Sales Math and Measuring What Matters

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| Peter Radizeski of RAD-INFO, Inc. talking telecom, Cloud, VoIP, CLEC, and The Channel.

Sales Math and Measuring What Matters

Sales Math is the concept that you need X number of leads to make Y number of sales where Y is a tiny percentage of X. The funnel starts out with a big number and the inked deals drip out of the bottom -- with a bunch of leads lost along the way (like a leaky hose).

We all believe in Sales Math. We are delighted to be asked to quote something. Why? Pavlov response I guess - plus you can't win if you don't play. But that runs smack dab into the fact that there are finite number of hours to get sales. (Sales is just Time Management).

Salespeople will not say NO. That is the problem. Even when the sale is small or not a good fit. We want it anyway because we want to book revenue - any revenue. We want to close a sale and get paid. Even a bad sale. Or one that will require way more time than it is worth.

Does that say we don't value our time? Maybe.

What if we are not measuring what matters? What if we are measuring the number of leads or the number of deals or even booked revenue but it is the wrong metric? Seth Godin writes, "It's not always easy to measure what matters. Sometimes, the thing that matters doesn't make it easy for you to measure it. The easiest path is to find a stand-in for what you care about and measure that instead."

What if the stand in - the number of leads or the number of contracts or the total revenue -- are the wrong indicator? If you are looking to raise net income, none of those will be a barometer to margin.

If you worry about cleaner installs, then wouldn't a focus on lit buildings be indicated?

If you want more engaged partners, then quoting everything just to be responsive and be quoting isn't the answer either.

Is a good channel program a reflection of how many sign up or on how many sell (high margin, high ARPU deals) every month?

Today, Big Data means we have more than enough data available - too much data - that can be analyzed to target better. Why don't we?

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