Google Analytics vs. IBM Watson Studio on Cloud Pak for Data

Google Analytics is particularly well suited for tracking and analyzing customer behavior on a grocery e-commerce platform. It provides a wealth of information about customer behavior, including what products are most popular, what pages are visited the most, and where customers are coming from. This information can help the platform optimize its website for better customer engagement and conversion rates. However, Google Analytics may not be the best tool for more advanced, granular analysis of customer behavior, such as tracking individual customer journeys or understanding customer motivations. In these cases, it may be more appropriate to use additional tools or solutions that provide deeper insights into customer behavior.

It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.

Incentivized

• Multiple reports to see website use and behavior
• Allows you to customize reports with days, weeks, months, and years
• You can build out a dashboard to easily view stats from multiple websites in one place
• You can share analytics reports via the dashboard, automatically emailed PDFs or in other formats

Incentivized

• Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
• SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
• Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
• Estimator validation lets data scientists test and prove different models.

Incentivized

• Data sampling is somewhat inaccurate on the free tier - this is addressed in premium but is expensive.
• Some of the UI is very similar in naming when presenting different data, some in-situ information might be useful.
• Gotchas around filtering and data validation.
• Implementation can be tricky, it can take a lot of time and expertise to get a full, accurate picture of your metrics.

Incentivized

• The cost is steep and so only companies with resources can afford it
• It will be nice to have Chinese versions so that Chinese engineers can also use it easily
• It takes a while to learn how to input different kinds of skin defects for detection

Incentivized

We will continue to use Google Analytics for several reasons. It is free, which is a huge selling point. It houses all of our ecommerce stores' data, and though it can't account for refunds or fraud orders, gives us and our clients directional, real time information on individual and group store performance.

Incentivized

because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)

Incentivized

Google Analytics provides a wealth of data, down to minute levels. That is it's greatest detriment: find the right information when you need it can be a cumbersome task. You are able to create shortcuts, however, so it can mitigate some of this problem. Google is continually refining Analytics, so I do not doubt there will be improvements

The UI flawlessly merges this offering by providing a neat, minimal, responsive interface

Incentivized

We all know Google is at top when it comes to availability. We have never faced any such instances where I can suggest otherwise. All you need is a Google account, a device and internet connection to use this super powerful tool for reporting and visualising your site data, traffic, events, etc. that too in real time.

From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected

Incentivized

This has been a catalyst for improving our site's traffic handling capabilities. We were able to identify exit% from our sites through it and we used recommendations to handle and implement the same in our sites. We have been increasing the usage of Google Analytics in our sites and never had any performance related issues if we used Analytics

Never had slow response even on our very busy network

Incentivized

The Google reps respond very quickly. However, sometimes they can overly call you to set up an apportionment. I'm very proficient and sometimes when I talk to reps, they give beginner tutorials and insights that are a waste of time. I wish Google would understand my level of expertise and assign me to a rep (long-term) that doesn't have to walk me through the basics.

Incentivized

I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path

Incentivized

The trainers on the job are very smart with solutions and very able in teaching

Incentivized

love the product and training they provide for businesses of all sizes. The following list of links will help you get started with Google Analytics from setup to understanding what data is being presented by Google Analytics.

1. How to Use Google Analytics for Beginners – Mahalo’s how-to guide for beginners.
2. A beginner’s guide to Google Analytics – A free eBook walking you through Google Analytics from setup to understanding what data is being presented.
3. Getting to Know Your Google Analytics Dashboard – The title says it all! This is a brief post with one goal: to introduce you to the Google Analytics dashboard.
4. Google Analytics for Beginners: How to Make the Most of Your Traffic Reports– This guide doesn’t cover setup, but it does a great job of helping you to better understand the data being presented.
5. Google Analytics Video Tutorial 1: Setup – A video presentation that walks you through Google Analytics setup.
6. Google Analytics Video Tutorial 2: Essential Stats – A video presentation that introduces you to some of the most important data being presented in Google Analytics.

The Platform is very handy and suggests further steps according my previous interests

Incentivized

I think my biggest take away from the Google Analytics implementation was that there needs to be a clear understanding of what you want to achieve and how you want to achieve it before you start. Originally the analytics were added to track visitors, but as we became more savvy with the product, we began adding more and more functionality, and defining guidelines as we went along. While not detrimental to our success, this lack of an overarching goal resulted in some minor setbacks in implementation and the collection of some messy data that is unusable.

It surprised us with unpredictable case of use and brand new points of view

Incentivized

I have not used Adobe Analytics as much, but I know they offer something called customer journey analytics, which we are evaluating now. I have used Semrush, and I find them much better than Google Analytics. I feel a fairly nontechnical person could learn Semrush in about a month. They also offer features like competitive analysis (on content, keywords, traffic, etc.), which is very useful. If you have to choose one among Semrush and Google Analytics, I would say go for Semrush.

Incentivized

The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.

Incentivized

Google Analytics is currently handling the reporting and tracking of near about 80 sites in our project. And I am not talking about the sites from different projects. They may have way more accounts than that. Never ever felt a performance issue from Google's end while generating or customising reports or tracking custom events or creating custom dimensions

It helped us in getting from 0 to DSX without getting lost

Incentivized

• It has helped us gain understanding of what is going on on our website.
• It has helped us determine areas that need fixing (i.e. pages with extremely high bounce rates may need to be redone).
• It has helped us understand our biggest avenues for bringing traffic to the website and business in general.
• It has helped guide our website redesign.

Incentivized

• Could instantly show data driven insights to drive 20% incremental revenue over existing results
• Still don't have a real use case for unstructured data like twitter feed
• Some of the insights around user actions have driven new projects to automate mundane tasks

Incentivized