IBM Watson Studio Reviews

I am participating in a project using Watson Studio for developing a chatbot for the banking industry.

We determined that Watson Studio is the most complete tool for AI projects.

It is used to enhance user experience in an e-commerce setting. By leveraging data on user clicks, browsing behavior, and past interactions with the platform, we can create models that enable personalized product recommendations. These models can identify products that align with the customer's interests and preferences, thereby improving the chances of suggesting items that are highly relevant to the individual's needs.

The primary advantage lies in the ability of AI to create value across the entire spectrum of a company's operations. The ultimate goal of employing AI is to generate value, support business growth, and identify opportunities for product enhancements and increased sales. It creates fresh sales opportunities and contributes to revenue growth. The benefits extend to discovering uncharted customer interests and needs, often hidden from plain view, which can lead to the introduction of new products and expand market reach.

The solution's interface is very slow at times. The interface of the product needs improvement.

I wouldn't like to see any improvements in the future since it is an already good product in the present.

I have been using IBM Watson Studio for two years. I am an end user of the product.

My primary use is to create a forecasting model for sales. I am doing automation from a supply chain point of view.

The most valuable feature is the page search, where I can have it visit my competitor's website and search through all of their promotions and offerings.

The SPSS Modeler components are all built-in, which is useful.

The notebooks are really helpful for data science.

It has a lot of data connectors, which is extremely helpful.

I use IBM Watson Studio to analyze personal resumes. In general, we use the machine to analyze resumes.

With the solution, it is easy to create a machine-learning model. The solution's UI is helpful since we had to work on Microsoft Excel or a CSV file earlier.

It was used for some basic purposes because all I did was use Jupyter notebooks to run codes on the Snowflake environment. This was done by me at my previous job. I had just started using Jupyter notebooks to run Python codes on Snowflake data warehouses.

I was really more on the engineering side of things. The data scientists built certain models around it. So that, I guess, was a very big improvement.

We mainly use it for our entire transformation logic. Everything that is in there, we store and process it in a similar fashion. We have globally rolled it out.

We use this product for every capability we have. It has greatly improved the performance because it is standardized across the company. Also, it will help us moving forward.

The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people. This is valuable for us. Also, how it integrates with the rest of the stacks, because we use many of the other products, and for that we find it useful.

We are doing the cloud part of the IBM Watson Studio. The customer needed a marketing analytics solution. IBM Watson Studio is a very comprehensive suite of marketing solutions including AI and predictive analytics.

IBM Watson Studio consistently automates across channels. When you're trying to build an end-to-end digital platform, it integrates consistently across your digital channel whether you're going through emails or shopping charts. That all is integrated into your call center. You use it mostly when you want to break into your communication channels your customer interactions. That's when it's actually really good. You don't have to bring many pools together to get your solution. You can have your emails, your leave management, hotspot, or your social media. You can have analytics built into that little eco-system that IBM Watson Studio creates.