CPQ Solutions with AI are the Next Gen Revolution in Manufacturing Sales

In the realm of business growth, few processes are as pivotal as sales. While technology has aided and accelerated sales, many critical forms of purchase still require human touch or aid. Bulk purchases, large deals, and custom deals involve nuances and complexities that require experienced individuals to convert. This is especially true for manufacturing, where custom orders can come with engineering complexities and require the department’s involvement, making things very complex and slow.

Configure, Price, and Quote (CPQ) solutions are the answer to these obstacles. CPQ solutions allow an accelerated process for custom sales with quick pricing and quoting through a digital customization experience. They don’t just speed up the process; they can also provide accurate information and eliminate inter-departmental dependencies. However, there is still some margin for error if the back-end configurations, rules, and decision engines are misconfigured. This is where AI comes into play!

But first, let’s look at why CPQ solutions are highly compatible with AI, especially in manufacturing.

Why are AI and CPQ Solutions Deeply Linked in Manufacturing?

If we draw parallels between CPQ and AI implementations, there are some common grounds that are easy to find, like:

• Both systems utilize historical data from multiple sources to deliver customized and/or personalized solutions to end users.
• CPQ tools require pre-defined rules to enable customization and subsequent pricing and quotation. These rules and configurations need to be updated periodically, which can utilize an AI’s self-improving nature.
• AI is great at handling complex calculations while accounting for multiple criteria, an essential requirement for CPQ tools to speed up their output.
• AI is one of the best decision engines out there, another complementary capability for aiding CPQ solutions.

AI is complementary to CPQ solutions in manufacturing, aiding in high-level customizability, fast calculations, and accurate decisions. This eliminates the need for inter-departmental involvement in the configuration and pricing processes. With AI, these horizons can be expanded to include more complex customizations. This is one of the biggest reasons why manufacturers must look into CPQ solutions with AI.

We will explore other advantages of AI in CPQ solutions later in the article. Before that, it is important to understand manufacturers’ needs for CPQ solutions and the complexity of customizations in manufacturing orders.

Why does Manufacturing need AI-CPQ Solutions?

A CPQ solution’s role is to perform complex calculations across systems, assemblies, and raw materials to derive the right pricing for a configured product. This process involves financial operations, engineering, production management, inventory planning, and several other departments for generating the various Bill of Materials (BOM) and eventually collating them into quotes.

Depending on the product, generating quotes can take several weeks to months. The process also becomes highly error-prone due to the multiple people and departments involved. Even small human resources, management, or methodology changes in any department can create obstacles in the process. 

AI-based CPQ solutions can overcome these challenges by automating the entire process with periodic updates to the necessary parameters. A healthy and fast sales process can be achieved with CPQ in manufacturing, bringing down quotation time to hours. It helps manufacturers provide competitive pricing and improve their bottom line in multiple departments. Improved customer experience and satisfaction are other advantages of CPQ solutions.

CPQ solutions also allow manufacturers to configure internal operations in parallel with sales. For instance, the BOMs are required in multiple formats for different steps/levels in the production process. These can be easily automated with CPQ solutions and AI. Deeper integration of CPQ and AI with CRMs and ERPs can unlock many such capabilities.

What Does AI Offer with CPQ Solutions?

We have touched on some of the technical capabilities while considering the compatibility of AI with CPQ systems, but that’s not all. AI brings other inherent and intrinsic advantages to the table that can add more value to CPQ and manufacturing sales processes. Here are a few of the most empowering ones.

Advanced Marketing and Sales Enablement

At this point, personalization is taken for granted when we think of AI. But there is a way to take it a few steps further. Consider a sales representative using an AI-powered CPQ tool to consult a potential customer. With the help of AI, the representative can also provide deeper insights, useful information, and risk assessments to the customer on the spot while giving them real-time feedback on customizations.

This is just one example of how AI can power CPQ systems and directly aid in the sales process with real-time customer-centric and product-focused analyses. It can directly help improve the customer experience and brand image.

Chatbot-Based CPQ Interface

A manufacturing CPQ interface is generally very technical due to the nature of the tool and the complexity of use cases. However, AI integration can provide a human-like communication experience alongside it or a chat interface to talk to the customers while converting the cue to customizations, giving customers a real-time feedback-based experience.

This kind of interactive experience can be highly advantageous for manufacturers by providing guided self-service to customers.

Wider Data Integration for CPQ

The database, rules, and decision engine of a CPQ tool are limited as per their requirements. With AI, CPQ systems can expand their analytical horizons with customer data on behavior, interaction, financials, etc. Even the AI decision engine can help provide much better pricing and quotes while assisting with pre-configured products, recommendations, and a  delightful experience.

There is also the stream of data AI can capture during the CPQ process for downstream applications like marketing, sales, engineering, and other departments involved in delivery.

Closing Comments

The above information points to the extensive advantages of utilizing AI in manufacturing CPQ solutions in various capacities. A recent study by the Harvard Business Review found that companies that use AI in sales have witnessed:

• Over 50% increase in leads and appointments
• 40%–60% cost reductions
• 60%–70% call time reductions

The study also comments on the value added by humans in parallel with AIs during the manufacturing sales process, with a greater focus on building relationships and brand value. Thus, AI not only accelerates sales with CPQ, but it can also have a wider impact through a variety of empowering advantages. Being a multi-departmental system, CPQ tools are often ignored by manufacturers due to the complexity of their setups and the risks associated with a flawed system. However, the gains are much more significant in the long run with AI-powered CPQ solutions. Current and upcoming economic scenarios demand that manufacturers adopt agile and scalable solutions to gain advantages, and AI-driven CPQ is among the most necessary options.