When I was young and fresh out of college, people urged me to start contributing to a retirement fund as soon as I could. They explained that since I had time on my side, even modest investments would pay significant dividends. I just needed the discipline to start saving early.

We’re all young, with respect to predictive analytics technology. According to Gartner’s Hype Cycle for CRM Sales, sales predictive analytics (which includes predictive forecasting, upsell/cross-sell recommendations and opportunity scoring) is still in its adolescence. This market is expected to grow quickly in the immediate future.

How can we take advantage of our youth, and get a head start on preparing for advances in predictive pipeline analytics?

Your CRM Thinks Too Linearly

Consider this. Your historic pipeline data suggests a correlation between sales stage and an opportunity’s likelihood to close. In many organisations, that correlation–directly or indirectly–informs seller coaching and forecasting decisions. But there is a disconnect between the sequential sales stages in a typical CRM system and the nonlinear buying process that customers actually follow. To improve the validity and accuracy of your pipeline analytics, you need to track more than sales stage. For this reason, measuring buyer behaviour along with seller-provided sales stage and probability clears a path to improved predictive analytics.

Much like that first 401k, procrastination means missing out. Collecting buyer activity data as part of your standard opportunity management offers both short term and long term benefits.

A Low-Risk Change

You can start tracking key buyer activities in your CRM without disrupting your existing sales process, and without investing in a new predictive analytics solution. There are immediate benefits to identifying key customer activities and tracking them in your CRM.

  • You’ll improve the quality of manager/seller deal reviews by focusing the conversation on verifiable customer outcomes.
  • You can supplement seller-provided sales stage and probability data with buyer activities in your existing pipeline analytics and forecasting.

Along the way, you’ll be building up a bank of buyer behaviour and outcome data. When you implement predictive analytics tools, that historical data will enable your new platform to offer much more accurate predictions and advice at go-live.

*This article is reprinted from the Gartner Blog Network with permission. 

Gartner for Sales Leaders clients can learn more about enabling buyers by reading Elevating the Value of Sales Interactions, and can explore the impacts on pipeline management and forecasting by reading Pipeline Management and Forecasting in a Nonlinear Buying Process.

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