The Future of CDPs: Packaged and Composable
Just because you can unbundle a CDP, should you? By combining the best of packaged and composable approaches, you can configure a solution that enables you to accelerate time to data value while also reducing total cost of ownership.
CDPs: Streaming vs batch?
Many Customer Data Platform vendors describe themselves as real-time, but not all support the real-time use cases that businesses want to execute. This article breaks down the technical capabilities required support real-time use cases and shares tips on how to identify the right CDP solution for your needs.
Maximize the ROI of your MarTech stack with this six-step checklist
In today’s MarTech landscape, there is no shortage of tools you can use to engage with your customers and deliver personalization. But adopting tools alone by no means guarantees improved business outcomes. Here is a simple checklist you can use to increase the ROI of your MarTech stack.
Snowflake vs. BigQuery: What are the key differences?
Learn more about the differences between two popular data warehouse solutions, Snowflake and Google BigQuery, and understand how to identify which is right for your team.
How we improved performance and scalability by migrating to Apache Pulsar
We recently made a significant investment in the scalability and performance of our platform by adopting Apache Pulsar as the streaming engine that powers our core features. Thanks to the time and effort we spent on this project, our mission-critical services now rest on a more flexible, scalable, and reliable data pipeline.
Deliver personalized loyalty experiences with the mParticle PAR Punchh integration
Power better loyalty experiences by forwarding high-quality customer data from mParticle to Punchh, and ingest loyalty insights from Punchh to mParticle to keep 360-degree customer profiles up-to-date.
Four ways to drive retention with mParticle Lifetime Profiles for Audiences
Learn more about mParticle Lifetime Profiles for Audiences and check out these four ways you can use Lifetime Profiles to increase retention and customer lifetime value.
Supercharge your SMS campaigns with the mParticle Attentive integration
By powering Attentive's best-in-class SMS capabilities with real-time customer data from mParticle, marketing teams can deliver more granular personalization and increase the impact of their SMS campaigns.
How HBO Max launched personalized reengagement campaigns
With mParticle, HBO Max's marketing team is able to create audiences without engineering support and engage with their users more strategically.
Meet mParticle IDSync: The flexible identity framework you didn’t know you needed
When it comes to resolving cross-channel user events to a single profile, there is no one-size-fits-all approach. mParticle’s identity framework prioritizes flexibility, and empowers data stakeholders to take control over how profiles are created.
Connected, by mParticle Episode 10: Bridging data strategy and business needs with Human37
In this episode, we sit down with Human37 co-founders Julien De Visscher and Vincent Crochet to discuss tactics teams can use to get more data out of their customer data.
Google Tag Manager vs Google Analytics: What Are the Key Differences?
Google Tag Manager and Google Analytics are two different solutions, but when used in tandem they can help teams understand user engagement while increasing efficiency.
How does Google Tag Manager work?
Learn more about the benefits of Google Tag Manager and how it compares to other solutions on the market.
New ways to understand in-app behavior with Apple iOS 16
With the latest updates to iOS and Xcode, Apple has introduced changes to its operating system and developer environment that give engineers and product teams creative new ways to uncover user behavior.
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.