I have been in the CPQ space for the last 20 years. Starting in product development, I was involved in developing two market leading configuration engines. One at Trilogy, a CPQ pioneer, and the other was at Siebel. They are very powerful engines and are still in use to this day.
After developing the platforms, I then transitioned to Solution Architect, and designed and implemented numerous complex CPQ solutions for a variety of large companies. Over the years I learned that enterprise CPQ problems are very complicated, vary greatly from company to company, and there is no one size fits all solution to it. When I started Veloce, my own CPQ company, I knew from day one I needed to design and implement a CPQ platform that is very powerful and customizable to solve various CPQ problems. It also needs a flexible UI and lightning fast performance to ensure high user adoption.
We started with the CPQ engines, and we built two.
We built a powerful, highly performance and customizable configuration engine. We took a completely different approach than most configuration engines in the market. The engine is purely mathematics based. All rules are in the form of logical expressions. Anything that can be modeled mathematically, we can do it in our engine. This avoids limitations in most configuration engines, where they only support certain rules. At the same time, we know there are some rules that are procedure based and can’t be expressed by a logical expression. For example, with the available configuration engines, you can’t write any logical expression to determine if an integer is prime, you have to write a procedure to determine if an integer is prime or not. So we introduced custom constraints to allow you to encode any kind of procedural logic in the configuration rule. Our configuration engine is highly customizable and it has a lot of mechanisms built in to allow you to customize it to meet your requirements.
Then we developed a pricing engine. Pricing is quite different from configuration. We wanted to separate the pricing logic from configuration logic for easy maintenance and performance. Our pricing engine has a very flexible pricing model and is highly customizable too. You can create your own pricing procedure to define how you are going to calculate the price. It supports high efficiency pricing rules to enable you to do different pricing calculations.
After we developed two engines, we started to put the CPQ solution together. But, we found that the approval and doc gen engines available in the market didn’t match the robustness that we needed, so we built our own. Now, with all engines in place, we designed and implemented a quoting process on the Salesforce platform, giving us an end-to-end CPQ solution.
Oftentimes CPQ projects fail because they’re too difficult for the sales team to use, resulting in low or even zero adoption. We found that companies want a user experience that has been configured to meet their own business process. However, customers often have to change their business process to fit the out of box UX. We realized that we needed to deliver an experience that supported the unique requirements of each client, so we built a UI framework for our CPQ solution to enable each customer to have a different UX. So far each of our customers has their own unique UX.
We knew we had to take a completely different approach to implement the CPQ solution for our customers. Instead of trying to force them to adjust their process so it could fit into our tool, we designed a flexible tool that could be adjusted to support their process.
Before building any solution for our customers, we design high fidelity mockups to reflect the customer’s business process. We then verify these UI mockups with the customers. Once signed-off, we build and deliver that exact experience, and there are not any surprises. After we finish the project, the customers get a CPQ solution that reflects how they run their business. It’s familiar, and the teams truly enjoy using it.
I read a blog post recently complaining that Configure, Price, Quote (CPQ) space is stagnant and lacks innovation. I completely disagree with that.
Beware a common sales tactic of advising you to deprioritize more complex use cases for phase two deployment. We hear stories from customers that have been told by a CPQ vendor that you should solve simple problems first and leave complex use cases for later.
When evaluating CPQ solutions, you may hear about constraint-based vs. rule-based configuration engines. This post will help make sense of the pros and cons of both. Veloce CPQ is exceptional in that it makes use of both constraint-based versus rule-based technologies. Read on to see why this is a benefit.
Nucleus Research report highlighting results of increased revenue and reduced operating costs achieved by companies in Telecommunications, Financial Services, and Health Care sectors after deploying Veloce CPQ
Supercharge your Salesforce CPQ with Veloce to easily manage your most complex use cases with incredible performance.