About Arm Treasure Data
Treasure Data was founded in California in 2011 and acquired by Arm in 2018. The company has its headquarters in Mountain View and offices in Korea and Japan. Arm Treasure Data describes itself as an "enterprise CDP". In other words, its platform is optimized for companies with highly complex organizations – with many different business units, for example, or sales regions.
Arm Treasure Data focuses on the automotive, retail and consumer goods, gaming, marketing and advertising, and IoT sectors. Its customers include Subaru, Wish, Bandai Namco and Dentsu.
Customer data platform – categorizing Arm Treasure Data
The Arm Treasure Data platform has been designed to collect, merge and segment data. With over 120 connectors, it can connect virtually all popular systems as both inbound and outbound channels. If the software a company is using is not supported, an open API allows additional tools to be attached. Arm Treasure Data's CDP also includes a cookie system that tracks and analyzes user behavior on websites in real time. The data is sent directly to Treasure Data via pipelines for further processing.
In addition to the ability to collect, merge and enrich data, Arm Treasure Data features built-in machine learning and artificial intelligence algorithms that enable the segmentation of users and creation of user profiles. While doing this, CDP observes country- and region-specific data protection regulations to ensure that the data is being used legally and ethically. The results of the analyses can be displayed in the built-in dashboard or in third-party software such as Tableau or Power BI. The analytics platform is supplemented by "workflows", which can create data processes directly in Arm Treasure Data.
This is why Arm Treasure Data can be classified as follows within the CDP categories:
CDP key features
The customer data platform of Arm Treasure Data contains the following key features:
Arm Treasure Data stores its data in a data lake and is a software as a service (SaaS). The data flowing into the CDP from the different data buckets is identified and used to populate a standardized data platform. Data sources include PoS, IoT, Web, SaaS, mobile and offline resources, which may be enhanced with second- or third-party data. Workflows process this data immediately and produce reports or analyses based directly on the new data.
Options to segment audiences are implemented directly in Arm Treasure Data. The tool features an integrated dashboarding module that makes viewing the segmentation results easier. The CDP also features AI and ML algorithms for scoring or making recommendations. The results can then be turned into visual dashboards or the data can be transferred to tools such as Python or R.
Arm Treasure Data is not strong on campaign management functions, preferring instead to rely on third-party vendors. The platform therefore provides ready-made connectors for exporting the segments and, depending on the provider, to request responses directly. This significantly optimizes marketing campaigns.
Segmentation and dashboarding
The built-in AI and ML algorithms provide a convenient way of creating and managing segmentations. The results are clearly presented in the dashboards and any adjustments required may be carried out directly via a GUI.
Workflows enable the creation of data transformations without the need for additional ETL tools. The processes can be started as soon as the data has been uploaded to the CDP, allowing the data to be processed in real time. Analysts can therefore easily provide the data required by other departments without having to involve an IT department.
Arm Treasure Data is designed for large organizations seeking a stable and highly scalable solution. Its highly open concept makes it easy to integrate any software currently being used or to replace individual Treasure Data modules with specialist tools. The benefit for companies lies in having a tool that not only provides a useful level of basic functionality when they are beginning their digital transformation but that can also be easily extended later should the company decide to continue investing in digitalization.
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