ThinkstockPhotos-166578139 If you’re in sales, you probably don’t consider yourself to be a science nerd. But many sales teams are learning that data science can help them do very interesting things when it comes to sales performance.

Take the common challenge of increasing sales velocity. Every effective sales leader knows that velocity can be improved in a number of standard ways.

  • Increasing your number of pipeline opportunities.
  • Improving your average win rate.
  • Increasing your average deal size.
  • Reducing the average length of your sales cycle.

Typically companies choose to address velocity by increasing the number of opportunities in the pipeline. There are two risks with this approach.

Risk #1: Just because you are increasing the number of opportunities in the pipeline does not mean that these opportunities are qualified and that you will win these deals.

Risk #2: When you increase the number of opportunities, you also stretch your sales resources and potentially restrict the sales team’s ability to win deals.

So, how can you really increase velocity without having to artificially increase the number of opportunities in your pipeline? Sales organizations that are ahead of the curve are now turning to data science for help.

For example, our own OppScore uses predictive analytics algorithms to analyze historically closed opportunities and isolate patterns of data signals that contribute to wins. These patterns are then applied to open opportunities and a 0-100 score is assigned to every opportunity. The higher the OppScore, the higher the likelihood of winning the deal.

Interpreting your OppScore is easy, because all the opportunities are categorized into four buckets: Very Likely, Likely, Somewhat Likely, and Not Likely. The accuracy of predictions is self-evident when you look at win rates for each of these opportunity buckets. For a typical customer, it would look as shown in the chart below.

Let’s now look at how a sales organization can improve sales velocity based on this insight.

  • By de-prioritizing qualified deals that still fall in the Not Likely bucket, the pipeline becomes leaner but is now filled with higher quality opportunities. This has a negative effect on the sales velocity formula, because you’re reducing the number of deals anywhere from 10% to 30% depending on a company’s pipeline. However, this negative effect is clearly cancelled out by the next two positive effects.
  • The overall win rate goes up significantly—anywhere from 30% to 40%. This increases the company’s velocity.
  • By focusing on fewer opportunities, the sales cycle drops for the opportunities pursued, which also helps improve velocity.

In addition to providing an objective measure for the likelihood to win, OppScore surfaces key risk factors for each individual deal. Factors such as whether a deal is overpriced, if a deal is being pushed an unusual number of times, or if a deal is stuck in a certain stage are immediately surfaced and they act as early warnings so that sales managers can intervene and coach the sales rep. C9 clients have used their OppScore to significantly improve their ability to move deals in the right direction, which has reduced their sales cycles and improve sales velocity. Isn’t this cool!  (And perhaps why Gartner recently named C9 as one of this year’s Cool Vendors in the Tech Go-to-Market.)

Yes, salespeople still need to master the art of selling: connecting with customers, cultivating relationships, and closing deals. But data science can be a lethal weapon that helps salespeople quickly focus on the right deals, identify key risk factors that can impede wins, and accelerate sales.

Interested in learning more about C9 OppScore and empowering your sales team with data science? Sign up for a free demo at


Shiv Ramanna is a senior product manager at C9.