Here’s a question for you: How do you focus digital marketing activities on the customers who are most likely to buy your products? Sure, there are several tools out there that can help you understand your customers better, but are limited to using their own datasets. What if you could combine data from different platforms like website analytics and customer relationship management (CRM) systems and perform statistical analysis against them to build a predictive model of likely high value customer prospects?
You may think that this sounds good in theory but hard to put into practice. That’s why we recently published an articleand tutorial demonstrating one way to achieve it, taking you on a step-by-step journey.
The diagram below shows what you need to know at a high level. Let’s talk through the big picture in a few paragraphs.
As you can see, there are a few products and data sources mentioned in this diagram. First, there’s Google Analytics Premium that provides actionable insights from your website data and can automatically export detailed, unsampled logs to Google BigQuery, Google’s fully managed, NoOps, data analytics service. In addition to Google Analytics Premium logs, BigQuery integrates with other Google Cloud Platform services like Google Cloud Dataflow, and supports third party tools for importing a wide variety of business data from existing corporate databases and CRM systems.
Fast, easy and powerful analytics with BigQuery
BigQuery can import, join, and correlate every single row of massive activity logs from different sources to extract valuable intelligence. By linking log data with your website registration forms, shopping carts, inquiry forms or any customer interactions, you can easily correlate those transactions with customer website behavior. These insights can dramatically increase the return on digital marketing investment. You can learn in this case study how Domino’s increased monthly revenue by 6% with Google Analytics Premium and Google BigQuery.
Standard tools for data scientists such as R, Tableau, and the Hadoop ecosystem are also best friends of BigQuery and can be tightly integrated with each other for sophisticated data analysis beyond simple correlations and table joins. For example, BigQuery can quickly aggregate and filter massive datasets for in-depth regression analysis with R.
In short, Google Analytics Premium + BigQuery + R provides an excellent platform for data scientists to realize a new predictive digital marketing approach.