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…
Treasure Data stacks up competitvely in the landscape of CDPs
Treasure Data is a Powerful Data-Driven, Technical Customer Data Platform
Treasure data accelerates Omnichannel Journey
Consolidated Customer Data Control Program
Treasure Data will let you fully, and EASILY, understand your data.
Treasure Data's Flexibility and Scalability is exactly what we needed
Integrated Customer Data for Triggered Target Audiences
Treasure Data will help us to grow all our revenue streams
Fullstack CDP
Treasure Data: Creating a 360° view of the Consumer for Better Media and Sales Effectiveness
Very good product to work with
I like to use treasure data, it has more pros than cons.
Great CDP with phenomenal support
Treasure Data for Seniors
Save Yourself the Headache – Give Treasure Data a Shot
Awards
Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards
Pricing
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…
Entry-level set up fee?
- Setup fee optionalOptional
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Details
- About
- Integrations
- Competitors
- Tech Details
- Downloadables
- FAQs
What is Treasure Data?
Treasure Data Screenshots
Treasure Data Videos
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 Cloud
- Pentaho
- Metric Insights
- Microsoft Office 2016 (discontinued)
- Microsoft Azure
- Google Cloud Storage
- Google Drive
- Intercom
- Zendesk Suite
- Elasticsearch
- MongoDB
- Google BigQuery
- Microsoft SQL Server
- PostgreSQL
- Snowflake
- MySQL
- MariaDB Platform
- Mirantis Kubernetes Engine
- Heroku Platform
- Stripe Payments
- Mailchimp
- Salesforce Marketing Cloud Email Studio, on marketing cloud
- Salesforce Marketing Cloud
- HubSpot Marketing Hub
- NetSuite ERP
- Meta Business Suite
- Sizmek Ad Suite
- AdRoll
- LiveRamp
- Salesforce Marketing Cloud Intelligence, on Marketing Cloud
- Twitter Ads
- Google Tag Manager
- Branch
- Amazon Kinesis
- Unity
- iOS
- Android
- Unreal Engine
- Oracle Marketing
- TUNE
- Google Marketing Platform
- pandas
- Eyeota
- Oracle Responsys
- part of Oracle CX Marketing
- salesforce sales cloud
- kafka
- hive mall
- jupyter
- R
- mLab
- fluentd
- JDBC
- Luigi
- Python
- Rest API
- informatica
- ruby
- 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
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% |
Comparisons
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Reviews and Ratings
(149)Community Insights
- Business Problems Solved
- Pros
- Cons
- Recommendations
Treasure Data has proven to be a versatile and powerful tool for a wide range of use cases. Customers have found that Treasure Data addresses the business problem of scattered data sources by providing a single platform for data collection and analysis. It serves as an ETL platform, analytical database, and data warehouse, supporting various business units across organizations. Users rely on Treasure Data as their primary storage and processing facility for large volumes of event data, eliminating the need to worry about storage and processing infrastructure.
Marketing teams utilize Treasure Data to enable a constant flow of data between databases and platforms like Salesforce, supporting email campaigns and providing refreshed data. The software helps clients understand customer behaviors, digitize the consumer base, and gain insights for business decisions, leading to increased revenue. It also serves as a central source of truth for customer data, solving the problem of fragmented information across digital and offline properties. Furthermore, Treasure Data is used for web tracking and analytics, supporting marketing teams in tracking website usage and campaign performance, ultimately improving the user experience. Overall, Treasure Data has helped companies store and secure their data while generating valuable insights to support data-driven decision-making.
Flexibility in Data Management: Many users have highly appreciated the flexibility of Treasure Data in ingesting different data sets and creating a data lake. This feature has been praised by numerous reviewers, allowing them to easily manage their data and streamline the data management process.
Extensive Native Integrations: The extensive native integrations provided by Treasure Data have received high praise from users. They have mentioned that these integrations cover the majority of systems they use, saving them time and effort in connecting different systems. Several reviewers have expressed their satisfaction with this feature.
Reliability and Uptime: Users consistently mention that Treasure Data is highly reliable, boasting a 99.99% uptime rate. This level of reliability has given them confidence in the platform and allowed them to trust that their data and jobs will always be accessible. Numerous reviewers have highlighted this aspect as one of the strengths of Treasure Data.
