Artificial intelligence is already one of (if not the) hottest topics in the world of business tech. 83% of companies already say it’s a top priority in their business plans.
McKinsey estimates AI can bring a potential $13 trillion to the manufacturing sector by 2030. And Accenture predicts a 40% productivity boost by 2035 in industries that adopt AI.
There are dozens of ways to integrate AI into your workflow. Generative AI apps like ChatGPT probably come to mind first. But that’s just the tip of the iceberg.
Your mind might not jump to the quote-to-cash process when you think about where to apply AI to your business. But it’s the most important aspect of your sales operations — everything from quoting to contracting to the final transaction falls under this umbrella.
The good news: There’s a new breed of AI-powered CPQ (configure, price, quote) software transforming the modern sales process.
And it’s transforming it for the better.
How AI and machine learning work within CPQ software
CPQ software provides a platform for product selection/configuration, pricing calculations, and quote generation. These are tasks your sales team would normally have to do manually. They’d need to reference multiple systems, deal with complicated pricing structures, and put everything into a quote template themselves.
With the intuitive interface CPQ provides, that’s no longer an issue. It automatically applies your product rules and pricing logic to create an accurate branded quote.
AI supercharges this process.
There are a few places where AI can be particularly useful when delivering quotes:
- Dynamic product recommendations
- Automated pricing adjustments based on real-time data
- Data entry when building quotes
- Analyzing pipeline data from leads and sales transactions
- Forecasting and predictive analytics for accurate pricing strategies
AI can also assist with contract negotiations, identify upsell/cross-sell opportunities, and even help with lead prioritization. And when you integrate CPQ and CRM, the amount of data and workflow automation at your disposal multiplies exponentially.
AI and ML facilitate smarter quoting.
It’s simply too risky to use spreadsheet- or document-based quoting. Your rep might miscalculate pricing. They could quote a customer for a product that doesn’t fit your current delivery capacity. Or, they might simply forget to include a line item.
With AI and ML in play, you’re getting an optimized quote every time. No more guesswork or manual inputting errors. Your reps can focus on selling, and nobody will have to go back and fix things later.
Let’s dive into how AI-powered quoting works.
Intelligent configuration
Traditionally, configuring complex products requires you to define and apply a bunch of different rules and constraints, like feature dependencies (if one option is selected, another must be excluded), pricing adjustments, and manufacturing limitations.
AI enhances this process by continuously learning from past configurations and interactions. It applies these insights to predict the best product combinations based on a customer’s specific needs.
Through guided selling, the end user gets a personalized experience based on their unique requirements. This makes for a fast, error-free process.
For manufacturers, when you integrate CPQ with your ERP system, the AI-driven platform will also dynamically adjust available options based on your current production capacity. That way, your sales reps always see viable configuration options, and nothing else.
Predictive quoting
ML algorithms analyze vast amounts of historical sales data — past quotes, customer purchase histories, transaction outcomes, you name it. They can also segment customers based on behavior, purchasing power, and price sensitivity.
By learning from these trends, your system can predict what price points will most likely result in a successful sale.
Imagine a business selling custom manufacturing equipment. A repeat customer requests a quote for 100 units of a product.
Here’s how predictive quoting works:
- Upon analyzing the customer’s past orders and negotiations, it appears the customer previously requested a 15% discount on bulk orders.
- The system looks at your input costs and determines the price of raw materials has risen by 5% since the customer’s last order.
- The system adjusts the base price to account for increased costs — a 12% discount is sufficient to win the deal while maintaining a healthy margin.
- Based on this analysis, the CPQ system generates a quote with a 12% discount, forecasting that the customer will likely accept it, given their historical negotiation patterns.
This intelligent configuration leads to higher customer satisfaction, as the system accounts for real-world constraints and preferences automatically.
Dynamic pricing and margin optimization
AI can dynamically adjust pricing based on real-time factors like market demand, competitor pricing, customer profiles, and historical data. Of course, it considers your profit margins as well.
