Coremetrics / IBM Digital Analytics (discontinued)
Score 9.1 out of 10
N/A
Based on the former Coremetrics, IBM Digital Analytics is a discontinued analytics product. IBM acquired Coremetrics in 2010, and re-branded the platform to the IBM Digital Marketing Optimization Solution. Product support was ultimately provided by Acoustic, but the product is not a part of the company's plans going forward.
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Treasure AI
Score 9.0 out of 10
Mid-Size Companies (51-1,000 employees)
Treasure AI is an enterprise customer data platform (CDP) that reclaims customer-centricity in the age of the digital customer. It does this by connecting all data and uniting teams and systems into one customer data platform to power purposeful engagements.
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Pricing
Coremetrics / IBM Digital Analytics (discontinued)
Treasure AI
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Coremetrics / IBM Digital Analytics (discontinued)
Treasure AI
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Coremetrics / IBM Digital Analytics (discontinued)
Treasure AI
Best Alternatives
Coremetrics / IBM Digital Analytics (discontinued)
Coremetrics / IBM Digital Analytics (discontinued)
Treasure AI
Likelihood to Recommend
Discontinued Products
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.
Treasure Data is well suited to integrating multiple data sources, including online and digital sources. It is also well suited to trigger audience activations to known customers based on their online activity, integrating 3rd party data, and activating target audiences to ad platforms.
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.
CDP provides a unified view of data from all touchpoints in the customer journey until a single customer uses the service. This feature is very helpful in making service decisions and direction.
It provides a variety of extensions to bring your data together in one place and helps you do this easily.
Kits provided by Treasure Box provide basic but helpful methods for further development of services.
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.
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
I do think that we definitely will be renewing. We are putting major resources, time, and effort into Treasure Data becoming an extension of our organization, in many ways. We are working toward complete synergies with this product and leadership is very excited about the direction we are heading to be completely customer-centric.
It's a easy platform to use and give the user detailed logs about what is going on in the workflows, so someone that do not have a lot of experience can start to work with it. And also the master segment usability is awesome, as we can filter a lot of data the way we want.
As treasure data has a 24 hours support, every time we has big issues that impacts the zones, we do have immediatly support from the treasure data team, so I would say that we do not have any issues with availability
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.
Since treasure data has started having a huge amount of data, sometimes we do have problems with the workflows logs because we generate a lot of then. But with integrations I have not to complain, its really easy to integrate with other platforms.
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 technical team has a good hold on the nuances of the data related to our organization. I have found the online technical support on their site quite responsive including the L1 support. In cases where the L1 team isn't able to resolve, I have found they are prompt in getting the product team's input to get a quick resolution.
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.
I wasnt here at the training in the start, but I had a few training with treasure data for a few functionalities, and they provided me god explanations and great documentations, eve if the project were in beta.
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.
We chose Treasure Data for the supreme customer service and lack of hidden costs. We don't need to manage any infrastructure or scale anything to meet customer demand. Treasure Data handles everything and makes it easy for us to integrate and focus on the tasks at hand. There may be cheaper options but we do not regret our decision to go with Treasure Data one bit.
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.
We have built and supported our source of truth data tables using Treasure. This forms the foundation of our decision making.
Most of our Tableau data sources are created using a Treasure Data export which is executed by workflows on a daily basis which allows us to have visibility into day to day performance and communicate them to a wide variety of roles.
We load custom data into our Salesforce instance which allows us to trigger certain workflows and build accountability - i.e. a "Sale" will only count once a certain product driven event occurs which comes from data we pipe into Treasure and then into Salesforce.