Cons:
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Frequent Request Failed Errors: Many users have experienced frequent "Request failed with status code 429" errors while using Treasure Data. These errors can be frustrating and disrupt the workflow, leading to delays in completing tasks.
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Lack of Error Resolution Guidance: Some reviewers have mentioned that they faced difficulties in resolving the "Request failed with status code 429" errors. They felt that there was a lack of clear guidance or documentation on how to troubleshoot and fix these issues, which made it challenging for them to resolve the errors independently.
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Impact on Productivity: The recurring "Request failed with status code 429" errors negatively impact productivity for some customers. Users expressed frustration at having to constantly deal with these errors, as it interrupts their work and requires them to spend additional time trying to resolve the issue or contacting support for assistance.
Users commonly recommend several actions for optimal use of Treasure Data. First, they suggest thoroughly testing the software before making a purchase decision. This allows customers to assess if the platform meets their specific needs and requirements. Second, users recommend having a skilled technical team in place to make the most of Treasure Data's capabilities. This ensures proper configuration and utilization of the platform's features. Lastly, users suggest engaging key personnel within the organization to maximize the benefits of using Treasure Data. This collaboration helps leverage the platform's flexibility and robustness for effective data management and analysis.
Additionally, users highly recommend Treasure Data for its comprehensive toolset, data connectors, analytical database, and excellent support. They emphasize that it is well-suited for managing massive amounts of data and allows analysts to work independently without relying heavily on engineers. With its powerful big data and business intelligence capabilities, Treasure Data can serve as an efficient ETL pipeline and facilitate seamless exporting of results to a warehousing database for scheduled queries. It is advised to ensure a comprehensive list of data sources and validate aggregation levels for accurate analysis. Reading through documentation and relying on customer success representatives are also recommended for efficient support.
Overall, users find Treasure Data to be a flexible and robust Customer Data Platform (CDP) with a powerful set of features and excellent support, making it a valuable asset for businesses dealing with large datasets.
Attribute Ratings
- 9.1Likelihood to Renew5 ratings
- 9.1Availability1 rating
- 8.2Performance1 rating
- 8Usability4 ratings
- 8.2Support Rating7 ratings
- 7.3Online Training1 rating
- 6.4In-Person Training1 rating
- 6.4Implementation Rating2 ratings
- 7.3Configurability1 rating
- 9.1Product Scalability1 rating
- 9.1Ease of integration1 rating
- 7.4Vendor pre-sale2 ratings
- 7.3Vendor post-sale2 ratings
Reviews
(1-5 of 5)I like to use treasure data, it has more pros than cons.
- 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.
- Creating dashboards, in treasure insights.
- 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
- Product Features
- Product Usability
- Prior Experience with the Product
- Don't know
- I guess find good ways to work the data inside the platform
- Zones adoption
- in-person training
- 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
And also the master segment usability is awesome, as we can filter a lot of data the way we want.
- Amazon redshift
- Google sheet
- Google bigquery
- Amazon s3
- Not really, all the integrations that I need to develop, treasure data already had the connector
- File import/export
- Single Signon
- API (e.g. SOAP or REST)
- ETL tools
- 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
- 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
- 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
- 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
- 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
Amazing Product, Amazing Service
- Customer Service
- Integration
- Insights
- Realizing return on investment quickly
- Robust capabilities (younger company)
- We have seen significant return on investment
- 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
- Acquisition
- Nurturing
- Post-sales enrollment communications
- Email - client newsletters
- Email - automated reviews
- Product Features
- Product Usability
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.
- 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
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.
- 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
- 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 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.
- Ad Hoc Queries
- Aggregation of Daily KPIs
- Integration with various other tools
- Two-way communication with Treasure Data's API
- Price
- Product Features
- Product Usability
- Implemented in-house
- Naming conventions in the mobile SDK were not followed, so column names in the tables can be different across games.
- Self-taught
- Running AdHoc Presto queries on relatively small data sets.
- Scheduling queries and workflows are very easy.
- Running Hive queries on very large data sets.