As a sales leader, you may find it increasingly challenging to decide how technology can improve your sales team’s performance.  In the past two years alone, there has been a literal explosion of new software products entering the market, and many of them use Artificial Intelligence (AI) to promise order of magnitude improvements in sales productivity.  As a software firm entering the market to enable our flavor of sales improvement, we had to consider how and why incorporating AI into our application made sense.  Our story offers some key ideas to consider as you look at how AI might impact your sales team.

Our AI Story

There is no shortage of hype about AI and how it will impact sales in the future.  The original intention of the partners at Funnel Metrics was to create an application that would help sales leaders evaluate their teams by assessing and scoring both quantitative metrics as well as qualitative skills.  Historically, we had achieved significant results by creating a sales rep scoring system in our previous careers as VP’s of Sales, primarily because scoring reps is more efficient than extensively analyzing CRM data and financial system reports.

As these new AI applications began to emerge, we realized that AI potentially offered an opportunity to assess and review a much larger data set.  AI also enabled the prioritization of quantitative metrics and skills that were driving successful sales performance. After all, AI is really just complex math and statistics that analyzes much larger amounts of data to interpret the results.  It would take a human hundreds of hours to analyze and assess all the information that an AI application can quickly analyze with far better results. We know this because we attempted to do similar analyses on spreadsheets, and the work effort was not sustainable.

AI at Scale

Several AI applications demonstrate this ability to process extensive data. For example, there’s an entire category of AI sales applications that capture e-mail, phone and other communications content, and then interpret content to determine how quickly an opportunity can be closed.  Similarly, some applications interpret conversations to help reps improve their conversational skills when conducting sales calls. These applications use an AI technique for language interpretation to perform conversation and/or content assessment. This is just one example of many different types of AI-based applications now available.

Making Choices

Realistically, with all the applications emerging in the marketplace, it’s difficult to determine what AI application offers the most improvement for the investment. Our experience as VP’s of Sales showed us that managers can expect to make only one or two choices that can effectively impact performance of their team in a given year. The reason is simple. There’s not enough time or resources to accomplish more.  If you are like most managers, you have to rely on the reporting and analysis that is generated from your CRM system to make these decisions.  What if AI could actually be used to determine what is most important and recommend what to change to improve sales performance?

Decide What to Do Before You Decide How to Do It

Funnel Metrics’ experience with AI showed that sales leaders first need to understand what to improve before determining a solution. Our FunnelocitySM application uses Machine Learning algorithms to determine the most important quantitative metrics and qualitative skills and behaviors that impact sales revenue. This permits Funnelocity to predict future rep sales performance over the next year and helps managers to quickly and easily evaluate and diagnose their team member’s activities to make prioritized coaching and management decisions.

Additionally, at its core, AI still requires someone who understands what to do with the logic and reasoning behind the calculations.  There needs to be human intelligence that diagnoses the problem, so sales managers aren’t guessing about the potential solutions.  At the heart of Funnelocity’s design is over 100 collective years of sales management experience to understand and diagnose sales productivity issues.  CRM generates significant data on a daily, monthly, quarterly, YTD and 12 month rolling average basis. Firms have hundreds of reports to analyze, yet it’s not clear if and how they point out the “conversation” problem team members experience. Yes, business conversations may be one critical issue that needs to be addressed, but how do you know that improving sales conversations for hundreds of reps is really the one problem demanding your focus, not to mention hundreds of thousands of dollars of investment?

Using the Power of AI to Impact Performance

We believe the power of AI should first be used for diagnosing and predicting the most important factors that influence revenue performance. The core of FunnelocitySM is an AI model that uses machine learning to predict what quantitative metrics most influence a rep’s ability to successfully generate revenue, and to reveal what metrics, behaviors and skills will have the most impact on sales revenue performance. These diagnoses allow managers and reps to decide what actions to take and ultimately determine what tools will most impact your team’s ability to sell.

Having a better sales tool to improve velocity and shorten the sales cycle is great if you are certain that reducing the sales cycle length will have the greatest impact on rep performance. Otherwise, your sales team will just lose deals at a high speed! Having an application that figures out where to make those one or two key changes is invaluable to improving team performance!