HCL Unica vs. mParticle vs. Treasure AI

Extremely well integrated in the TelCos and Financial Services areas. Retail & Online Gaming are the next big sectors. Real Time capabilities via IBM Interact are starting to come to the fore as marketers start to understand the necessity for true reactive CRM. Additional functionality using IBM Distributed Marketing is also another very powerful area for the future, allowing regional marketers to fill out web based forms, which initiate and run flowcharts & email delivery automatically.

Do not integrate multiple analytics / customer messaging / download attribution SDKs into your mobile or web apps, duplicating data and risking a fragemented view of the customer. Instead integrate mParticle as a CDP, and configure the necessary integrations which will enable you to progress towards a world of the single-view of the customer. Also works great to import historical data into a newly onboarded/integrated tool.

Incentivized

Any time you need to process and store very large volumes of data at scale, Treasure Data will aways be at the forefront of my mind. Especially if the data being handled is constantly changing or evolving, rigid schemas just wont do. Treasure Data has the ability to adapt as your product needs change over time. Having the storage and processing flexibility is a huge win.

Incentivized

• Campaign treats a marketing campaign as a discrete entity that is made up of one or more flowcharts, which are in turn comprised of one or more processes.
• IBM Campaign performs actual data manipulation live.
• Users do not need to know SQL to design campaigns.

Incentivized

• Collect customer data from multiple sources.
• Integrated with wide breadth of vendors and verticals.
• Helps track unregistered user data into registered user data.

Incentivized

• 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.

Incentivized

• Not suitable to small industries even if they really want to use. It would be great to have a lighter version to let any company use in order to make more customers.
• It would really great to have support team available whenever having the issues / difficulties with in the tool itself. At least able to respond asap.

Incentivized

• UI for events for customers takes time to update, its unreliable.
• Hard to inspect the data once its inputted.
• Not possible to link data with other non-customer related data.

Incentivized

• Pricing is a bit of a black box. We are currently priced on split hour usage and some spikes come out of nowhere and leave us seeking answers (and sometimes finding unsatisfactory ones).
• Some jobs will fail, causing workflows to be interrupted due to a product change or a one-time product related issue. We usually contact Support in these cases, and while they are incredibly responsive and helpful, it would be great to have more proactive communication.
• Treasure's UI leaves us wanting more in terms of organization and controls, especially as we scale and grow the number of data sources, queries, and workflows.

Incentivized

I know Unica well and can make it do just about anything I need it to do. I love the abiity to call in custom code along the way for extremely complicated scenarios and optimum performance. Situations that would steer me to other applications are: If already a heavy SAS user with Enterprise Miner and/or Enterprise Guide I would seriously consider SAS CM; if already owning Teradata platform would seriously consider Teradata RM.

Incentivized

It's a great tool for beginners but not scalable to advance use cases. It's not it's a fault in our case, because any platform is as good as the data collected

Incentivized

Because treasure data is a great platform with a great support team behind, it's a scalable solution that deals well with huge amounts of data every day and has a huge catalog of integrations that can be easily use to download data from several platforms, like aws s3, redshift, google bigquery.

Incentivized

I think it is easy to use, if you don't have to do to complex selections.

If you are a data person, you will likely understand the product and how to use it well. We did find that some of our queries run into memory issues though. If you are a marketer and want to build easy audience segments, I am not sure how easy it will be for you. We are still working through this.

Incentivized

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

Incentivized

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.

Incentivized

I didn't use the Unica support since it is with IBM, only before.

They will go above and beyond and will file tickets If they don't have the answer. They are friendly, respectful, and punctual.

Incentivized

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.

Incentivized

I was not here when treasure data was implemented to our company.

Incentivized

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.

Incentivized

- We had to rebuild a part of the datamart afterwards to tighten up and simplify the selection process. But as it was too time consuming to rebuild all the existing campaigns, we no run campaigns on different versions of the datamart. - The response tracking of the campaigns never worked out well, it was impossible to implement a direct response where there is a link between the lead and the response in our operational process

Implementation was quick and our developers had very few issues with the SDK.

Incentivized

The contact history and the response history are so powerful. You can track whatever you want to help the call center to push relevant offers to our customer. In addition, predictive models can be built, with patience, in IBM Campaign. If you have some complaints from the call center about any campaigns, you can easily validate it into the contact or response history.

Incentivized

mParticle has a bigger catalog of services you can interface with and provides a more complete check for data integrity. It also allows you to use any analytics solution.

Incentivized

Both Tealium and Evergage are mostly focused on online sources. They don't have as easy or robust data model capability to ingest CRM, e-commerce, or offline data. Bluevenn has good identity resolution like TD, but the Unify data processes/model are not exposed to the customer to modify or develop data load workflows.

Incentivized

In abi we do have a lot of data coming every day, so treasure data always give us god solutions and options that would fix the problem.

Incentivized

• We’ve been able to send out Thousands of communications and generate over 1 billion touches per year because of the speed and flexibility of the tool.
• We’ve helped our marketing partners achieve or exceed some very lofty goals in the past two years because of the tool

Incentivized

• This might be less of an issue with mParticle, but often times we found ourselves troubleshooting discrepancies between what mParticle showed vs downstream analytics platforms, more so than troubleshooting the issue itself.

Incentivized

• When there are Treasure Data updates, there might be old functions that are deprecated or existing functions which no longer work as before --> this may have impact on existing workflows/queries
• As many developers are working on the same environment, the jobs are queued because there is a limited amount of computation cores available --> if we want to increase it, our client needs to pay for more cores
• As data are increasing, some workflows are too expensive and need to be rethought / made more efficient --> this means re-designing existing workflows and also requires constant support from Treasure Data which analyzes the queries and identifies points of improvement that allows client to pay less

Incentivized