Coremetrics / IBM Digital Analytics (discontinued) vs. Jeeva AI

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.

Incentivized

If anyone is looking to pile up the list of email lists to send out e-blast or cold messages, I would highly recommend Jeeva AI. However, if anyone needs more of organic work, I would recommend using Jeeva AI to collect contact information, but do the work manually.

• 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.

Incentivized

• Finding specific leads according to descriptions provided
• Allowing customers to experience Jeeva AI by offering free credits
• Following up with leads

• 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.

• You run out of credits very fast, they charge per email sent. The credits should be for lead generation not emailing.
• Incorporate delivery results, bounce results, mailer unfound results, etc... We can not see any of those metrics.
• Incorporate a text sequence campaign as well. To be one stop shop for contacting all ways.

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.

Jeeva is composed of individual products / features that form a robust, automation-based, outbound system when combined. Parts of the tech stack within Jeeva itself – can be difficult to work with independently. Some of what the individual products provided makes you ask why? Why was this individual product / feature implemented

Incentivized

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.

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.

Jeeva AI is less straightforward than Sales Nav. It seems that it is trying to be everything that Sales Nav is, but not quite achieving it yet. The customer service for Linkedin is far superior to Jeeva's. Jeeva's team refused to give me a refund on my first month's subscription despite their refund policy clearly stating that I was entitled to it. This has never happened before with Linkedin Sales Nav.

Incentivized

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.

Incentivized

• We just started and was great for lead generation
• Those leads we can manually email them or call them
• Our sequence campaigns are barely 1 email in, looking forward to see if we get any traction on the last 2 sequences