BigQuery ML (Machine Learning) is a BigQuery feature that lets you create and train machine learning models directly in BigQuery, without having to use other machine learning tools or frameworks.

Here are 4 concrete examples of how BigQuery ML can be used to improve conversion rates:

  1. Conversion probability prediction: you can train a regression or classification model that predicts a user's probability of conversion based on their characteristics and behavior on your site or application. You can use these predictions to target users most likely to convert with special offers or retargeting messages.
  1. Conversion factor analysis: using BigQuery ML, you can train a regression model to identify the factors influencing your conversion rate. For example, you can use the model to understand which pages on your site have the greatest impact on conversion, which products or which characteristics of your users are most associated with successful conversion.
  1. Acquisition channel and ad performance analysis: you can use BigQuery ML to create a model that predicts the likelihood of conversion based on the acquisition channel and ads a user has been exposed to. This enables you to understand which channels and ads perform best, so you can target your marketing efforts and optimize your advertising strategy accordingly.
  1. Predicting the long-term value of a customer: you can train a regression model that predicts the long-term value of a customer based on their characteristics and behavior on your site or application. This enables you to target the most profitable users for your business, and determine which marketing efforts are worth the "cost" of acquiring new customers.

To get the most out of BigQuery ML, you need enough quality data to drive your model. If you'd like to improve your company's performance, don't hesitate to contact us at. We'll help you not only to implement effective data harvesting, but also to optimize your performance according to your needs.

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Written by:
Camille Monneret

Camille, with 11 years' experience, drives service quality and continuous improvement, guaranteeing operational excellence and customer satisfaction. With expertise in Data strategy, Web Analysis, CRO and Automation, she supports companies in exploiting their data to optimize their performance. Camille is also training as a full-stack developer.

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