If you’re operating in an industry where prices change quickly and frequently, dynamic pricing gives you the power to react just as quickly.
And if you use custom pricing (e.g., for an enterprise SaaS product or engineer-to-order manufacturing deal), you’ll need CPQ’s AI features to account for profitability when quoting each customer.
When your rep quotes someone someone below the minimum profitability threshold, the CPQ will flag it and prevent them from going through with the deal.
Personalized customer experiences
Since AI-powered CPQ systems analyze your customers’ purchase history, it’s easy for them to make targeted upselling/cross-selling recommendations for your sales reps.
This streamlines quote delivery and increases your average deal size, sure. But it also makes the buying experience more personalized.
In a world where 86% of B2B buyers expect companies to be well-versed in their preferences during sales interactions, this is the difference between long-term customer satisfaction and losing the deal altogether.
Churn risk analysis
CPQ with AI revolutionizes financial forecasting. Since it has a wealth of customer data, it can also assess customers’ likelihood of churning.
For subscription-based businesses, this means the CPQ system can analyze how likely a customer is to renew or upgrade. It considers factors like contract length, product usage trends, and customer preferences.
For manufacturers and consumer goods companies, PROS Smart CPQ is a solid example of this. Its churn forecasting algorithms consider all the factors that influence customer churn. You can use this data to plan out retention strategies or change your sales approaches based on the chances of success with each customer.
Enhanced sales enablement
CPQ itself is a sales enablement tool. With AI, it becomes an even more powerful asset.
Through…
- Guided selling
- Automated configuration
- Predictive quoting
…your reps can focus on building relationships and selling. No more backtracking to fix mistakes or incorrect configurations after the fact. And they have all the information they need to act as trusted advisors when working with prospects.
Beyond this, your sales leaders can use CPQ data to look at sales cycle times and sales rep performance. From there, they can identify knowledge and skill gaps, and develop training programs tailored to specific needs.
Achieving business success with AI-enhanced CPQ
Aside from the obvious benefits of AI-powered quoting, like improved accuracy and faster quote delivery times, there are tons of advantages you probably haven’t considered. For instance, the more data an AI system collects, the smarter it gets.
AI can analyze past quotes, sales transactions, and customer data to learn about pricing strategies and identify trends. This means that over time, your CPQ software will be able to generate more accurate quotes with less human intervention.
To help you grasp the concept more clearly, let’s take a look at a few real-world examples.
Infosys and Salesforce CPQ
Infosys has integrated AI into Salesforce CPQ to enhance the quote generation process with features like guided selling and natural language processing (NLP).
AI makes it easy to create quotes by allowing sales reps to use generative AI models, which can ask dynamic, context-based questions. That way, they can better tailor product configurations and quotes to each customer’s business needs.
Oracle and Oracle CPQ
Oracle used its own CPQ solution to significantly streamline and enhance its sales operations. By leveraging the AI within Oracle CPQ, the enterprise software vendor was able to successfully introduce automated, self-service quoting options.
The result was an increase in self-service quotes from 2% to 79%, a 4X reduction in time and effort to get new products to market, and a 10X boost in order accuracy.
And, since customers could generate accurate quotes independently, they reduced their overall sales cycle and enhanced the customer experience.
Tacton for manufacturers
Tacton, a leader in AI-powered CPQ for manufacturers, surveyed hundreds of businesses and learned that 59% of them were excited about AI’s potential to improve their operations. So, they helped businesses transform their sales processes by embedding AI capabilities into their CPQ solutions.
One key success was in automating complex product configurations based on customer preferences and market conditions. AI-driven dynamic pricing optimization allowed these businesses to respond to market fluctuations in real time, improving profitability while maintaining competitiveness.
