Treasure Data
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Treasure Data
Overview
What is Treasure Data?
Treasure Data is an enterprise customer data platform (CDP) that powers the entire business to reclaim 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...
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- Setup fee optionalOptional
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- Free Trial
- Free/Freemium Version
- Premium Consulting / Integration Services
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What is a Customer Data Platform (CDP)? [The Ultimate Guide]
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Product Details
- About
- Integrations
- Competitors
- Tech Details
- Downloadables
- FAQs
What is Treasure Data?
Treasure Data is an enterprise customer data platform (CDP) that powers the entire business to reclaim 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 that drive value and protect privacy for every customer, every time.
According to the vendor, Treasure Data serves customers globally across a broad base of industries that utilize it for personalization at scale:
• 170+ Pre-built connectors to collect data and activate profiles
• 2M+ Events collected every second
• 10B+M Profiles activated every month
• 130T Records managed
• 1M Presto queries run daily
• 30T+ Rows of data processed daily
• 99.99% Uptime
Treasure Data Screenshots
Treasure Data Videos
Webinar: What is a Customer Data Platform?
Watch How a Customer Data Platform Achieves Over 800% Marketing ROI
Watch Webinar: Demystifying Customer Data Platforms, with Winterberry Group
Treasure Data Integrations
- Adobe Marketo Engage
- Twilio Segment
- Mixpanel
- Google Analytics
- AppsFlyer
- Adjust by AppLovin
- Amplitude Analytics
- Chartio (discontinued)
- Tableau Desktop
- Tableau Server
- Looker
- Domo
- Adobe Analytics
- Heap
- Apache Hadoop
- Amazon Redshift
- data.ai
- Microsoft Power BI
- Tableau Online
- Pentaho
- Metric Insights
- Microsoft Office 2016 (discontinued)
- Microsoft Azure
- Google Cloud Storage
- Google Drive
- Intercom
- Zendesk Support Suite
- Elasticsearch
- MongoDB
- Google BigQuery
- Microsoft SQL Server
- PostgreSQL
- Snowflake
- MySQL
- MariaDB Platform
- Mirantis Kubernetes Engine
- Heroku Platform
- Stripe
- Mailchimp
- Salesforce Marketing Cloud Email Studio
- Pardot
- HubSpot Marketing Hub
- NetSuite ERP
- Meta for Business
- Sizmek Ad Suite
- AdRoll
- LiveRamp
- Datorama
- Twitter Ads
- Google Tag Manager
- Branch
- Amazon Kinesis
- Unity
- iOS
- Android
- Unreal Engine
- Oracle CX Marketing
- TUNE
- Google Marketing Platform
- Oracle Responsys
- part of Oracle CX Marketing
- salesforce sales cloud
- kafka
- hive mall
- jupyter
- pandas
- R
- mLab
- fluentd
- JDBC
- Luigi
- Python
- Rest API
- informatica
- ruby
- eyeota
- instagram Ads
- xbee
- MQTT
- RaspberryPi
- Serial Devices
- CSV
- FTP
- Webhooks
- mysql workbench
- razorSQL
- SQuirreL SQL
Treasure Data Competitors
Treasure Data Technical Details
Operating Systems | Unspecified |
---|---|
Mobile Application | No |
Supported Countries | global |
Supported Languages | English, Japanese |
Treasure Data Downloadables
Frequently Asked Questions
Reviewers rate Support Rating highest, with a score of 8.2.
The most common users of Treasure Data are from Mid-sized Companies (51-1,000 employees).
Treasure Data Customer Size Distribution
Consumers | 0% |
---|---|
Small Businesses (1-50 employees) | 10% |
Mid-Size Companies (51-500 employees) | 50% |
Enterprises (more than 500 employees) | 40% |
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Reviews and Ratings
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August 18, 2021
I like to use treasure data, it has more pros than cons.
Treasure Data is being used for data capture for almost every country in the world. It helps in data capture and availability.
- It helps a lot on data capture and availability.
