Digital Marketers have access to more data than ever before. However, this data is often spread across many individual systems. Without consolidating this data into a central repository, you lose some incredibly deep and valuable insights about your customers. As a result, you either accept that you have remote inaccessible data or you employ a manual work process. The latter necessitates hours of resource to bridge the gap between these data silos. Market analytics with Google BigQuery and Matillion ETL for BigQuery addresses these challenges. Together these solutions can help you consolidate your data to gain insights that foster market activation and improved customer experience.
Google, unsatisfied with the current state of affairs developed a marketing data analytics starter pack. This is for Predictive Digital Marketing to make analysis easy and fast. This bundle supports the early life stages of of the data cycle, primarily Collect, Transform and Analyze.
The technology helps with the first three steps. This allows users to focus their time and energy at added value stages further along the data lifecycle. For example, this time can be spent on generating insights, activation or even Machine Learning.
Google Cloud Platform follows a straightforward formula for generating insights. Data is enhanced by the number of connectors, which has a multiplying effect on the insights or business outcomes.
By increasing the number of connectors and therefore amount of data available, companies are able to gain a more holistic view of their customers. This customer centric approach to marketing not only delights audiences in its ability to meet needs before they are even realized, but is also contributing to a greater trend in digital marketing – Predictive Market Analytics. The key is more connectors and more data.
While Google is able to connect with a host of native data sources including, Google AdWords, Google Drive, DoubleClick, and Youtube to name a few, other ecosystem tools can expand BigQuery’s pool of data sources to ingest.
Matillion ETL for BigQuery
With over 50 data connectors, Matillion ETL for BigQuery can help you quickly ingest data into BigQuery from a variety of different systems. These include payment systems, flat files, CRM software, social media sources and more. Even data from internal bespoke systems using a Database Query or an API Query, can be easily consumed into BigQuery. The Scheduling feature can help you build a continuous data loading pipeline. This ensures BigQuery always has your most recent and up-to-date data.
Matillion ETL, however, is more than just a data integration tool. Use the transformation tools within Matillion ETL to clean and transform data to be used in data visualization tools such as Google Data Studio, Tableau, or Looker. Since Matillion ETL for BigQuery has been natively built for Google, it fits in nicely with other Google Cloud Platform services. Being able to use Pub/Sub, for example, further enhances the usage and benefit of your data.
To learn how you can use Matillion ETL to populate your BigQuery database, watch a clip from our recent webinar “Accelerating Marketing Insights with Google Cloud and Matillion ETL”.
the7Stars’ Market Analytics with Google BigQuery and Matillion ETL for BigQuery
the7Stars, the leading UK Digital Marketing agency, has global clients ranging from Nintendo to Suzuki to supermarket chain, Iceland. With growing data volumes, the7Stars faced the challenge of centralizing all their customers’ marketing data for quick and easy analysis. To get control of their reporting and billions of rows of data, they turned to Google BigQuery and Matillion ETL for BigQuery,
Since retiring manual Excel based workflows, the7stars is saving hundreds, if not thousands of hours a year on reporting. Furthermore, they are able to get all their DoubleClick, Google Analytics 360, AdWords, Facebook and affiliate partner data into Google BigQuery. Matillion ETL for BigQuery can then interact with the data to prepare it for ingestion by Tableau. This is making the visualization process more performant than ever before. the7stars is now able to dedicate more time to commentary and insights on deeper data than on data preparation activities. This is leading to fast informed business decisions.
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