Combine sales incentives with machine learning to increase sales

In the U.S alone, thirty-eight million people start their day by eagerly fastening a device to their wrist that isn’t for fashion or keeping time.

Combine sales incentives with machine learning to increase salesIt’s a fitness tracker. And these little gadgets have swept the nation. People love having instant access to their performance, activities and goals; they enjoy tracking their progress throughout the day; and they are addicted to the gratifying notifications of success, plus the social aspects of competing with friends, family members and coworkers.

The fitness tracker market has achieved tremendous success by providing consumers with relevant data and motivating incentives. They are successfully inspiring the world to be more active by leveraging principles from both data science and behavioral science.

When behavioral science meets sales incentives

So what does this have to do with sales incentives? Human behavior can be seen as the byproduct of millions of years of evolution. To change it, we must embrace our human nature, instead of fight it. And one of the most powerful tools to help enable change is data.

Data science is a discipline that allows us to analyze the unseen – and with machine learning, it allows us to look at large sets of data and surface patterns, identifying when past performance is indicative of future results. For instance, we can forecast what products are most likely to be sold and which customers are most likely to buy.

But what if you sought more than to just understand potential outcomes? What if you could completely change outcomes? More specifically, what if you aimed to change the way in which people behave?

Behavioral economics tells us that making a fundamental change in human behavior that affects the long-term outcome of a process requires an inflection point.

What’s a successful tool to create an inflection point or get someone to do something they would not ordinarily do? Incentives. In our case, sales incentives.

How to use science with sales incentives

Let’s say two years ago, your total bookings was $1 million. Last year, it was $1.1 million. And this year, you expect $1.2 million. The trend is clear. Growth has been linear and predictable. However, a change in company leadership results in an increased quota of $2 million for next year.

What is going to motivate your team to practically double bookings? The difference between expectations ($2 million) and reality ($1.2 million) is often referred to as the “behavioral gap.” When the behavioral gap is significant, an inflection point is needed to close that gap. The right incentive can initiate an inflection point and influence a change in behavior. Perhaps that incentive is an added bonus, President’s Club eligibility, a promotion, etc.

Data scientists work with product and sales teams, employing data and patterns to manage incentive programs. Using forecast modeling and behavior mechanics, teams can plot out the path from one goal to the next and analyze and implement proper incentives.

Technology uses machine learning for sales incentives

Imagine you use a CPQ tool to manage complex quoting and pricing processes. One of the major reasons your company invested in the CPQ solution was to curb chronic, costly discounting by the sales team.

A new sales rep is using the CPQ solution. Mid-quote, your system alerts the rep that the discount he entered – while within the approved range – may not be ideal. Machine learning runs in the background and identifies a different discount used by the top 10 percent of reps that has a higher success rate. Additionally, the system tells the rep that if he uses the prescribed discount, he’ll earn 40 percent more commission! Talk about a relevant incentive based on powerful data.

If you use sales activity management software, personalized scorecards act like fitness trackers for every member of your sales team. Each sales rep is equipped with a mini scorecard that tracks their real-time sales metrics and follows them around in CRM. This type of machine learning helps sales managers identify where and when they can use sales incentives as inflection points to spike performance.

When applied together, data science and behavioral economics provide powerful business results by collecting relevant, timely insight and defining sales incentives that align human behaviors with organizational goals.

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Sarah is a Director of Product Marketing at Apttus, focused on the Incentives portfolio including Incentive Compensation, Promotions and Rebate Management. She has decade of experience in high-tech, communications and logistics industries and she enjoys designing innovative, customer-focused content and solutions.

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