Coremetrics / IBM Digital Analytics (discontinued) vs. Google Optimize

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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It is a little too limited for a full stack experimentation programme. Many times we required development support or tech advise but we were simply unable to get this due to it being google. This was a big problem for us. However it is quite good if you were looking to get started in experimentation and didn’t have the budgets for a wider tool

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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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• Easy to follow set up procedures. Once I walk a client through the process, it's effortless for them to emulate on subsequent tests.
• Lots of geo and user attribute customization features to be able to drill down into specific targeted audiences — all based on the power of Google's immense data system.
• Google Optimize is the logical choice for many people to start with since most are already familiar with and using GA.

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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.

• Only works for browsers, not for the apps testing.
• Missing possibility to test complicated features.
• Audience division in groups is not always accurate.

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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

Very easy to implement and use.

Google has always been known to make easy-to-use products. The Google Optimize interface is intuitive and easy to follow for anyone.

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Never had any issues

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.

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.

Google has well-documented resources and unlimited use cases that can be found online. Plus, their support is always helpful and available.

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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.

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

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.

Google Optimize being part of the Google stack makes it great in reporting and analysis. Wish Google would add more features like dynamic tests, multi funnel tests, conversion calculator based on the total number of traffic of the page being tested instead of using the websites total traffic. Should integrate form analysis, heatmap, and page analytics.

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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.

• 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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• We were able to increase our main KPI for conversions by almost 50% by testing button copy.
• We were able to increase secondary KPIs for conversions by almost 30% by testing form design.

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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