Supercharged audience segmentation with Google Analytics & iBQML

Instant BQML (iBQML) is a new point solution built by Google that enables marketers to improve audience targeting by applying machine learning to their first-party data in Google Analytics — modeled on BigQuery Machine Learning (BQML). 4 Mile Analytics + Media.Monks are actively supporting the tool’s global roll-out by leading training workshops on this easy-to-use marketing analytics technology.

Marketers can use iBQML to increase customer re-engagement and reduce the cost per customer acquisition. It applies propensity modeling to predict audience segments that are most likely to take a desirable action (like make a purchase), which can be directly exported into Google Ads to optimize return on ad spend (ROAS) through audience remarketing and bidding optimization. It also supports additional key marketing use cases like generating customer insights and supporting experiments to improve the customer experience.

iBQML leverages Google Analytics data and overlays a prebuilt machine learning (ML) model built on BigQuery’s native ML APIs. It provides a push-button tool to deploy data pipelines to facilitate the movement of data between Google Analytics and BigQuery. It only takes about 30 minutes to stand-up this workflow as opposed to what may have taken months in the past.

We see iBQML as an exemplar of the next wave of innovation in the analytics and ML space — bringing ML into targeted business-facing applications allowing users to generate predictions and take action within an integrated workflow.

GCP’s efforts to bring ML directly into BigQuery through BQML creates this potential for any number of use cases across industries and business domains. As long as data is available in BigQuery, we can now easily generate ML models to predict, classify, and forecast results, making them available for business intelligence and user action.

Feel free to reach out if you are interested in iBQML for marketing, BQML, or related analytics use cases.