We are pleased to announce the latest release of Analytics Canvas, with new features and upgrades that provide even more powerful access to your analytics data.
- Google Analytics Cost upload and Bing Ads API connectivity
- Advanced funnel Analysis
- Enhanced GA profile management for those accessing hundreds of profiles at once
- Advanced query partitioning to avoid sampling
Cost Upload into Google Analytics for online advertising ROI reporting
Sure, ad words might be a significant part of your overall digital marketing spend, but it’s not all of it. When Google Analytics introduced the ability to upload data INTO GA and created its Ads return on investment report, your ability to track cost and return from all of your advertising campaigns took a quantum leap. Analytics Canvas is the best way to take advantage of this functionality, particularly if you have lots of ad spend sources, and want to automate. You can learn more here with a helpful tutorial.
Advanced funnels for ecommerce analysis
While Google Analytics provides funnel analysis, we’ve stepped up the bar by pushing the Google Analytics API to its fullest, and combining it with Analytics Canvas automation and database connectivity. If you want to better understand your funnel, you have to give this new capability a try.
Define your funnel steps using:
- Custom variables
- Page path
Accessing and combining data from hundreds of Google analytics profiles at once
Many Analytics Canvas customers need to connect to dozens or even hundreds and hundreds of Google Analytics profiles. In V1.6 we’ve added even more features to help make this as easy as possible.
Filtered search, better options for multiple selection, editing and saving of profile lists make Analytics Canvas the choice of anyone with hundreds of websites that use Google Analytics. Check out our video tutorial that shows you how it works.
Sampling? No thanks!
If you try to query more than 500,000 sessions, Google Analytics will return sampled data. Analytics Canvas can automatically break the query down into smaller time frames, each of which is under the limit, so therefore avoiding sampling. Companies with serious web traffic can get access to raw data, and then pump it into databases using automation to integrate with their enterprise systems.
In version 1.6 partitioning is even easier to use, with more options for large numbers of queries and automation.