AI and CPQ: The Three Ways AI Makes a Difference

Artificial Intelligence and augmented intelligence (AI) have been around for a long time now, but it’s only recently that companies have started applying it to sales and configure, price, quote (CPQ) processes.

According to the Harvard Business Review, a full 60 percent of executives believe their future success depends on the successful implementation of AI, and this no doubt includes sales ops leaders.  AI and CPQ: The Three Ways AI Makes a Difference

By now, most sales operations managers have their eye on AI as a powerful tool to accelerate onboarding, significantly improve pricing, cross-selling, and upselling; and change their workload from tactical to strategic. It can absolutely do all of this and more.

But first, enterprises sales operations teams and sales leaders need to have a solid understanding of what AI is and what it isn’t.

It should be noted that AI is not a way to have your decisions made for you by a machine or software program. It’s a way to empower your salespeople with quick, granular insights, and to incorporate data you didn’t even know you had into your sales ops lifecycle so that your salespeople’s own decision-making becomes way smarter and way faster. That’s why augmented intelligence, not artificial intelligence is a much more accurate way to describe how AI is enhancing B2B applications today.

Used correctly, AI has the potential to significantly improve your sales processes by creating high value, easily handling all the complexity that comes with scale, and saving you from the tragedy of missed opportunities.

More specifically, in CPQ, AI will have the following impacts:

1. Decision making

Where AI is perhaps most powerful and valuable in sales operations is in gathering data enterprises were not tracking and mining it for precious insights that end up being game-changers in the lead to cash lifecycle.

AI leverages the rich data that exists around lead-to-cash decisions and uses it to develop models for likely outcomes given different pricing, products and configuration points. These models provide sellers recommendations for action, guiding their actions with an intelligence otherwise unreachable by humans. It does this by running simulations and providing recommendations at the right time to achieve the desired business outcomes (i.e., more sales, with margin preservation).

With the rise of sales-ramp time, guiding new hires through the quoting process is crucial to accelerate your return on investment. Combined with actionable up-sell, cross-sell and configuration recommendations, you’ll ensure your sellers never leave money on the table while delivering products and services your customers want.

2. Price optimization

Grocery stores are already proving the AI model as much in price as in service, and there’s no reason enterprise B2B sales ops leaders can’t use the same technology for their own products.

AI can analyze historic price patterns and sell points far better than any human or human-powered system, uncovering dynamic relationships between cross-category cannibalization, price sensitivity, promotional cadence and approval processes.

This is especially important when you have a complex product with a lot of different moving parts and price points. A non-AI-powered solution isn’t going to be able to take into account how a price change in one part will impact other items, because it will be treating every item as an independent event rather than as an ecosystem of interrelated parts. Your sellers may only rely on the experience of the person sitting next to them or their manager to set the price. AI, however, can make the connections between data to provide valuable insights on how one small price change can ripple through your entire quote and maximize your chance to win.

3. Injection of creativity and strategy

Finally, by improving the efficiency, accuracy, and profitability of your sales operations, AI replaces the tactical workload of price management off your sales operation team’s plate so they can focus on strategic programs, analytics and insights that drive revenue.

Moreover, sales will have more data than ever before at their fingertips without being overwhelmed by this data. That’s because their AI engine will be combing and learning from sales activity data and delivering insights they should be paying attention to at the right time.

AI for changing sales behavior

In the end, the real application of AI in sales operations is for permanently changing the behavior of your salespeople for the better, but in a way that makes them relatively unaware of the change that is occurring. It works seamlessly under the surface for your sellers, producing efficiency, quick and clear decision-making, and long-term change.

The correct AI application delivers immediate value without costly implementation and time consuming training by data scientists and promises to be the most powerful sales tool since automation—you just need to choose the right platform.

Learn how AI can help your organization hit your number and optimize your lead-to-cash processes.

By Kevin Markl | June 18th, 2018 | CPQ

About the Author: Kevin Markl

Kevin Markl

Kevin Markl has worked with CallidusCloud for six years, evangelizing the Lead to Money suite to align sales and marketing teams, replace disconnected systems, and drive bigger deals, faster.