Post by account_disabled on Nov 23, 2023 6:06:13 GMT
Building your own technology solutions GA 's integration with BigQuery also gives us the flexibility to build our own technology solutions to support our advertising campaigns, SEO optimization and other marketing activities. We can use this data to create advanced attribution models, which are key to monitoring the effectiveness of our campaigns. IN CubeGroup, we use GA integration with BigQuery to build advanced attribution models and our own marketing tools that help us better understand the impact of advertising campaigns and optimize their results. This allows us to analyze data more deeply, create personalized solutions, automate work and make better decisions in the area of marketing.
GA and BQ integration issues Google is strongly promoting its Cloud services, which are certainly intended to help the company diversify its revenue sources. One of the ideas to improve finances was to introduce GA , which, when combined with GCP and BQ, will start Email Marketing List generating micropayments. For most businesses, these costs should not be significant and the benefits of additional capabilities offered by a given data warehouse should provide an appropriate ROAS. Unfortunately, GA still has bugs, and some of them can be found after connecting to BQ. The best way to connect GA to BQ is to use the builtin connector.
This solution allows us to transfer all data without incurring additional costs. In practice, however, it turns out that Google has problems with some metrics and, for example, does not transfer all gclid data, which affects the quality of Google Ads data in BQ. However, connecting GA with an external API tool also does not solve this problem and generates other problems, such as the lack of pseudo_user_id or pseudo_session_id metrics, thus making it impossible to build many different metrics and computational data. The solution to the problem is to use UTM parameters in all Google Ads campaigns.
GA and BQ integration issues Google is strongly promoting its Cloud services, which are certainly intended to help the company diversify its revenue sources. One of the ideas to improve finances was to introduce GA , which, when combined with GCP and BQ, will start Email Marketing List generating micropayments. For most businesses, these costs should not be significant and the benefits of additional capabilities offered by a given data warehouse should provide an appropriate ROAS. Unfortunately, GA still has bugs, and some of them can be found after connecting to BQ. The best way to connect GA to BQ is to use the builtin connector.
This solution allows us to transfer all data without incurring additional costs. In practice, however, it turns out that Google has problems with some metrics and, for example, does not transfer all gclid data, which affects the quality of Google Ads data in BQ. However, connecting GA with an external API tool also does not solve this problem and generates other problems, such as the lack of pseudo_user_id or pseudo_session_id metrics, thus making it impossible to build many different metrics and computational data. The solution to the problem is to use UTM parameters in all Google Ads campaigns.