- Helps on data visualization for all the marketers in the world.
- It is pretty fast working with big data.
- I think maybe the structure, like its not possible to create tables with specific fields.
- Positive on storing and showing data insights for the marketers.
I think it does, I know that a lot of marketers use our data in Treasure Data to make decisions.
- Creating dashboards, in treasure insights.
I haven't used other products, just a few features from Treasure Data, like treasure insights.
Treasure data is used to load and treat it to disponibilize to the final user
5
To work with treasure data at maximum potential, you need sql skills.
- Data availability
- God support, answers pretty quickly
- Scalable platform, supports well new amount of data
- Maybe for big python implementations
- Use it to run complex machine learning projects
Yes
Yes, but I was not here at the time so I do not have any information.
- Product Features
- Product Usability
- Prior Experience with the Product
I am not sure about the pricing itself, but I think treasure data still is a crucial project that we ave going on in the entire word for ab inbev, and as the platform offers a lot of options to use it, as it's own dashboard BI platform to have a better visualization.
I was not envolved in treasure data decision, but for what i hear the platform was a huge upgrade considering the funcionalities and availability.
- Don't know
- I guess find good ways to work the data inside the platform
- Zones adoption
- in-person training
Actually I think depends in what you are working and what you need from treasure data, so you need to choose the best tool for that. For example treasure insights, it's a great platform, but the model building were not made to be a real time dashboard if you have more then 50 milion records.
No - we have not done any customization to the interface
No - we have not done any custom code
Not really, the one big change that I am aware was about a storage issue when exporting data, and treasure data worked and gave us a new feature to fix the issue.
yes, Abi does have the premium suport, as we do deal with a lot of final users that requires a quick response.
Yes
Yeah, i reported a storage bug and treasure data developed an improvement for us to be able to export a huge amount of data.
Just yesterday I need help with creating secrets workflows using an api rest, and Ivan presented to me a perfect and functional example how to do so, and that saved a couple hours of reading the documentation.
- Master segment, where you can easily filter data
- A huge catalog of integrations
- Easy way to export data
- using python in treasure data could be a challenge
- Create tables with different columns formats
- Export more than 2 Billion records
- Amazon redshift
- Google sheet
- Google bigquery
- Amazon s3
For these integrations, we were downloading data into cdp, and it was really easy to do so, as the configuration and setup for the connector it's really fast to be completed
- Not really, all the integrations that I need to develop, treasure data already had the connector
N/A
- File import/export
- Single Signon
- API (e.g. SOAP or REST)
- ETL tools
I think most of the integrations we have is about export and import data.
Just keep doing the great integration work!
I do not participate in any sales project with CDP or ABI.
I do not participate in any sales project with CDP or ABI.
Yes
Yes, they worked very nice to delivery a god transition
- I am not aware of the new upgrade, only by the contract upgrade
- I would like if the workflows could load the logs faster
- And sometimes the loading from the workflows could take a while, so it would be nice to fix that as well
No
No
It is being rolled out in phases but will be used across the whole organization. Currently within sales and marketing, primarily. With the ultimate goal of complete customer-centricity, the main problem we are addressing with the CDP is creating better experiences for our customers. Additionally, we have so much data that we need to unify and bring into one place.
- Knowledgeable team
- Helpful in setting up platform
- Insightful tools, platform, and people
- Great at strategic planning in our use cases
- Training has been great. We've had many training sessions across the org that were held by the ATD team.
- Hard to use if you're not heavily involved in data and analytics. We are hoping for an easier way for the marketing teams to utilize.
- Dashboards aren't super intuitive, but just require some additional walk-throughs.
- Need more resources
- We've run into some memory issues on the platform, but the ATD team is making improvements to fix these.
- We've been driving incremental revenue within our current use cases.
- Allows us to bring many 3rd-party tools in-house, which is a cost-saver and allows the platform to pay for itself.
- Brings our data together in a way we didn't realize was possible.
