How Google’s Machine Learning Tools Turn Data Into Predictive Power
Discover how Google Analytics 4 and BigQuery ML make enterprise-grade machine learning easy. Learn to build churn models in SQL, create predictive audiences, and act on insights—while respecting user privacy. See five practical tips you can apply today
Lisa Ying
Manager, Data Solutions
Machine learning is transforming modern analytics from rear-view reporting to forward-looking predictive insights. Rather than simply tallying past clicks and conversions, tools like Google Analytics 4 (GA4) and BigQuery ML forecast what customers will do next, enabling teams to react faster, allocate budgets smarter, and craft experiences that anticipate user needs.
A great example of how this is happening in the real world is Google. With tools like Google Analytics 4 (GA4) and BigQuery ML, Google is bringing powerful machine learning features to businesses of all sizes, and making them surprisingly easy to use.
Why Predictive Analytics Beats Guesswork
For years, analytics was about looking backward. You could see how many people visited your site, where they came from, and what they clicked on. Helpful, but limited.
GA4 Forecasts: Purchase Probability, Churn, Revenue
Now, with GA4’s built-in predictive metrics, you can see what’s likely to happen next. You can track:
Purchase probability - Which users are most likely to buy something soon
Churn probability - Which users might stop visiting your site
Predicted revenue - How much value each user might bring in the future
This kind of information helps businesses act before it's too late, like reaching out to users likely to leave or giving a nudge to someone who’s close to purchasing.
Machine Learning For Everyone - No Data Science Degree Required
Building Models with AutoML and Familiar SQL
One of the best things about Google’s approach is how accessible it is. With tools like BigQuery ML and AutoML, teams can build machine learning models using tools they’re already familiar with, like SQL.
That means marketers, analysts, and product managers - not just engineers - can use machine learning to solve real problems. You can build models that predict churn, group users into high-value segments, or even forecast revenue. No complex code or special infrastructure required.
Smarter Audience Targeting & Real-Time Personalization
Exporting Predictive Audiences to Google Ads
Once you have predictive data, you can act on it immediately.
In GA4, you can create audiences like:
“Users likely to buy in the next 7 days”
“Users likely to churn”
These audiences can be sent straight to Google Ads, so your campaigns are targeting people based on real data, not assumptions. It’s more efficient, more personal, and usually more profitable.
Training Models with SQL in BigQuery ML
With BigQuery ML, Google brings machine learning to the same place many teams already run their analytics - BigQuery.
You can train models with a simple SQL query like this:
CREATE OR REPLACE MODEL `my_project.my_dataset.churn_model`
OPTIONS(model_type='logistic_reg') AS
SELECT user_id, session_count, avg_time_on_site, churned
FROM `my_project.my_dataset.user_data`;
This lets analysts move from analysis to prediction without needing to move data or learn new tools.
Privacy-Aware, Responsible Machine Learning
As machine learning becomes more powerful, there’s also a responsibility to use it the right way. Google is putting a lot of effort into building tools that protect user privacy and support ethical AI.
Federated Learning & Differential Privacy Explained
Some examples include:
Federated learning, which keeps user data on the device instead of sending it to the cloud
Differential privacy, which helps keep individual user data anonymous
Clear guidelines for transparency and fairness in how models are built and used
These steps make sure companies can benefit from machine learning without putting user trust at risk.
Key Takeaways
Machine learning in GA4 lets you…
Spot at-risk customers before they churn by surfacing churn-probability scores in real time.
Forecast future revenue and high-value buyers so you can focus spend where it matters most.
Auto-build audiences ready for activation in Google Ads, DV360, and beyond—all without extra code.
Machine learning is no longer just for massive tech companies or people with PhDs in computer science. Thanks to platforms like GA4, BigQuery ML, and AutoML, it’s now within reach for anyone working in digital marketing, product, or analytics.
Whether you want to understand your customers better, run smarter campaigns, or just stop relying on guesswork, machine learning can help. And getting started is easier than you might think.
⭐ Napkyn Can Help
Need a partner to turn these predictive possibilities into real revenue? Napkyn is a Google Marketing Platform & Google Cloud partner specializing in:
- GA4 strategy, implementation, and custom training
- BigQuery architecture, cost optimization, and ML model development
- Audience activation in Google Ads, DV360, and SA360
- Privacy-first analytics solutions and Consent Mode
Let’s unlock smarter marketing together - contact us
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How Google’s Machine Learning Tools Turn Data Into Predictive Power
Discover how Google Analytics 4 and BigQuery ML make enterprise-grade machine learning easy. Learn to build churn models in SQL, create predictive audiences, and act on insights—while respecting user privacy. See five practical tips you can apply today
Lisa Ying
Manager, Data Solutions
August 6, 2025
Machine learning is transforming modern analytics from rear-view reporting to forward-looking predictive insights. Rather than simply tallying past clicks and conversions, tools like Google Analytics 4 (GA4) and BigQuery ML forecast what customers will do next, enabling teams to react faster, allocate budgets smarter, and craft experiences that anticipate user needs.
