Predictable Revenue, a concept popularized by Aaron Ross in the first edition of Predictable Revenue (2011), is important. It’s important to us, perhaps to forecast commission earnings and when we might buy that new car or go on the big vacation.
Win/loss analysis should be a critical tool for improving sales force effectiveness, yet many organizations only analyze some of their wins and losses, and the focus is often more on the losses than the wins.
Sales forecasting is hard. For proof, you need look no further than the 2018 CSO Insights Sales Performance study, which reported that on average a little over 46% of all forecasted sales deals actually resulted in a win (never mind the timing).
If we’re driven by data and interested in statistics, there are a wide range of sales metrics we can choose to monitor. Assuming that we have collected the data in the first place, we can measure win rates, sales cycle velocity, changes in deal value or close date and all manner of other indicators.
Sales analytics are supposed to make everything about your sales system more effective. Companies that market sales analytics technologies love to tout its benefits, from providing greater “insights” to promoting “optimization” of the pipeline.
When I meet sales leaders for the first time, one of the questions I usually ask is, “Who is your top salesperson?” Very often, the answer is the name of a woman.
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