Coremetrics / IBM Digital Analytics (discontinued) vs. Google Analytics vs. SAP Analytics Cloud

IBM analytics has continued to improve upon the days of being the original core metrics. After using the updated version for quite some time, it has been great at providing the needed analytics to measure ROI and goal performance for our quarterly KPI's. It has resulted in a great increase in web engagements although we are a midsize company, smaller outfits may not need such an expensive option.

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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.

>> Using SAC predictive analytics capabilities for inventory management in a Production line setup has helped generate Purchase Requisitions and Purchase Orders for raw or semi-finished goods without much head-banging into Demand management rules. It does it beautifully with seamless integration with HANA core MM and PP modules, along with BI integration. It has resulted in 30% greater warehouse storage capacity, thereby saving revenue from piled-up inventory and associated manpower costs. >> SAC sometimes shows latency in working out a large data set, thus giving a poor user experience compared to its competition. Also, it may occasionally show misinterpretations when embedding data from 3rd-party systems into the HANA core dataset.

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• IBM CXA comprises an acquisition called Tealeaf. This tool has deep heritage and this is evident in its present-day capabilities.
• The Universal Behaviour Exchange or UBX puts the concept of personalisation at the forefront. The ability to combine physical (analog) and digital transactions to create the complete picture of a customer journey, is a stand out benefit.
• The solution does not have to involve the purchase of software. IBM CXA can be sold as a service bundled with analytics as a service. This not only lowers the cost of ownership, it gets around one of the principal issues. Strong staff with design and analytical capability to drive the solution and deliver tangible benefits.
• The seamless integration of Watson AI services to help with the heavy lifiting. Watson reinforces the analytical focus this solution has and can learn to recognise situations specific to a company.

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• 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

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• It makes it easier yo analyse order and related records easily.
• We can easily maintain and track the performance of employees in organisation.
• Can easily track various aspects for the growth of an organisation thus allowing real time analysis and tracking of organisation's growth and performance.

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• The user interface is in Flash, which can be very frustrating and slow at times. Apparently, this is to be transitioned in a future release.
• Can only segment the last 93 days of data. Any historical segmentation beyond the 93 days must be run in Explore (which is credit based, and has its own limitations with the number of credits per month, based on the initial contract with IBM).
• Reports can only display 93 days of data at a given time for custom date ranges. There are pre-programmed date ranges setup with IBM during implementation (last week, last month, last quarter etc.), but are not flexible enough to answer more specific questions.
• Certain reports cannot have segments applied, making answering some simple questions a bit more tricky. For example, I can create a segment around mobile devices and apply it to the marketing channels report, but I can't create a marketing channel segment and apply it to the mobile reports.
• Built in API calls allows for nice report design and automation.

• 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.

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• Complexity in Data Modeling
• SAC supports various data sources, but improvements in the ease of connecting to and integrating with certain data repositories, especially non-SAP databases, would enhance the platform's versatility and integration capabilities.
• An offline mode for SAC could be valuable for users who need to access and analyze data without an internet connection. Additionally, optimizing performance for large datasets and complex visualizations would contribute to a smoother user experience.

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IBM Digital Analytics is a great solution for our clients and I believe they offer the best solution for the retail space. We have access to IBM support via email or live chat and they can answer many of the reporting questions that come up. IBM is receptive to our feedback of the product so I am confident they will continue making improvements

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.

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We are planning to review the licensing as we have issues with SAC dealing with huge datasets. Analytics area is good for import models but when we have live connections in place that's when we have issue with SAC dealing with huge datasets in live be it BW or be it HANA models in the backend.

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Very easy to implement and use.

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

I landed on a 7 out of 10 for a few key reasons. The tool is flexible in the sense that we are using very very very (very) little off the shelf solutions and customizing to our needs. Users enjoy having the customized data actions, key variance calculations, and easy to use headcount/salary planning in the same tool. One downside is that users are hard to please when they are used to excel. SAP Analytics Cloud simply is not excel, and the flexibility of excel in a crunch is not there.

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Never had any issues

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.

I would rate SAP Analytics Cloud an 8 out of 10 for scalability. It offers a flexible, cloud-based architecture that supports expansion across departments and geographies. The platform adapts well to growing data volumes and user needs, making it a strong choice for organizations looking to scale analytics capabilities efficiently.

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As reports are templated, the system is pretty quick. Sometimes you have to wait a bit for a report to render. Or you might have to re-load the page. But there is no real issue here and the system is on par with other similar systems.

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

I would rate SAP Analytics Cloud’s performance an 8 out of 10. Pages generally load quickly, and reports run within a reasonable time frame, even with complex datasets. Integration with other systems is smooth and doesn’t noticeably affect performance. Overall, it’s a responsive and efficient tool for business analytics. But

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Overall, the level of support is very good and I would say it is a strong asset of the solution. However, you can sometimes feel that there is a difference of level among the support team.

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.

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Since the implementation stage, the support team has been very helpful and assisting. Even in the later stages, the tech team had quite a rapid response. In general, SAP has provided us with great customer support, let it be for a specific product of SAP or for integration of different modules.

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Good videos and reference material available in SAP Portal.

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Online training is really great. One of the best assets that they have. Lots of great videos, pop quizzes at the end of each module. Fantastic. Other tools have similar features, but not as good.

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.

In hindsight, it would have been easier to have someone there in person. Questions were answered, but with 11 participants, it got a bit chaotic online

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See previous comment: reading and understanding the encyclopedic implementation guide is a must.

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.

SAC is a simple solution ad it works fine when connecting it to other SAP tools. On the other hand, connecting it to third party solutions brings difficulties when there's no previous design and the objetives are not clear. It is really important to integrate Business users from the start to provide with valuable business insights

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Much of the work we did in IBM Digital Analytics could have been answered through Google Analytics, a much simpler, agile and FREE solution set. Not mention, given the vast number of Google Analytics USERS, free and actionable support is simply a click away ... this compared to IBM Digital Analytics fractured and often absent support service.

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.

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SAP Analytics Cloud and Power BI are both tools that help businesses understand their data, but they have some differences. SAC, made by SAP, works well if your company already uses other SAP products. It's in the cloud, easy to use, and has features for analyzing data, getting insights, and planning for the future. Power BI, made by Microsoft, can be used in the cloud or on your own computers. It fits well with Microsoft tools, is easy to use, and can do advanced data analysis. SAC has built-in planning tools, while Power BI needs extra tools for detailed planning

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unit pricing

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This solution can support large amount of data and transaction. The way that user management features are built, it shows it is meant for large organizations.

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

Is good for use across multiple locations. It allows users to access data and reports from anywhere, regardless of their location. Can consolidate data from various sources, including different SAP systems and external sources, which facilitates cross-location analysis. SAC enables access to data and models from SAP Datasphere to create new stories. Detailed permissions can be defined for cross-departmental use.

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very simple

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• We spend too much time trying to work around bugs on the new UI.
• We spend too much time trying to figure out how to make certain segments work because support and the knowledge center are lackluster.
• Our sales rep is very unresponsive and leaves us searching for a lot of answers on our own, including what other products we may benefit from that IBM offers.

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• 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.

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• Many manual data manipulations and exports in Excel have been replaced by the tool, providing management with improved insight into the amount of time spent at each stage of an invoice's lifetime, allowing bottlenecks to be discovered.
• We now have more insight into the data, and people with little technical experience can easily build stories.

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