A great example of how this is happening in the real world is Google. With tools like Google Analytics 4 (GA4) and BigQuery ML, Google is bringing powerful machine learning features to businesses of all sizes, and making them surprisingly easy to use.
Why Predictive Analytics Beats Guesswork
For years, analytics was about looking backward. You could see how many people visited your site, where they came from, and what they clicked on. Helpful, but limited.
GA4 Forecasts: Purchase Probability, Churn, Revenue
Now, with GA4’s built-in predictive metrics, you can see what’s likely to happen next. You can track:
Purchase probability - Which users are most likely to buy something soon
Churn probability - Which users might stop visiting your site
Predicted revenue - How much value each user might bring in the future
This kind of information helps businesses act before it's too late, like reaching out to users likely to leave or giving a nudge to someone who’s close to purchasing.
Machine Learning For Everyone - No Data Science Degree Required
Building Models with AutoML and Familiar SQL
One of the best things about Google’s approach is how accessible it is. With tools like BigQuery ML and AutoML, teams can build machine learning models using tools they’re already familiar with, like SQL.
That means marketers, analysts, and product managers - not just engineers - can use machine learning to solve real problems. You can build models that predict churn, group users into high-value segments, or even forecast revenue. No complex code or special infrastructure required.
Smarter Audience Targeting & Real-Time Personalization
Exporting Predictive Audiences to Google Ads
Once you have predictive data, you can act on it immediately.
In GA4, you can create audiences like:
“Users likely to buy in the next 7 days”
“Users likely to churn”
These audiences can be sent straight to Google Ads, so your campaigns are targeting people based on real data, not assumptions. It’s more efficient, more personal, and usually more profitable.
Training Models with SQL in BigQuery ML
With BigQuery ML, Google brings machine learning to the same place many teams already run their analytics - BigQuery.
You can train models with a simple SQL query like this:
CREATE OR REPLACE MODEL `my_project.my_dataset.churn_model`
OPTIONS(model_type='logistic_reg') AS
SELECT user_id, session_count, avg_time_on_site, churned
FROM `my_project.my_dataset.user_data`;
This lets analysts move from analysis to prediction without needing to move data or learn new tools.
Privacy-Aware, Responsible Machine Learning
As machine learning becomes more powerful, there’s also a responsibility to use it the right way. Google is putting a lot of effort into building tools that protect user privacy and support ethical AI.
Federated Learning & Differential Privacy Explained
Some examples include:
Federated learning, which keeps user data on the device instead of sending it to the cloud
Differential privacy, which helps keep individual user data anonymous
Clear guidelines for transparency and fairness in how models are built and used
These steps make sure companies can benefit from machine learning without putting user trust at risk.
Key Takeaways
Machine learning in GA4 lets you…
Spot at-risk customers before they churn by surfacing churn-probability scores in real time.
Forecast future revenue and high-value buyers so you can focus spend where it matters most.
Auto-build audiences ready for activation in Google Ads, DV360, and beyond—all without extra code.
Machine learning is no longer just for massive tech companies or people with PhDs in computer science. Thanks to platforms like GA4, BigQuery ML, and AutoML, it’s now within reach for anyone working in digital marketing, product, or analytics.
Whether you want to understand your customers better, run smarter campaigns, or just stop relying on guesswork, machine learning can help. And getting started is easier than you might think.
⭐ Napkyn Can Help
Need a partner to turn these predictive possibilities into real revenue? Napkyn is a Google Marketing Platform & Google Cloud partner specializing in:
- GA4 strategy, implementation, and custom training
- BigQuery architecture, cost optimization, and ML model development
- Audience activation in Google Ads, DV360, and SA360
- Privacy-first analytics solutions and Consent Mode
Let’s unlock smarter marketing together - contact us
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Ricardo Cristofolini
Senior Implementation Specialist, Data Solutions
Sep 17, 2025
Read More
Key Events in GA4: Tracking What Really Matters
Chris Wright
Associate Director, Training and Development
Sep 10, 2025
Read More
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Sign Up For Our Newsletter