Sales research suggests that the single biggest driver of improved sales effectiveness is sales coaching. According to the Corporate Executive Board, effective sales coaching can potentially increase top-line revenue by up to 20% (*). Unfortunately, most sales organizations lack any structured systems or tools that provide sales leadership the right content and context to coach from.
Data science can be an immensely powerful source of quality sales coaching. Here are a few examples of what data-driven insights and sales coaching can do for a sales organization:
Identify At-Risk Deals. Early.
Data science can be used to monitor the “health” of deals. When a deal falls off a “winning trajectory” or is about to fall off, a sales manager can be alerted which can prompt a conversation about the deal and its circumstances, and corrective action can be taken. By providing early alerts and identifying swing deals, data-driven sales coaching is a powerful tool to hit a sales target and allow every rep to sell at his or her highest potential.
Prioritize. Prioritize. Prioritize.
Historical patterns of deals can be used to predict which deals are more likely to move to the next stage relative to other deals, and how sensitive they are to effort. This kind of information can be used by sales managers in their 1:1’s with reps to identify which deals to prioritize and which deals to deprioritize.
Discover Possible Upsides.
Data-driven applications often find a way to “score” the object in question – whether they are marketing leads or opportunities for sales. These scores can be used as a prioritization mechanism but in the sales scenario, they can also be used to discover upsides. For example, a deal that has a “decent” score, but isn’t in “Commit” could be the topic of a conversation to determine what actions to take to move this deal further along and thereby close the Commit-to-Target gap.
Track Deal Changes.
Data science can be used to provide a more sophisticated view into deal velocity. This in turn can determine the health or staleness of pipeline deals. Sales managers can then track and help reps manage and navigate their deal-landscape, and make the right decisions.
Get an Unbiased Forecast.
Sales managers who are armed with a predictive analytics forecast can use the unbiased information that it provides to investigate discrepancies with the internal numbers. This is often a great starting point for more detailed conversations around deals that might have been missed in a conversation with a sales rep that only touched on “top-of-mind” deals.
Sales coaching done right can be a game-changer. But until recently, there has been a dearth of applications that focus on harnessing the power of big data for the benefit of sales users (see why.) With the advent of the first of these kinds of tools, Sales Coaching is just entering a massive disruption cycle, and with it, we can expect dramatic improvements in sales effectiveness and other sales metrics.
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