What are some of the well-known MA tools?

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(4) Profile API Tokens
We have an API that can call up the segment data you created in real time. It can be used for website recommendations, so you can use the data that companies own to, for example, display content according to age and gender, or you can re-appeal to users who added products to their carts on an e-commerce site but did not purchase them.

Please also refer to the official Treasure Data website , which contains a wealth of case studies and technical resources.

Our website also provides useful materials comparing Treasure Data CDP with similar products, so please feel free to download and use them.

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Treasure Data CDP data usage process
When using data with a CDP, the general procedure is to follow the steps of 1. integration of various data, 2. analysis and visualization, and 3. implementation of measures. We will explain the role of Treasure Data CDP in each step.

1. Integration of various data
By aggregating various information such as customer information held by companies colombia whatsapp number database (name, age, gender, postal address, address, email address, purchasing information, etc.), web behavior log data from Google Analytics, and information obtained at physical stores, and selecting a key to combine this information, it is possible to build a system that automatically connects each piece of data on Treasure Data CDP.

In addition to data owned by your company, there are also products that provide data that estimates annual income by residential area, so it is possible to use data from other companies by using postal codes, prefectures, cities, towns, and villages as combining keys. In this way, we think it is important to combine data from your company and other companies and automate the process to move on to the "2. Analysis and visualization" step.

2. Analysis and visualization
After logging in to Treasure Data CDP, you can use SQL on the management screen for the integrated data, making it possible to quickly search and aggregate large volumes of data using aggregation functions.In addition, by using the machine learning (AI) function, you can predict users who are likely to make a purchase and link them to measures.

In terms of visualization, it can be integrated with major BI (Business Intelligence) tools such as Tableau, Microsoft PowerBI, DOMO, and Google Sheets (Looker Studio). By automating BI integration with date and time processing, etc., it can help speed up a company's PDCA cycle.