Omnichannel marketing and customer analysis
Connects with POS data, web, mobile, or CRMS to collect customer data so marketers can track user statistics, income, interest, and demographics to create targeted media campaigns
Automates mobile push, video ads, surveys, chat bots, or contents based on custom audience segments
Supports personalized email campaigns by pulling and analyzing customer data and collecting data-driven feedback about each campaign
Enables advanced queries and workflows so teams can analyze omnichannel data with a few clicks
How Treasure Data works
Treasure Data is an integrations platform that gives you tools to extract data out of various cloud apps and pull everything together in a single data platform. The interface gives you a visual representation of the integrations you’ve plugged into the system and how they’re connected. The operations for data transformations are written in SQL right in the tool and Treasure Data handles the heavy lifting to pull the right data out of your integrations and dump it into your data warehouse or other destinations. When it comes to customer data from your website or mobile app, Treasure Data gives you a few options to export data from specific analytics reporting tools, or via a one-click process with Segment.
Protect the quality of your data in Treasure Data with Segment
If you’re already using Segment and want to try out Treasure Data, the process will be simple. The main advantages of sending your Segment data directly into Treasure Data rather than pulling that data out of Google Analytics, Mixpanel, or some other analytics reporting tool is the Segment data format and data governance features that are not available in Treasure Data.
The Segment data spec is designed to be easy to understand and ready for analyses and transformations alike. The data coming straight from the specific analytics tools will be in the format those tools need to power reports and metrics, rather than the true raw format of what happened on the site or app. That slows you down ultimately since you need to transform each dataset to the convention in which you process it for analysis. Secondly, Segment has features (like Protocols) that protect the integrity and quality of the customer data that’s flowing to end tools. By using Segment to send your data, its all kept to the same intuitive spec, so you don’t have to waste time processing or translating it each time you need to use it. You also don’t need to worry about bad data polluting your marketing, analytics, or data warehousing tools, because it’s governed at the point of collection.