Conga Advantage CPQ vs. Spotfire

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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A high level of data integration is available here it supports various data sources and so on. Collaborating features allow users to give access to the dashboard and merge data analytics with other team members. It can meet the demands of both small and large size business enterprises. A customized dashboard and reports are provided to meet the specific needs and get support of extensibility through APIs and customized scripts.

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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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• It has the best coding integration (python, R) of any BI product
• The ability to work with very large datasets (10 mil+) is better than competitors
• Export options are more complete and have better functionality
• The data canvas is the best tool to join and transform data vs. competitors

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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• In my opinion, the configuration methods of Conga CPQ are outdated and error-prone.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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• The donut chart is I guess a powerful illustrations but I hope it should be done quite simple in Spotfire. But in Spotfire there are lots of steps involve just to build a simple donut chart.
• Table calculation (like Row or Column Differences) should be made simple or there should be drag and drop function for Table Calculation. No need for scripting.
• Information Link should be changed. If new columns are added to the table just refreshing the data should be able to capture the new column. No need extra step to add column

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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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-Easy to distribute information throughout the enterprise using the webplayer. -Ad hoc analysis is possible throughout the enterprise using business author in the webplayer or the thick client. -Low level of support needed by IT team. Access interfaces with LDAP and numerous other authentication methods. -Possible to continually extend the platform with JavaScript, R scripts, HTML, and custom extensions. -Ability to standardize data logic through pre-built queries in the Information Designer. Everyone in the enterprise is using the same logic -Tagging and bookmarking data allows for quick sharing of insights. -Integration with numerous data sources... flat files, data bases, big data, images, etc. -Much improved mapping capability. Also includes the ability to apply data points over any image.

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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Basic tasks like generating meaningful information from large sets of raw data are very easy. The next step of linking to multiple live data sources and linking those tables and performing on the fly analysis of the imported data is understandably more difficult.

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I have not heard of any issue

Even though, it's a rather stable and predictable tool that's also fast, it does have some bugs and inconsistencies that shut down the system. Depending on the details, it could happen as often as 2-3 times a week, especially during the development period.

Generally, the Spotfire client runs with very good performance. There are factors that could affect performance, but normally has to do with loading large analysis files from the library if the database is located some distance away and your global network is not optimal. Once you have your data table(s) loaded in the client application, usually the application is quite good performance-wise.

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.

Support has been helpful with issues. Support seems to know their product and its capabilities. It would also seem that they have a good sense of the context of the problem; where we are going with this issue and what we want the end outcome to be.

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The instructor was very in depth and provided relevant training to business users on how to create visualizations. They showed us how to alter settings and filter views, and provided resources for future questions. However, the instructor failed to cover data sources, connecting to data, etc. While it was helpful to see how users can use the data to create reports, they failed to properly instruct us on how to get the dataset in to begin with. We are still trying to figure out connections to certain databases (we have multiple different types).

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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

The online training is good, provides a good base of knowledge. The video demonstrations were well-done and easy to follow along. Provided exercises are good as well, but I think there could be more challenging exercises. The training has also gone up in price significantly in the last 3 years (in USD, which hurts us even more in Canada), and I'm not sure it is worth the money it now costs (it is worth how much it cost 3 years ago, but not double that.)

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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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The original architecture I created for our implementation had only a particular set of internal business units in mind. Over the years, Spotfire gained in popularity in our company and was being utilized across many more business units. Soon, its usage went beyond what the original architectural implementation could provide. We've since learned about how the product is used by the different teams and are currently in the middle of rolling out a new architecture. I suggest:

• Have clearly defined service level agreements with all the teams that will use Spotfire. Your business intelligence group might only need availability during normal working hours, but your production support group might need 24/7 availability. If these groups share one Spotfire server, maintenance of that server might be a problem.
• Know the different types of data you will be working with. One group might be working with "public" data while another group might work with sensitive data. Design your Library accordingly and with the proper permissions.
• Know the roles of the users of Spotfire. Will there only be a small set of report writers or does everyone have write access to the Library?
• ALWAYS add a timestamp prompt to your reports. You don't want multiple users opening a report that will try and pull down millions of rows of data to their local workstations. Another option, of course, is to just hard code a time range in the backing database view (i.e. where activity_date >= sysdate - 90, etc.), but I'd rather educate/train the user base if possible.
• This probably goes without saying, but if possible, point to a separate reporting database or a logical standby database. You don't want the company pounding on your primaries and take down your order system.

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.

Spotfire is significantly ahead of both products from an ETL and data ingestion capability. Spotfire also has substantially better visualizations than Power BI, and although the native visualizations aren't as flexible in Tableau, Spotfire enables users to create completely custom javascript visaualizations, which neither Tableau or Power BI has. Tableau and Power BI are likely only superior to Spotfire with respect to embedded analysis on a website.

In an enterprise architecture, if Spotfire Advanced Data services(Composite Studio),data marts can be managed optimally and scalability in a data perspective is great. As the web player/consumer is directly proportional to RAM, if the enterprise can handle RAM requirement accomodating fail over mechanisms appropraitely, it is definitely scalable,

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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.

• It is costly, so not suitable for small scale implementations.
• Dashboards are as good as the developer, so need experience to get most out of it
• You need to be on Spotfire 11 at least to implement out of the box visualizations
• Integration with Python and R is a game changer, it comes very handy to onboard data scientists without much hassle
• performance is exceptionally well.
• Secure

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