What is our primary use case?
I use out-of-the-box objects like price list item and price list to create a product and show it in the catalog, such as category, category hierarchy, and product hierarchy, while using attributes for any product features. I show or hide those attributes using constraint rules, and for any defaulting, I use product attribute rules, while approvals are used for approval discounts, and they create quotations for negotiations. I have the order object for the orders as well.
My main use case for Conga CPQ is digital E-commerce like Amazon and Flipkart, where I have something like PowerShop, a Hitachi Energy client. In PowerShop, they usually sell all electronic-related products, and users will log into that Angular framework PowerShop UI to select products, add them to the cart, and place orders for quotations, which I achieved all by using Conga CPQ.
How has it helped my organization?
Conga CPQ has positively impacted my organization by increasing more revenue through client satisfaction.
It has improved the quote-to-order revenue process accurately and generated more revenue by providing a rich user interface.
What is most valuable?
Conga CPQ offers the best features, particularly pricing, allowing me to achieve complex pricing with ease, such as using the totaling callback and base price callback.
When I mention callback-based pricing, it helps my team because initially, if I want to give a price to a product, I use the price list item with only one price possible, but using Conga CPQ allows me to change the price based on different business scenarios. I can use out-of-the-box price rules, and if customizations are needed for complex pricing, such as setting different prices for users or business units, I achieve this using the base price and totaling callback. The base price applies to each single product price, and totaling calculates the tax amount. For example, if the total cart amount is 20 lakhs, I can calculate the required tax, and I can do all of this in the totaling.
What needs improvement?
Conga CPQ could be improved as it has recently launched Conga RLP, a Revenue Lifecycle Platform, to enhance performance. However, I am currently facing many difficulties with data synchronization, and it has several loopholes not working as expected in Turbo, such as validation callbacks working fine in Turbo but failing in RLP. I have encountered many issues recently and have raised these to the product team.
Regarding the needed improvements for RLP, data sync is the first issue, especially incremental sync and full sync. When I create a new field, I must perform a full sync, which takes a lot of time. The initial org setup also consumes time, and tracing failed syncs for related records is difficult. Furthermore, these validation messages, error messages, and warning messages that compare old and new JSON values, along with cascading from parent to child, even when blank, have a lot of issues. There are also many discrepancies in approvals, with backend queries returning one value and displaying a different value in the UI.
Currently, Conga CPQ is performing well. If Conga RLP can expedite its processes and resolve all open related bugs, as well as increase the product and engineering team size, it will benefit many clients, allowing them to switch from Turbo to RLP with fewer issues. In RLP, increasing the team solving product bugs would lead to faster pricing and overall improvements.
For how long have I used the solution?
I have been using Conga CPQ for the past four years.
What do I think about the stability of the solution?
In my experience, Conga CPQ is stable.
What do I think about the scalability of the solution?
Regarding Conga CPQ's scalability, it is good since I can adapt to more clients and encourage them to switch to Conga CPQ for better user experience and quick quote-to-order placements, enabling them to expedite the ordering process. By using Conga CPQ or Conga RLP, orders and quotes can be placed more rapidly, decreasing process times.
How are customer service and support?
Conga CPQ's customer support is good, as they prioritize issues based on urgency, so if there is a P0 issue, they handle it quickly, and I receive good and prompt responses with great resolution.
Which solution did I use previously and why did I switch?
I have not used a different solution before Conga CPQ; I have been using Conga CPQ since I joined the project.
Before choosing Conga CPQ, they evaluated Salesforce CPQ, but it does not support complex pricing and approvals. The out-of-the-box features of Salesforce CPQ require extensive customization, whereas Conga CPQ offers many out-of-the-box features, requiring much less customization.
What's my experience with pricing, setup cost, and licensing?
I have experience with pricing, setup cost, and licensing, having worked with out-of-the-box price rules, price dimensions, and price rule sets. I have also dealt with base price callbacks and totaling callbacks and set up list prices and base prices on the price list item. I have debugged issues related to net prices, such as understanding why a specific net unit price is displayed. I possess considerable knowledge in pricing, and only Conga CPQ can achieve complex pricing, a capability other CPQs such as Salesforce CPQ lack.
What other advice do I have?
I would rate Conga CPQ an eight out of ten.
I chose eight out of ten for Conga CPQ because, as I mentioned, I can handle complex pricing and approvals effectively. However, the two points deducted are due to new issues arising since they moved to RLP. As it was recently launched two years ago, it requires more improvement, and clients expect quicker resolutions and more new features.
Concerning Conga CPQ's AI capabilities, my organization currently uses GitHub Copilot in my project, with the code base repository having access to Copilot. I also have a notebook LLM for Conga RLP, providing accurate results, saving my time by allowing me to ask or prompt it for precise inquiries.
Regarding Conga CPQ's AI capabilities and the accuracy and reliability of output, I find it accurate since I have Copilot and notebook tools. If a Conga product has an AI feature capable of accessing the repository and offering the same results for code optimization and analysis, it can save time in both development and debugging. The notebook LLM also provides accurate results, and if the product team could develop something similar, it would enhance accuracy and expedite delivery.
In my organization, many projects are using Conga CPQ, usually working through these E-commerce websites to build the E-commerce and for shopping.
Initially, I had two or three clients only, but once Hitachi Energy became successful, I acquired more clients such as Roche and some others that I am not directly working on.
I advise others looking into using Conga CPQ to consider it if their business has complex pricing and approvals, as other CPQs may not achieve these efficiently. If they want improved user experience and faster cart loading performance, then they should definitely switch to Conga CPQ.
My company has a relationship with Conga, as I take help from them regarding this product; however, I am not aware of the exact nature of the relationship.
My overall rating for this review is eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other