Conga Advantage CPQ vs. IBM watsonx Orchestrate

It is well suited to providing quick pricing recommendations, allowing those who are quoting to get our agreements out efficiently. Where I find there may be some limitations is around the details that it uses to establish recommendations and the overrides. For example it would be nice to have a way to set overrides for those criteria like length of agreement, etc. and have it apply across the board

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For starters, most enterprise-grade organizations and Customers struggle to align their current IT estate and landscape with fast-moving, agile, AI-driven automation and development initiatives. All tooling, governance, structure, and frameworks available to support and facilitate the incorporation of this new but still cross-system technology layer are essential to minimize the risks of data leaks, unauthorized access, unbridled token consumption, and other issues. For some businesses and organizations with a handful of systems or a smaller footprint, the platform could be a bit too complex.

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• The perceived power strength is that it is supposed to contain CPQ, Contract Management, Document generation and template manipulation, and cash/invoice process all in one wrapped package.
• It was developed on the Force.com platform.
• They provide multiple releases of their product per year.

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• New and improved natural language processing yielding better results helps the assistants understand the intention behind the query.
• Preserves context of communication, allowing the customers to establish inquiries on the website and continue on the mobile app without having extra informational input.
• Intelligent conversations mean that complex paths that are branched based on the user's inputs allow for a much more natural flow of the conversation than fixed scripts.

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• Our number one complaint with Conga CPQ has been speed. In my experience, Conga CPQ is extremely slow, especially for large orders.
• In my opinion, the configuration methods of Conga CPQ are outdated and error-prone. One literally puts configurations into string-based custom settings, including the API field names. This often leads to deployment issues and run-time configuration errors.
• In my experience, Conga CPQ is everything but simple to develop. You need things like a 12-step pricing callback to support custom pricing.
• In my experience, Conga CPQ support is not responsive.
• When it comes time to lock in a renewal contract for Conga CPQ, in my experience, they delay engagement, so you are truly behind the 8 ball when it comes time to decide if you are going to continue with Conga CPQ.

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• I think that it needs to be able to integrate better with the knowledge catalogs. It currently provides a default database, which isn't quite large enough for enterprise use. We can connect that then to an external source, but it'd be nice if we could able just to instantiate one straight away.

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The rating is based on several things: 1) Ongoing support requirements being able to be addressed by cross training existing Salesforce administrators 2) Apttus superior corporate vision for the quote to cash space 3) Apttus execution of the corporate vision with automated agents (Max), and Artificial Intelligence/Machine Learning offerings to leverage the investment in Configure Price Quote 4) Apttus corporate health and investment in the product line

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Currently we are using to develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. Action flow and dialog flow we are currently in chatbot.

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Conga CPQ is a great tool but lacks good support and [a] very limited knowledge base which doesn't include day to day errors which users face, thus leading us to support and take more time in turn. Also cart performance can be improved drastically which will enhance the user experience as the user doesn't have to wait for the pricing.

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With the growing use of AI and chatbots, it's very easy to use, and the conversational language makes it easier than keyword searches in a document. The contextual language processing is impressive. It's easy to integrate into our internal portal. The use of this tool would depend on each company's security and data sensitivity.

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I have not heard of any issue

To develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. IBM Watson library anyone can easily learn and develop chatbots.

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Tier1/tier 2 support can only handle native functionality. Customizations have to be escalated to developers which aren’t included in the support program.

I go ahead and copy the people I directly worked with on implementation for assistance. I would rate them an 8 for support assistance.

We've rarely had to engage support, but they've always been prompt in responding and very attentive. Support experiences have been extremely positive (but we're mostly happy that we just don't have any cause to routinely need support in the first place!).

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We attended 5 hours worth of webinars early on.

We had to understand how objects worked to figure out how to structure our data.

I would have liked more in-depth training but it would have been an additional cost

Excellent course material.

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Be iterative. Take the opportunity to build a catalog based on how Apttus works well. Learn the tool yourself or use an SI. Take the time to build a configuration / pricing migration tool with X-Author for Excel or roll your own. Stick with OOTB Apttus as any customization will cost you every time a new version is released

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Overall the implementation was simple.

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We selected Apttus CPQ over SteelBrick due to the simplicity of SteelBrick's out of the box pricing and ability to customize quoted products. As a global organization with selling a highly configurable products, we felt the ability of Apttus to handle our requirements as standard functionalty rather than a customization was a material difference between the platforms.

Strong ITSM and HR workflow automation with governance, ServiceNow excels in IT/HR but lacks flexibility for cross-departmental use cases such as demand planning, finance close, or procurement analytics. Orchestrate supports a broader set of enterprise functions beyond IT service automation. So, watsonx is a better approach than any other available tool in the market as of now, based on the use cases I've encountered and my efforts to understand the essence of the service.

From past 3+ years I am using IBM Watson in our current project easily can implement and manage and monitor user how their using. Is there and update also just update dialog is just enough to change no need to touch any other templates. Multiple language will support, and action and dialog speak recognize chatbot we can create as per client requirement. Overall, as of now good experience with IBM Watson.

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• The ability to generate engineered configurations that is right by construction has reduced the cycle time of the customer engagement. The fact that we are able to guide the process and end up with a validated bill of material reduces the iterations with the customers.
• As long as the validations rules are correct the generated bill of material is accurate. We are now looking at using Apttus to perform quality checks in our product rules since the tool is able to test different configurations quickly and efficiently.
• Configuration that use to take weeks and consumed valuable engineering resources has been transformed to become a customer facing application that is simple enough for customer to self-service.

• As a very small team WxO give us more time back and handles manual tasks.
• WxO helps us reduce manual errors (and the time it takes to find and resolve.)
• WxO, as a task scheduler and reminder system, helps us not forget certain key events with time-dependent requirements.

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