- A better understanding of our customer
Yes, the Treasure Data platform is definitely driving organizational change and making us much more data-driven. We are really finding that we have so much data, internally, that no one has the full breadth of it until we started this project. Internal processes and work change management are slowly changing as well. It has been a bit tough on that front, getting everyone on board to think of the CDP as the new way "of life."
- Increased personalization via various marketing campaigns, in new ways
- A holistic look at our customers and engagement with the company and our brands
- Scoring of our customers, active and inactive
I did/do think that Adobe Analytics is a good tool that helps bring in all data. I really think the big point with the tool is for metrics and de-duping across media campaigns. Treasure Data is definitely much more than that. You do get to see how all of your campaigns 'play' together but it's more of a customer-focused tool that makes sure you're not overly communicating with anyone.
We have users and people who are involved with the use of the Treasure Data CDP, from nearly all functions of our organization. Primarily the main "users" are on the IT and data analytics side. But, our marketing side on both pre- and post-sales depends on this tool. Also, our media agencies and partners use the data from this tool as well.
11
We have 11 people in total that are 100% committed to supporting Treasure Data. The positions include program managers, project managers, IT (several areas), data scientists, and data engineers. Outside of the core group, we have representatives from each main stakeholder from pre and post-sales, marketing, media, customer relations management, etc.
- Increase personalization within our current campaigns
- Bringing in tools that are sourced from outside vendors, in-house by utilizing the data we store within Treasure Data
- Customer and engagement scoring
- Bringing in potentially more vendor products in-house to reduce costs and make them more personalized
- Additional audience building within media campaigns
- Tapping into our dealer's internal systems to gather more information
Yes
We are replacing our email deployment tools, some of our 3rd-party vendor products, and some aspects of our campaign management system. Having all of the tools in 1 location, which enriched data and customer profiles is the smart way to go. We will have additional information and data and easier to have everything in one place. Additionally, it's a cost savings.
The technical abilities made us choose Treasure Data over other products that we looked at. The fact that the tool can bring many things in-house vs being single-threaded like we noticed some of the other vendors were. The price is pretty comparable across the board, so that wasn't a huge driver for us. Additionally, the profile unification features were a big win.
I do know that this was a very strenuous and time-consuming project to undertake. I do believe that all of the time and effort put into it was worth it. Perhaps if we would have dug in a bit more on the technical and usability side, that could have been beneficial to us.
Not Sure
No
The team, as I mentioned, are very much all hands on deck. We see that they are working all hours of the night to ensure that we are on a good path and our issues are resolved. We literally see that they are working until 5 AM our time and will be present in a meeting the next morning without any concern. They definitely care about our well-being and success.
- Query finding and loading
- Reading the data
- Interface is intuitive to use
- The dashboards aren't very intuitive (for reporting)
- Building actual queries
- Audience segmentation in a way that makes sense to marketers
All of the same comments as the other questions. They have gone above and beyond, especially during negotiations and contract signing due to COVID-related issues. But, never skipped a beat with us and worked diligently on good faith. We did negotiate some additional assistance in shadowing and transitions from Treasure Data 100% supporting us to our team taking over, which has been very helpful
I do not think that they were difficult to negotiate with at all. I don't think I have any advice in that sense. They are offering and providing everything that we had asked for, so no change in that sense. In fact, they went above and beyond what was expected of them.
July 29, 2020
Amazing Product, Amazing Service
The marketing team at National Debt Relief is leveraging Treasure Data in many ways to expand and grow our audiences for acquisition purposes. We leverage our first-party data to create more audiences for paid social, display, and email. And that is just the tip of the iceberg. We are able to realize a slew of insights and act on them swiftly and proficiently. Out of all of the products we use (CDP, DMP, DSP) we believe that the CDP provides us the most insight and return on revenue.
- Customer Service
- Integration
- Insights
- Realizing return on investment quickly
- Robust capabilities (younger company)
- We have seen significant return on investment
Treasure Data is able to take your first-party data to the next level. The solutions we have found using Treasure Data have allowed us to grow and expand our team. The possibilities and integrations are endless and they're a team that can make it happen for you!
