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Artificial Intelligence (AI) has the potential to impact Sales Performance Management (SPM) in a big way. Still, it may or may not be the answer for you right now. In a previous blog we gave a short primer on AI and looked at the scope of the potential impact of AI on SPM. In our webcast, “Can AI Transform Sales Performance Management?” Lily Scanlon, Principal in Korn Ferry’s Sales Effectiveness Practice, provided a good overview of what’s possible and what’s realistic in the realm of AI and advanced analytics for most sales organizations today.  

The webcast gives sales management and sales operations a primer in what AI is, what it can do to impact sales performance, what kind of commitment is required, and how to realistically get the most value and ROI from the technologies available today. 

How Can AI impact Sales Performance Management?

So, how can AI be applied to sales performance? First, AI applications generally fall into one of three categories:

  • Predictive:Using historical performance data to predict future performance (set quotas, forecasts, predict customer behavior, upselling/cross-selling)
  • Prescriptive:Analyze data and decide on the best path to meet goals (territory allocation, guidance for sales reps, lead scoring and opportunity ranking based on propensity to buy)
  • Robotic Process Automation (RPA):Automation of tasks that don’t need a human (low complexity dispute resolution, data cleansing, data visualization, appointment/meeting creation)

According to the Salesforce research, the main use cases for AI in sales include:

  • Intelligent forecasting:Data science insights on commit, open pipe, and likelihood to deliver on target
  • Opportunity insights:Customer sentiment, competitor involvement, and overall prospect engagement
  • Lead prioritization:Automatically prioritize leads most likely to convert based on history
  • Account insights:Surfacing of business developments relevant to accounts, such as by scanning social media and news
  • Activity capture:Connecting data from sources like email, calendar, and CRM to automatically update records
  • Guided selling:Opportunity ranking by potential value and sales activity effectiveness

Another example is more of the RPA variety, compensation dispute resolution, which is most useful for low complexity, high volume disputes, where showing the sales transaction, commission splits, and calculations will answer the question (assuming this data is available).

What’s the ROI?

According to a report by Teradata, for every dollar invested in AI today companies expect an average return on investment of $1.23 within the next three years, $1.99 in the next five years, and $2.87 in ROI over the next 10 years. But each case will be different, so this is something you will have to evaluate based on your own vision, goals, opportunities, strategy, and investment. And there may well be other options that deliver much of the benefit at significantly lower cost. We'll get onto that in the next blog. 

So, are you ready to make the commitment to AI? Is it the best route to sales performance and ROI for your company? To help decide, watch the free on-demand webcast Can AI Transform Sales Performance Management?

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