CPQ levelled up – Potential use cases with AI

Generative AI – The latest buzzword in the tech sector has left everyone bewildered at its capabilities and at the same time, anticipating for its future possibilities.

To put it simply, Gen AI involves the use of machine learning models to create new and original content. These models are trained on a large set of data and can generate output in multiple formats – images, videos, text etc.

Predictive AI refers to the process of predicting the future outcomes by using all the relevant data that is available. It uses machine learning, data analysis and statistical models to predict future behavior.

Although it has existed in the tech world for some time now, Predictive AI has found a whole new set of use cases when combined with Generate AI.

What is Salesforce CPQ?
Part of a bigger Salesforce Revenue cloud model, Salesforce CPQ (Configure, Price and Quote) provides capabilities to streamline Quote-to-Cash. It has strong abilities in product bundling, complex pricing and discounting, contract lifecycle management and asset management.

Let’s explore some of the benefits of AI in a CPQ application.

Dynamic Pricing Optimization

AI can help boost revenue by providing strategies for maximizing deal size by providing the best prices based on customer’s recent selling habits, their market size, competitor’s prices, and the real-time market demand for the products.

Salesforce CPQ provides complex discounting mechanisms, but all that is based on the configuration that is already setup in the system. Using AI, Sales Rep can help in giving the best discounts to the customer by using all the available data which is outside the system.
Along with this, the algorithm can also refer to other deals for the same customer, and then provide in more discount to keep them interested in doing more business.

Sales Recommendations

Salesforce CPQ provides capabilities to give recommendations based on the products selected in the quote. This is done via code and is based on the existing data that has been setup in the system.
With Predictive AI, these recommendations can be done more pro-actively using knowledge about the client’s current business models and priorities. System can also use its knowledge about what the customer’s competitors are buying and can then help recommend appropriate product lines to stay up to date in the market.

Automated Approval Workflows

Salesforce CPQ provides Advanced approvals, which is a configurable setup. This helps in getting the deals approved by appropriate personnel based on some criteria. Combined with AI, this can further help in the approval process by automatically approving certain deals based on past experiences.

Upsell and Cross-sell Recommendations.

As AI algorithms can capture more data, they can stay updated with client’s current business model, their needs and then try selling more products suiting different business verticals with the same client. These recommendations can be automated and be used for proactive and more targeted advertising.

Guided Selling

This is another feature which is already inbuilt in Salesforce CPQ and is highly used by Sales Reps to help reach to the correct product by answering a pre-defined set of questions. As this is a configurable setup done in the system, there is a limit to the questions that can be set.
Using Generative AI, the questions can be made more dynamic rather than static. This can be done by using data around customer’s current business status and then asking appropriate questions.
The answers put in can then be used along with more customer data to present the most suitable option.

Natural Language Processing (NLP) for Quote Generation

This can be one of the most important features and use case of Generative AI in Salesforce CPQ.
For Quote creation, user needs to input certain values, like the dates and term of the quote, the products to be added, currency to be used etc. All this is a setup currently and requires an implementation team to set up based on client’s requirement.
With Gen AI capabilities around NLP, Sales Rep can create quotes using natural language, thus making the entire process more intuitive and efficient.


In conclusion, the advent of AI has changed the way businesses are running. If Predictive AI was the cake which dealt with all the huge volumes of data, Generative AI has been the cherry on the top and has started creating new content in natural language using all the data.
Salesforce CPQ as a platform is primarily used by companies to sell their products.
Using these in conjunction, businesses can leverage the power of machine learning to optimize their sales strategies, identify cross-selling and upselling opportunities, and ensure accurate and efficient quoting processes.


Author Details

Nimit Bedi

Nimit is a Salesforce Consultant working with the Enterprise Cloud Application Services (Salesforce) Unit at Infosys. He has total of 8+ years of industry experience, working on multiple sides of software development, understanding the technical side and the functional business needs, all leading him to his aim of becoming a Salesforce Solution Architect.

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