- Expanding into 3P audiences and leveraging the CDP to retarget them
- Integrate into multiple walled gardens to activate 1P LAL and overlap interest audiences
- Stand up an integration with SalesForce marketing cloud to set up 'nudge' emails to push people down the funnel
Unfortunately, I was not apart of the decision to onboard Treasure Data. I was very new to this space when I inherited this tool and initiative on my team.
2
Treasure Data is used by the marketing team for customer acquisition purposes. The CDP serves us with multi-function purposes on the acquisition front. Using insights from the CDP we are able to curate lower and mid-funnel avenues so we can digitally target the potential client in the most cost-effective way.
2
For the most part, Treasure Data does the heavy lifting from the software side. However, it does help to have a team or product knowledge to make sure the data is funneled, captured, and used properly. Otherwise, the intended audiences you create in the CDP may now be accurate. From a marketing side, it's good to have someone on your team that is well equipped to understand audience and buyer personas to be able to use the CDP to the fullest extent.
- Acquisition
- Nurturing
- Post-sales enrollment communications
- Email - client newsletters
- Email - automated reviews
No
- Product Features
- Product Usability
At the end of the day, we want to make sure the products we purchase continue to produce an ROI. After 1 year of use, I am happy to say that we made the right decision and we are excited by the growth we are seeing from this product.
I would not do anything differently, I am very happy with the results.
Not Sure
No
We wanted to set up an integration with Salesforce Marketing Cloud, which was not set up internally and our product team was spread to thin to make it a priority. Treasure Data reached out to internal teams to set up API connections so we could feed in audiences, essentially creating a workaround for something we couldn't do in the past. This meant we could streamline email campaigns and processes because of the help of Treasure Data.
Treasure Data is used as the CDP for one of the regions (APEC) primarily for creating master customer profiles. Currently, we are using it for various use cases like Abandoned Cart/Abandoned Browse, Social Media campaigns, RFM segments, Cross-sell, etc. Additionally, the master segment and reporting/dashboarding functionalities are being used to track the growth of the number of customer profiles, attribution by various email sign-up sources, other reporting uses cases.
I have found the step-by-step workflow in building multiple segments very useful, which can be either run on-demand or scheduled for automated execution and campaign activations. The next steps are to leverage machine learning models for additional use cases like predictive scoring, etc.
I have found the step-by-step workflow in building multiple segments very useful, which can be either run on-demand or scheduled for automated execution and campaign activations. The next steps are to leverage machine learning models for additional use cases like predictive scoring, etc.
- Providing omni-channel view of customer behavior
- Data ingestion including batch and near real-time data
- Campaign activation including email and social media
- Great UI, Flexible Data Model to work with given enterprise data
- Documentation could be better for the workflows & any custom logic implemented. Seems to be improving with the new approach using Markdown.
- API key management can be improved further
- Better customer engagement levels
- Reducing churn and increasing customer LTV
- Campaigns are now more effective resulting in higher RPU (revenue per user), better CTO rates, etc.
Prior to Treasure Data, the campaigns were mostly generic without being tailored to guest preferences. With the CDP on Treasure Data implemented, it has helped our organization to better target the customers based on their master/unique profile as well as better manage the customer lifecycle journey especially engaging with the lapsing or lapsed customers. Overall the CDP has helped in a deeper understanding of customer behavior.
- Calculating the inferred product gender
- Leveraging the PySpark API to get the curated/profiled data back from Treasure Data for the purpose of integrating with the data lake
- Agilone and Acquia Platform
Based on my experience, the most striking difference between the two platforms are the way their data models are organized.
Agilone (now part of Acquia) has a very hard/strict requirement for integration with the source systems as we need to conform/adhere to their canonical/existing data model while Treasure data is quite flexible in being able to work with the respective source data as long as the relevant data was present. Overall, this has translated into a faster time to market in the case of Treasure Data and flexibility in incorporating changes/enhancements.
