Machine learning

Growth

AI and Data Privacy: How to ensure your AI programs are safe, responsible, and effective

AI has the potential to transform marketers' business impact. But if you don't have a compliant data foundation, leveraging ML predictions for personalization can lead to breaches of customer trust. This blog post provides guidance on how you can use data and AI to strengthen customer relationships, and not disrupt them.

Growth

How the Wall Street Journal increases the value of their first-party data with AI

Partnering with mParticle Cortex, the Wall Street Journal have been able to generate predictive audiences based on first-party data, increasing advertising performance while also supporting data privacy.

Growth

How the New York Post tripled campaign conversions for its premium sports membership

Learn how the New York Post leveraged AI to improve campaign targeting and drive subscriptions.

Growth

How to improve ROAS with predictive advertising

As paid media budgets tighten and consumer expectations increase, delivering highly-targeted paid campaigns is critical. This article walks through how predictive advertising can increase paid efficiency, and how you can get started with AI without a team of data scientists.

Growth

How to use your customer data to predict customer churn

As the cost of acquiring new customers increases, retaining your existing customer base is becoming more important. This article walks through how you can leverage customer data to predict customer churn risk and prevent churn before it happens.

Growth

What’s the difference between predictive vs. prescriptive analytics?

Understand the difference between predictive analytics and prescriptive analytics and get tips on how you can begin using both types of AI insights to personalize the customer experience.

Growth

Transform customer data into predictive insights with an AI CDP

You don’t need an army of data scientists to generate predictive models from your customer data, or complicated pipelines to translate this intelligence into business value. mParticle is democratizing AI adoption, and turning what was once a pipe dream into a catalyst for your pipeline.

Engineering

Data enrichment and machine learning: Maximizing the value of your data insights

Data enrichment and machine learning are two techniques that can enhance the ability of your customer data to drive personalized experiences. While there is some overlap in the end goal of both approaches to enhancing data value, there are significant differences in the time, resources, and overhead they each require.

mParticle Product

How to harness the power of a CDP for machine learning: Part 3

Learn how you can activate machine learning insights across analytics and customer engagement platforms in part three of this three-part series.

Growth

Meet your marketing goals with customer data

Your marketing campaigns will only be as effective as the customer data that you use to power them, especially if leveraging AI/ML. Check out these tips and tricks to get your customer data in the best shape possible and begin accelerating your marketing strategy.

Engineering

Generate in-warehouse predictive audiences

Learn how Jayant Subramanian, data science intern, developed a proof-of-concept machine learning pipeline for predicting user behaviors from data pre-processing to model training and beyond using Snowflake and Apache Airflow.

Growth

Money20/20: Innovation, AI, and data management

A recap of the need-to-know themes from Money20/20’s annual gathering of FinTech experts.

Growth

Improve products with AI and Machine Learning

Traditional digital marketing can’t keep up with machine learning and AI marketing solutions. Learn exactly how these powerful point-and-click tools work and how they can help your team experiment at scale.

Engineering

Hyperloglog Algorithm: A must-know for data scientists

Hyperloglog (HLL), a powerful streaming algorithm, helps mParticle deliver real-time analytics products. Learn why it's a must-know for data scientists.

Engineering

The problem with app updates: Communication breakdown

While apps continue to make improvements from the time they launch, app stores don’t offer them a means to share progress within app updates.