IBM Machine Learning for z/OS vs. Profound

IBM Watson Machine Learning is an AI-based scalable self-learning model for any type of business. It can be used to help any company automate repetitive tasks, predict future trends, and make data-driven decisions. I used it to predict stock prices based on certain variables. It works well, cost me nothing, and gives me the ability to create my own AI-based models that I can use for any purpose.

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Profound is a great AEO platform, with so much information and insights available around what competitors are doing and what prospects are searching for, and how we are cited. The down side is also just too much information and without enough resources or a full time person using the platform, it's difficult to know what to prioritize

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Good machine learning tool
• Easy integration

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Proper usage of REST API documentation is missing.
• Not localization friendly, cannot support regional or local language documents.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Profound tracks A LOT of data, which is great, but it can also be overwhelming to look at/digest all the raw data without their internal measurements.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

IBM had a hard time providing business level support. There were a lot of data scientists and technology experts but rarely a simple business person shows up. Also the way IBM operates IBM Consulting has competing priorities as compared to IBM Technology. This has resulted in a lot of confusion at the client's end.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

We have been using Microsoft Azure as a machine learning tool. But the challenges remain the same. These are all tools that you need a robust analysis before a decision on the tool. Unfortunately, the technology company cannot make that determination due to lack of core business understanding. Without that the project is doomed.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Semrush is much more mature for SEO but lacks the focus needed to be effective for AEO. Because Profound is build for AEO from the ground up, all of the associated features are optimized to be useful for AEO (for example focusing purely on topic visibility). SEMRush's AI Search tools feel a bit muddled in the system they have set up for SEO

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Create secure business environment.
• Save upto 90% of manual labor.
• Improve my sales and marketing ROI.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info