{"id":16050,"date":"2023-09-13T14:33:34","date_gmt":"2023-09-13T07:33:34","guid":{"rendered":"https:\/\/gcloudvn.com\/?p=16050"},"modified":"2024-07-31T10:17:46","modified_gmt":"2024-07-31T03:17:46","slug":"built-with-bigquery-the-new-era-of-cdps-built-on-bigquery","status":"publish","type":"post","link":"https:\/\/gcloudvn.com\/en\/ban-tin\/ky-nguyen-moi-cho-customer-data-platforms-cdps-voi-su-tich-hop-hightouch-va-google-bigquerry\/","title":{"rendered":"Built with BigQuery: The new era of CDPs Built on BigQuery"},"content":{"rendered":"

In almost every industry and organizations of every size, first-party data is stored internally <\/span>Google BigQuery<\/span><\/a> are all of great value. From operations to marketing and personalized experiences, first-party data is always the key to unlocking business success in the 5.0 advertising era.<\/span><\/p>\n

Historically, marketers and advertisers have relied on packaged customer data platforms (CDPs) to collect, store and model customer data, then push that data into downsteam tools. next. However, thanks to the development of AI Lakehouse and Google BigQuery, separate processes for collecting data, establishing models, and storing in CDPs have become redundant.\u00a0<\/span><\/p>\n

By Integrated with <\/a><\/span>Hightouch \u2013 a data activation platform that enables organizations to make the most of BigQuery data<\/span>, companies can now create a consolidated customer data platform, leveraging existing data investments and the powerful optimization capabilities of their data warehouse. With Hightouch and BigQuery, businesses can build customer personas and synchronize data with more than 200 tools and touchpoints. This integration empowers organizations, creating a unified and flexible platform that meets all their business use cases, while maximizing the potential of their data assets.<\/span><\/p>\n

In this blog, Gimasys will help you learn more about the concept CDP Composable<\/strong>, explores the benefits they offer, providing practical guidance on how to unlock the true potential of your data with CDP when built with BigQuery and Hightouch integration.<\/span><\/p>\n

\"Use
Use cases for a composable CDP built with BigQuery<\/em><\/figcaption><\/figure>\n

Use case 1: Building a Customer 360<\/b><\/p>\n

Data teams can build <\/span>Customer 360<\/span><\/a> directly in BigQuery, allowing companies to understand customer engagement in the most comprehensive way across all channels, devices, and media (including offline engagement). This 360 profile is the basis for effective analysis, personalization and delivering the best customer experience.\u00a0<\/span><\/p>\n

Hightouch offers a 360 Customer Toolkit that allows organizations to create multiple identity and entity resolution models directly in BigQuery without writing any complex SQL or code.<\/span><\/p>\n

Use case 2: Activating data with Reverse ETL<\/b><\/p>\n

Data teams can sync data to downstream business tools like CRMs, ESPs, and ad platforms by using Reverse ETL.\u00a0<\/span><\/p>\n

Business operations using these tools will be improved by data, driving better results and ensuring that everyone is working on the same source of truth in BigQuery. These features help data teams save effort on building and maintaining systems, integrating with APIs, and distributing ad-hoc CSV to other business teams.<\/span><\/p>\n

Use case 3: Driving personalization across channels<\/b><\/p>\n

Marketers can achieve better results by personalizing the content delivered to their customers.\u00a0<\/span><\/p>\n

Customer lifetime value will improve when companies provide relevant and personalized experiences through SMS, email, mobile and web notifications. To do this, organizations first need to collect and store customer information, model predictions from that data, and then make that data and insights available to tools and channels. their marketing.<\/span><\/p>\n

Use case 4: Improving Return on Ad Spend (ROAS) and increasing ad efficiency<\/b><\/p>\n

Marketers can improve the efficiency of their campaigns by syncing customer data into advertising platforms.\u00a0<\/span><\/p>\n

Marketers can limit the types of customers they do not want to target, such as those who have signed up to make a purchase or those who have declined to make a purchase, to reduce waste in advertising spend. Similarly, marketers can build audiences from their existing customer base to identify new customers to attract. They can also provide conversion data to these platforms to optimize their automated campaigns. All of this advertising effectiveness depends on the ability to easily sync data from BigQuery to ad destinations.<\/span><\/p>\n

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