It’s hard to imagine daily life without technology. Whether it’s the computer at your desk, the cell phone in your hand, or even the television where you shop online, stream your favorite shows, and catch up on the news, technology is everywhere. More recently, technology has evolved and artificial intelligence and machine learning (AI/ML) has grown in popularity. And to no one’s surprise, it is a part of our everyday lives.
When we search on Google, AI/ML intelligence helps autocomplete our search query and provides results based on our location and what others commonly search for. Netflix, YouTube, and Amazon all use AI/ML to recommend content and related products based on not only your behaviors but the behaviors of millions of other users.
From how we live to how to buy, both artificial intelligence and machine learning play an increased role in decision making. In fact, 49% of consumers are willing to shop more frequently while 34% will spend more money, according to AI Trends.
It’s not just our home and personal lives, however, that AI/ML is impacting. Business technology has boomed over the past decade, and it’s becoming almost second nature to automate processes in every company. In reality, if you’re company isn’t automating processes, you are already falling behind.
Unfortunately, businesses aren’t as quick to adopt AI/ML technology as we are in our personal lives. The 2019 pwc Annual Global CEO Survey found that 85% of CEOs believe that AI will significantly change the way they need to do business in the next five years, yet nearly a quarter of CEOs have no plans to pursue AI/ML “at the moment.”
Here’s the reality: AI/ML, when used correctly, can provide a huge competitive advantage for organizations—specifically for sales teams. There are a lot of considerations that go into the sales plans that drive growth and performance in your organization—and this is precisely where artificial intelligence and machine learning can be a vital tool.
The Value of AI/ML with Sales Technology
Sales Performance Management (SPM) has expanded in today's sales world. Primarily, businesses have focused on incentive compensation to drive performance, but it takes more than just optimized incentives to become a leading sales organization.
Gartner describes SPM as a collection of “tools and process functions that automate and unite back-office sales processes. It is implemented to improve sales execution and operational efficiency."
Ultimately, SPM helps you align your sales team around a single source of truth and use your data (along with AI/ML sales technology) to uncover strategic insights. You can then use those insights to inform decision making and planning continuously throughout the entire fiscal year.
Artificial intelligence and machine learning can be a game changer when it comes to transforming a data-driven organization with an SPM platform. But before you can take advantage of AI/ML sales technology, you need data to truly uncover the advantages of AI/ML technology. Without data, AI/ML is just a fancy algorithm and it won’t help you optimize planning and performance. It needs data to learn and provide insights.
Your data needs to be usable—that means, you must compile your data from all of the different sources and undergo data cleanups to ensure your data is accurate and concise. Then you’re ready to apply AI/ML to your dataset to gain strategic insights.
According to Gartner, “[Machine Learning] ML uses mathematical models to extract knowledge and patterns from data. Adoption of ML is increasing as organizations encounter exponential growth of data volumes and advancements in compute infrastructure.” However, only 4-14% of organizations surveyed leverage some form of AI in order to improve their processes.
The problem may stem from not knowing where to get started with AI/ML sales technology. At Xactly, we have shifted from focusing on Incentive Compensation solely, but to a broader sales performance management (SPM) approach. And AI/ML are crucial in identifying key areas of optimizing behaviors and performance across our platform.
How Xactly Applies Artificial Intelligence / Machine Learning (AI/ML) for Sales Organizations
Consider the following example: a top rep leaves your sales organization. What is the organizational impact in replacing him/her? On average, it costs between $115,000 - $150,000, taking into account the acquisition costs, training and lost territory sales. In addition, it takes a little over six months to hire someone and roughly a year for that new rep to be fully ramped.
Considering this scenario, there are a number of ways AI/ML sales technology can help not only plan accordingly in hiring, but also be proactive in rep retention.
- Ramp: We’ve heard from many different sales leaders about the desire to understand how long it takes a new rep to be fully ramped. By analyzing historical data indicators, AI can certainly analyze relevant historical data and provide recommendations.
- Annual Quota: There are a number of things to take into account including prior year numbers, similar sized companies and likelihood of attaining revenue based on current headcount. Does turnover impact this? AI can help provide a recommendation for this value.
- Monthly Seasonality Setting: Furthermore, how much can you expect individual reps and an organization to attain, can be driven by AI.
- Sales Rep Attrition: When assessing a sales organization, is someone at risk of leaving? Perhaps this is a top performer? Or perhaps a rep who isn’t performing but has no plans of leaving an organization?
All of these scenarios can be addressed by AI and ML alongside your sales technology, and can help organizations better prepare and set themselves up for success. The important thing to remember is that you need data to make your AI/ML sales technology useful. When you apply AI/ML, you gain a competitive advantage and can identify hidden opportunities to improve your sales planning and for your team to succeed. And the smarter your sales organization is, the more successful your team will be.