Agilone (now part of Acquia) has a very hard/strict requirement for integration with the source systems as we need to conform/adhere to their canonical/existing data model while Treasure data is quite flexible in being able to work with the respective source data as long as the relevant data was present. Overall, this has translated into a faster time to market in the case of Treasure Data and flexibility in incorporating changes/enhancements.
12
Treasure Data is mostly used within our eCommerce and Digital Marketing, Data Science and Data Analytics, and CRM (Customer Relationship Management) functions.
6
To support Treasure Data integrations, the team has skills related to Data Engineering (Azure Data Factory, Databricks, Apache Spark, ADLS, etc.) and Data Science (Python, ML, etc.)
- Customer Data Platform for maintaining the 360-degree view of the customer
- Activating email and social media campaigns
- Tracking RFM scores & increasing Customer LTVs
- Enhanced reporting and dashboarding
- Building propensity models
- Better retention of lapsing guests and win back of churned guests
Yes
We require the support as we are still in the process of enhancing and building new uses for the business functions like building propensity models based on various criteria like propensity to buy on markdowns/discounts, propensity to buy certain product categories, etc. There is a backlog of features like the above as well as integration of new geographies that are planned in the near future that requires further support.
Yes
The Pyspark API was not working with datasets that have array columns/datatypes. This was promptly resolved upon reporting to their technical team who in turn raised it with their product team.
When we were faced with a couple of issues in being able to integrate the curated data from Arm Treasure Data platform back to our Azure DataLake, we reached out to Arm Treasure Data's support team. They provided the much-needed support on the changes to be made in the scripts and the right way to apply the API keys to successfully establish the connection and resolve the issue.
Treasure Data is being used across about half of the organization. It gives us the ability to ingest, store and analyze a very large volume of gaming events. It also helps us to get near instantaneous data events from our games. Ability to handle large volume of events is why we went with Treasure Data in the first place.
- Treasure Data is excellent in integration with various software and services.
- Implementation of the their SDK is also very easy.
- Treasure Data SDK works well in our applications and does not crush.
- Data management is very challenging with Treasure Data (can't delete records, update tables, create indexes, etc.).
- Analyzing and queries tables with very large number of records is near impossible or takes a very long time.
- To effectively visualize data we need to first export it to SQL and the run our viz tools due to the reason above.
- Treasure Data allowed us to start measuring metrics in our apps which we never been able to before.
- I would say that at this point Treasure Data is most likely ROI positive, although we haven't done extensive analysis.
We definitely have access to detailed data we did not have before with Treasure Data. This allows us to make data-driven business decisions on how to operate our mobile applications better. Our monetization strategies in our applications have improved as a result of us examining the detailed application events by a good margin.
- We schedule a lot of our data aggregation in Treasure Data and push the data to MS SQL for faster analysis and visualizations.
- We are looking into utilizing Treasure Data's API to do two-way communication and data passing.
Treasure Data is more cost effective than Leanplum, has more functionality then Mode or App Annie, although not as user-friendly or provides as many tools for analysis. As a data ingestion tool, Treasure Data we believe gave us the best bang for our buck. Our development team also liked Treasure Data's SDK implementation better than Leanplum's.
5
Three DA's, one BI Engineering, and a Director - All Data Analytics.
1
BI Engineering (DBA)
- Ad Hoc Queries
- Aggregation of Daily KPIs
- Integration with various other tools
- Two-way communication with Treasure Data's API
Yes
Replaced Flurry Analytics
- Price
- Product Features
- Product Usability
No, I think Treasure Data is what we need.
- Implemented in-house
No
Change management was a small part of the implementation and was well-handled
- Naming conventions in the mobile SDK were not followed, so column names in the tables can be different across games.
- Self-taught
Documentation is excellent, so learning without training is not a problem.
No
No
My queries ran out of memory, support helped me optimize my Presto SQL to run my queries.
- Running AdHoc Presto queries on relatively small data sets.
- Scheduling queries and workflows are very easy.
- Running Hive queries on very large data sets.