Author Photo By John Huang, Software Engineer

Cross-posted from the Google Analytics Blog

Measuring how marketing efforts influence conversions can be difficult, especially when your customers interact with multiple marketing channels over time before converting. Last fall, we launched Multi-Channel Funnels in Google Analytics, a new set of reports that help shed light on the full path users follow to conversion, rather than just the last click. One request we’ve had since the beginning was to make this data available via an API to allow developers to extend and automate use cases with the data. So today we’re releasing the new Google Analytics Multi-Channel Funnels Reporting API.

The API allows you to query for metrics like Assisted Conversions, First Interactions Conversions, and Last Interaction conversions, as well as Top Paths, Path Length and Time Lag, to incorporate conversion path data into your applications. Key use cases we’ve seen so far involve combining this conversion path data with other data sources, such as cost data, creating new visualizations, as well as using this data to automate processes such as bidding.

For example, Cardinal Path used the new Multi-Channel Funnels API, Analytics Canvas ETL (Extract, Transform, Load) and Tableau Software to help their client, C3 Presents, uncover how time and channels affected Lollapalooza ticket sales in an analysis dubbed “MCF DNA.” The outcome was a new visualization, similar to a DNA graph, that helped shed light on how channels appeared throughout the conversion funnel.

MCF DNA Visualization in Tableu Software


In another case, Mazeberry, an analytics company from France, helped their client 123Fleurs decrease customer acquisition costs by 20% by integrating data from the Multi-Channel Funnels API into a new reporting framework. Their application, Mazeberry Express, combines media cost and full conversion path data to provide new Cost Per Acquisition (CPA) and Return on Investment (ROI) metrics that provide a more complete understanding of how online channels are working together to influence conversions.

Mazeberry Express Screenshot - Focus on a Channel


Please note that this functionality only works with the new v3.0 API libraries, so you should upgrade now if you haven’t already (see our migration guide). We look forward to seeing how you make use of this new data source.


John Huang is a Software Engineer working on Google Analytics. John is interested in all things analytics, mobile, and photography.

Posted by Scott Knaster, Editor