start to get quiet (the very silent “valley of death”), I follow a flow similar to the prospecting flow above. The main difference between prospecting and a qualified leads is that the problems faced in the prospect organisation should have been clearly established. So, rather than speculatively stating the problems addressed, the content of the mails / calls are centred on these problems (as mentioned here).

Oh, last but not least. When it comes to statistics such as those in the slide above, did you know that 68.5% of statistics are wrong? :)

 

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