How I Learned to Stop Worrying and Love Predictive Sales Analytics

predictive sales analytics

By Kevin Brooks

Predictive analytics is a major topic at industry conferences, but it is poorly understood by most sales leaders. In truth, it is poorly understood by most people, but – as the market for predictive sales analytics continues to grow at a rapid rate – today’s sales teams are in the midst of a steep learning curve about the potential benefits of this powerful technology.

Sales has always been an information game. The more you know about your prospect, the market, your product, etc., the more likely you are to close the deal. This is as true today as it was back in the days of Willie Loman. But the advent of, the rise of digitally-connected buyers, and a steady increase in computing power have brought about an age of data unlike anything poor old Willie could have imagined.

With great data comes great responsibility. Having access to the full archive of a customer’s history, competitors, org chart, stock performance, demographics, and compelling business events is tremendous. Knowing how to put all that information to use – and to do so quickly and strategically – is a different kind of challenge requiring different skills and tools. An explosion of marketing automation tools and solutions has evolved to fill this gap, most of them focused toward the early stages of the demand generation pipeline. By some estimates, the market has grown from 150 to more than 3,500 solutions in the past five years.

There is a difference between marketing analytics and sales analytics, and confusing the two can create problems. For example:

  • Highly scored leads may be unrelated to those likely to close.
  • Creating demand requires different activities than creating revenue.
  • MQLs are the end of one process; SQLs are the beginning of the next.

When you talk about predictive analytics, many people picture the classic “laboratory” approach with white-coated data scientists and complex equations on a whiteboard. Because sales is often consumed with immediate quarter-closing priorities, any discussion about data and analytics is often relegated to the finance or marketing teams that have time and resources to engage in laboratory analytics. Sales needs something different: a new kind of “operational” analytics, fully integrated with their daily workflow and constantly adapting to new conditions and situations.

Consider today’s sales rep, logging into his or her CRM system and viewing a list of leads to pursue or qualify. Even if the leads have been targeted and drip-marketed and screened and filtered by marketing, a sales rep still must assess data and organize his or her time effectively. Time spent pursuing business that is unlikely to close loses both the opportunity and the time itself, and setting an incorrect close date or amount can demoralize a rep and screw up a pipeline forecast for the entire company.

This is why predictive sales analytics is making such a strong impression. Knowing which leads are most likely to turn into revenue – and prioritizing actions that can make a borderline opportunity tilt toward a closed deal – is an intoxicating power. Being able to do this consistently, quarter after quarter, for all levels of a sales organization is nothing short of miraculous when compared with previous approaches. The impact can be eye-opening:

  • 200 percent increase in opportunity close rates
  • More than 25 percent lift in overall booked revenue
  • 50 percent faster ramp time to productivity with new sales reps
  • More accurate and consistent pipeline forecasting

The good news is that sales-focused solutions are out there, and we’re finally starting to bring analytics out of the laboratory and into the operations of the business to help everyone win, win faster, and win far more frequently. The challenge is to stop looking to marketing solutions to tackle sales challenges.

To learn more about this subject, join DxContinuum for a session at the upcoming Sales 2.0 Conference in Boston where speaker Sam Capra, RVP of Sales, will present “Sales Technology Overload: How to Select the Right Tools for Your Sales Organization.” He will lead a candid conversation about steps you can take to eliminate some of the noise around identifying and selecting the right technologies for your sales team. You will walk away with a clear strategy on how to identify and select the right sales technology partner(s) for your company based on your goals, industry, and budget.

KevinBrooksAs Vice President of Marketing, Kevin Brooks ( is responsible for all marketing at DxContinuum, Inc., a leading solution provider in the field of predictive analytics for sales teams. He is a marketing innovator with more than 20 years of leadership experience in both startup and Fortune 100 software companies. His most recent role was Chief Marketing Officer at Ivalua, Inc. Prior roles include Senior Vice President of Marketing at iTradeNetwork, Inc., and Chief Marketing Officer positions at FoodLink Holdings, Inc., IQNavigator, and TrueDemand Software. He is also known for cofounding the procurement industry media site Spend Matters as well as for his marketing leadership at Ariba and ADP. Kevin is also chair of the board of directors at the Santa Clara Vanguard, a national nonprofit youth music and arts organization, and he holds a bachelor of arts degree from Macalester College.

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