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Named a Strong Performer in “The Forrester Wave™: Sales Performance Management Platforms, Q1 2023”

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The Artificial Intelligence Revolution in Sales Commissions

Table of Contents

Imagine a world where companies have the power to unlock their data potential, revolutionizing laborious manual tasks across the sales process —such as quota planning — with automated statistical analyses. 

To stay ahead of the curve, businesses are moving from traditional sales models to more modern approaches rooted in artificial intelligence (AI) and machine learning (ML).

Companies are looking to AI to help them make intelligent, data-backed business decisions that help them remain competitive and innovative in the marketplace. — Paul V., Principal, Deloitte Consulting

So, what can AI exactly do for sales?

What can artificial intelligence do for sales?

AI moves fast. Like really, really fast. It’s time to join the AI revolution or get left behind.

AI will only get better and better over time, crossing into thresholds where its utility becomes more realistic. Good AI is AI that you don't notice or see; it works in the background without the user knowing there's AI there at all. — Don B., Founder, BHuman.ai

Gartner, Inc. states:

By 2025, 75% of B2B sales organizations will augment traditional sales playbooks with artificial intelligence (AI) guided selling solutions.

That’s a considerable number.

When it comes to sales, AI can be highly impactful if you have access to data and a workable data set. 

That’s why companies are adopting AI across multiple stages of the sales process to unlock accurate, data-driven insights, shed light on realistic goals, and help forecast pipeline and revenue. By using insights from AI, sales leaders can:

  • Increase forecast accuracy: Better organize sales data to uncover patterns within the sales funnel.
  • Hone in on what matters: By increasing visibility into individual deals, AI can help sales reps focus on activities most likely to lead to closed-won
  • Optimize organizational growth: Make existing teams more efficient while increasing cost savings.
  • Increase productivity: Help find solutions that work and scale alongside the company.

According to Deloitte, the top AI use cases across the sales process span territory and quota optimization, forecasting, performance management, commission insights, and more (pictured below).

Deloitte point of view: the top AI use cases across the sales process.

In this article, we’ll focus on the impact of AI on sales commissions.

First things first … let’s talk data.

Why is it so important to "get the data right?”

Artificial intelligence in sales (or any industry for that matter) relies on data. Good data. A lot of good data.

As the saying goes, bad data in, bad data out.

Bad data makes it more difficult to take advantage of artificial intelligence and digital transformation, robbing companies of potential productivity gains. (Source)

AI is more accurate, consistent, and relevant with more data. It learns over time. The better the data input is, the better the output.

The challenge for companies is not only access to the data but the way the data is collected. When data collection is heavily reliant on individual users manually inputting data into various software tools, you become very susceptible to data entry errors.

According to Deloitte’s State of AI in the Enterprise, 4th Edition, data fluency is one of the three key Ingredients of an AI-ready culture (trust and agility being the other two).

Developing data-literacy skills builds confidence and a deeper trust in models and AI, which in turn can help set organizations up for positive outcomes.

Further, from the Deloitte report: 

In order for there to be AI success, people will have to change their relationship with data. — Andrew B., Chief Technology Officer, Tableau

The Deloitte report also conveyed that “data-focused organizations tend to require a more profound understanding of data. Workers should be incentivized to explain and justify model decisions; this serves to drive more creative insights as well as faster detection of model errors if and when they arise.”

The good news? Modernizing data infrastructure for AI is one of the top AI initiatives necessary to increase competitive advantage. This is because the success of AI relies heavily on having the right data to effectively “learn.”

Source: Deloitte, State of AI in the Enterprise, 3rd Edition, 2020

So, when you’re looking to uplevel certain aspects of the sales process, we suggest starting by asking the fundamental questions:

  1. Pick the algorithm(s): What algorithms do I need to transform data sets into the information I need?
  2. Determine the best data: What variables do I need to use?
  3. Clean the data: How can I effectively cleanse the data so I’m in a good starting position?
  4. Data integration: What data integrations do I need for my data set?
The biggest hurdle that companies seem to face is not around having the AI capability itself. A lot of companies struggle with having the data in an organized fashion to which they can apply AI functionality or capability. So where you tend to see AI being leveraged the most right now is in these very narrow point solutions because data is not as democratic as it ideally would be. — Paul V.

What are examples of AI for sales commissions?

Sales commissions are a vital component of variable compensation and are critical in motivating sales teams.

Access to sales performance data (deals won, trends, peer comparisons, etc.) is just table stakes. Today’s modern salesforce wants more visibility and transparency: sellers want to be able to focus on the forward-looking statement (like the one below) to help guide and inform selling activities and which opportunities should be prioritized for realistic success.

An example of a forward-looking statement predicting rep performance to help guide selling activities (e.g., “Do I have enough pipeline to achieve quota?”).
Pairing commission software with AI technology can help accelerate the what-if analysis. Reps today want more visibility into what they need to do to be successful and, further, how they might go about overachieving the goal. On the operation side of things, you can use these technologies to determine and predict the cost of sales based on various inputs, including quota, plan design, different performance scenarios, and even real-time data coming from the pipeline. I haven't seen companies doing this yet, but having both visibility and better forecasting into the cost of sales is highly valuable for multiple reasons. — Paul V.

AI-enabled tools are rapidly changing the way sales and revenue leaders operate. There is a real opportunity for these teams to combine commission software with AI technology to:

  • Recommend the best path for reps to achieve quota based on data-driven insights for specific deal types
  • Highlight reps at risk of underperforming ... and alerting managers to help get them back on track
  • Provide actionable insights to assist reps in closing more deals

The key result is salespeople will have more visibility into what they need to do to achieve (or overachieve) quota and the expected commissions they will earn. They can also have access to unprecedented levels of actionable insights that can help them move from reactive to proactive behavior:

  • What will happen if I close this deal? 
  • What do I have to do to hit my number? 
  • What do I have to do to get to 110% or 150% of my quota?

It’s time for companies to adopt a more prescriptive approach to their commissions solutions, especially as certain vendors are becoming increasingly easier to use and integrate with other existing tools and platforms. Cloud-based platforms like CaptivateIQ are the most open and easy to integrate, as they allow companies to share and leverage data in a way that benefits AI.

AI-enabled tools are finally getting the attention they deserve from sales and revenue leaders. By leveraging automation, AI, and ML for operational tasks, AI-enabled tools provide accurate and actionable insights that can't be achieved with traditional spreadsheet-based tools. This is helping business leaders work smarter and motivate and engage sellers to achieve maximum productivity. 

According to Forrester, personalized dashboards are a prime example of AI's uses in sales and revenue operations, providing valuable information at a glance while customizing insight to the individual seller. Given its current capabilities today, AI promises great potential for maximizing sales performance management (SPM) within organizations.

Want to learn more about how AI is changing the way sales teams operate and influencing the future of SPM? Download our whitepaper, Streamlining the Sales Process with Artificial Intelligence!

Make commissions 10x better with CaptivateIQ

Talk to our in-house experts to learn how you can make commissions a strategic growth driver.

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