Yagna iQ Renewal Cloud
Yagna iQ provided a specialized AI-powered CPQ solution for Cisco renewals, giving partners like Arsenal Infosolutions and Brilyant IT Solutions the power to automate their entire contract renewal process.
The platform’s “Journey Builder” feature facilitates proactive notifications and personalized engagement with customers, both of which lead to a more seamless renewal experience.
The AI also gives companies insights into customer behavior by tracking interactions. This improves channel partner relationships and drives operational efficiency.
Camos CPQ and capital goods manufacturers
Camos CPQ is one of the top solutions for enterprise manufacturers. Manufacturers use Camos’ AI-enhanced CPQ software to optimize the content within their quotes, streamline the product configuration process, and use intelligent search functions to reduce the time required to create quotes.
AI tools also help users evaluate product models and simplify comparisons between different products, which makes for a far more efficienct B2B sales process. They’re especially useful in industries like mechanical and plant engineering, where customization and complexity are big challenges.
CloudSense for telecom companies
CloudSense helps telecommunications and media companies leverage AI in their quoting and order management workflows through dynamic pricing and visual configuration. They use AI-driven insights to guide sales reps through the quoting process, ensuring that all product and pricing options are considered.
For example, when a customer is configuring their service plan, CloudSense’s AI technology can recommend add-ons or upgrades based on the customer’s usage patterns. The result is a more personalized quote for the customer and a more profitable one for the company.
Emerging trends in the CPQ space
While AI has already made massive waves in the CPQ space, there are other emerging trends worth keeping an eye on.
Predictive analytics and pricing optimization
AI and ML are enhancing CPQ systems by predicting optimal pricing based on historical sales data, customer behaviors, and real-time market conditions.
With this level of granularity, you can offer dynamic, competitive pricing that maximizes profitability while considering input costs and customer price sensitivity.
You can also set customized pricing models with guardrails for minimum profit margins and approval workflows for complex, high-value deals.
Essentially, it solves all the problems your having with an outdated pricing process.
Explainable AI
As AI models become more complex, businesses are focusing on explainable AI to make machine learning models transparent and trustworthy. In CPQ, explainable AI helps users understand why a specific configuration or pricing was recommended, making the process more reliable for sales teams and customers.
Visual configuration with AR/VR
Visual configuration through built-in 2D and 3D configurators has been around for years. So has CAD automation.
The integration of augmented reality (AR) and virtual reality (VR) is providing customers with interactive and immersive experiences, enabling them to visualize product configurations in 3D.
In industries where complex products require high levels of customization, like engineer-to-order manufacturing, this makes it easier to align sellers/engineers with buyers to co-create the perfect solution.
Personalization throughout the customer lifecycle
CPQ systems already use ML to deliver personalized product recommendations and configurations based on customer preferences, previous purchases, and market trends.
Now, you can also use it to offer personalized billing experiences.
Zum Beispiel:
- Customer-specific discounts and promotions
- Usage-based pricing models
- Upselling and cross-selling opportunities
- Loyalitätsprogramme und maßgeschneiderte Anreize
This level of personalization creates more engaging and satisfying experiences for customers. For you, it’ll increase CLV and retention rates.
Explore the transformative impact of AI-powered CPQ
It seems like a lot, but the reality is most CPQ vendors already are building AI features into their platforms. The benefits are huge but the actual changes to the application’s interface and functionality are quite small — you might not even notice AI is working behind the scenes.
When you’re selecting a new CPQ vendor, test the AI and automation features it offers. Ask about use cases and customer success stories, too. That way, you’ll find the solution that best fits your organization’s unique needs – and gives you a competitive edge.Ready to find the right CPQ for your needs? Take a look at our CPQ reviews and product comparisons to make an informed decision.
Andrew ist ein professioneller Texter, der sich auf die Erstellung von Inhalten für Business-to-Business-Software (B2B) spezialisiert hat. Er recherchiert und verfasst Artikel, die seinen Lesern wertvolle Einblicke und Informationen bieten.