customer support

They say “a bird in hand is worth 2 in the bush”. I say, “how can you be so sure?”

The bird in hand represents a paying customer – that does seem pretty good. However, how much is that customer paying? Is it higher than your customer average? More importantly, what pipeline stage is “in the bush” and what is the probability of closing at that stage? All these questions help you boil things down to expected value or expected revenue. Let’s walk through the calculations starting with the following assumptions:customer support

  • Average customer value is $1,000
  • Recent closed opportunity value is $750
  • Probability of closing “in the bush” pipeline stage is 75%.

Okay, so the expected value of the two birds in the bush is $1,500 while the value of the bird in hand is $750. There are a bunch of assumptions and oversimplifications here but my point is that an existing customer is not always worth more than your next two prospective customers. Really, you’d have to look at the expected cost associated with keeping that customer or fulfilling his/her needs.

The real question I have regarding this proverb is, “why do you have to choose between a current customer and two potential customers?” Let’s ask that question this way: what happens when you have a client sitting in your waiting room for an appointment and then the phone rings? If you have to choose between the two, which will it be? The more relevant and overlooked question is, “where should I spend more of my limited company resources: keeping clients that I have or trying to acquire new clients?” Put another way, is the ROI of trying to keep this existing client greater than the ROI from trying to win new business? When your resources are scarce, this is a very important question and one many companies aren’t asking.

If you assume “a bird in hand is worth two in the bush” then you are probably making similar assumptions when it comes to managing your pipeline or even organizing your business. It’s never too late to start questioning those assumptions and collecting the data to prove them.

By Rich

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