Prevent data quality issues with these six habits of highly effective data
Maintaining data quality across an organization can feel like a daunting task, especially when your data comes from a myriad of devices and sources. While there is no one magic solution, adopting these six habits will put your organization on the path to consistently reaping the benefits of high quality data.
How BD myShopi improved personalization while protecting consumer data privacy
BD myShopi connects consumers with exclusive deals from Europe's leading retailers. Learn how they leverage mParticle to present consumers with relevant offers while also supporting data privacy.
3 Tips on Growing a Startup from Nick Warner at Route
The future of every business is dependent on improving the customer experience. The first step to improving that experience is to know your customer. We spoke to one of the rising stars in growth hacking to learn his strategy.
What does good data validation look like?
Data engineers should add data validation processes in various stages throughout ETL pipelines to ensure that data remains accurate and consistent throughout its lifecycle. This article outlines strategies and best practices for doing this effectively.
How Reverb’s engineers optimized their data workflows at scale and gave users the rockstar treatment
With mParticle at the heart of their data stack, engineers at the world’s largest online music marketplace said goodbye to burdensome ETL pipelines, slashed their data maintenance workload, and unlocked new opportunities to build data-driven features into their product.
How to assemble a cross-functional data quality team
Smash your data silos and improve data quality across your organization by assembling a cross-functional team to own data planning.
Improve data quality with mParticle’s data planning infrastructure
Data planning is the foundation of any mature data strategy. But without the ability to translate a data plan into views conducive to each team's needs, it's hard to turn planning into action. Learn how mParticle's data planning infrastructure can help you get more out of your data plan.
How to build your first-party data strategy
The demise of third-party tracking presents brands with the opportunity to invest in modern data infrastructure and build trust with their customers. Learn how you can transform your data supply chain by developing a first-party data strategy.
6 tips for building a Customer Data Platform tracking plan
The value of your Customer Data Platform depends on the quality of data that you get into it. Here are six implementation tips you can follow to set yourself up for success.
Using first- and zero-party data to drive LTV growth
First- and zero-party data collection is becoming increasingly important as brands shift away from relying on third-party data. Learn how you can use mParticle and Iterable to collect high-quality data and use it to deliver personalized customer experiences.
How to leverage user data to improve customer service
Great customer service is an important driver of retention. Learn how you can connect user data to your support system in order to provide a better support experience and prevent churn.
What is Gatsby?
Gatsby is an open-source framework that combines functionality from React, GraphQL and Webpack into a single tool for building static websites and apps. Owing to the fast performance of the sites it powers, impressive out-of-the-box features like code splitting, and friendly developer experience, Gatsby is fast becoming a staple of modern web development.
Where should you be building your audience segments?
Every tool seems to offer segmentation capabilities these days. Disconnected audiences builders, however, can lead to overreliance on developer support and disjointed customer experiences. Learn more about data infrastructure and when it helps to centralize your audience segmentation.
Build your own walled garden
The data privacy landscape is constantly evolving. For brands to control their destiny, they need to invest in breaking their addiction to third-party cookies and building their own first-party data asset.
How to manage data across your tech stack based on customer consent
Great customer experiences are built on trust. Learn more about the tooling that can help you collect customer consent and manage how data flows between systems based on customer consent.
Capture page navigation events in a React Application
In a single-page application, understanding which pages your customers visit and the journeys they take through your website can be challenging. Here, we’ll look at a scalable and maintainable strategy for tracking page navigation events in a React application.
How to support your behavioral marketing strategy with a Customer Data Platform
Behavioral marketing has become a core competency for growth teams today. Shifts in privacy legislation and customer preferences, however, have changed the way in which teams must design contextual experiences. Learn more about how you can use a Customer Data Platform to support your behavioral marketing strategy.
Data-informed Decision Making: What does it mean, and should you be doing it?
Like data-driven decision making, being data-informed entails relying heavily on raw, measurable information to guide an organization’s direction. Data-informed strategies leave more room for opinions and past experiences, however, and recognize the limitations of using data alone to make every decision.
Why you should replace your analytics tracking code with a Customer Data Platform
Analytics tracking tools have become the standard for collecting user events and understand engagement. But in a rapidly evolving market environment, sometimes "standard" isn't enough. Learn more about how you can upgrade your data pipeline with a Customer Data Platform.
Why real-time data processing matters
Business-critical systems shouldn't depend on slow data pipelines. Learn more about real-time data processing and how implementing it strategically can increase efficiency and accelerate growth.
What is data orchestration
Data orchestration is an automated process in which a software solution combines, cleanses, and organizes data from multiple sources, then directs it to downstream services where various internal teams can put it to use. The purpose of data orchestration is to help a company make its data as useful and versatile as possible.
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.
How to harness the power of a CDP for machine learning: Part 2
Get a step-by-step guide to activating ML insights with mParticle and Amazon Personalize in part two of this three-part series.
How to harness a CDP for machine learning: Part 1
Learn how an infrastructural Customer Data Platform can help you overcome common machine learning challenges in part one of this three-part series.
How Airbnb scaled their growth strategy while increasing developer efficiency
Learn how Airbnb uses mParticle as the foundation infrastructure of their data pipeline, enabling them to evolve their growth stack and stay agile during tumultuous market conditions.
What is first-party data?
First-party data is the most powerful and reliable type of customer information, and it can give your organization many distinct advantages. Learn how to distinguish between different categories of customer data, and the ways you can leverage your company’s first-party data from multiple channels.
A single customer view is not the goal (it's the result)
Companies have long tried to establish a single customer view, but few have been able to put a solution into place that addresses the cross-functional needs of stakeholders. The problem is that a single customer view is often seen as the goal of processes, rather than the result. Learn how to create a single view of the customer by enforcing an organization-wide commitment to data quality and collaboration catalyzed by a sound data design process.
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.
3 data strategies for high-growth companies
As an mParticle CSM, it’s my job to help brands develop and implement a customer data strategy to drive growth. Here’s what I’ve seen work across industries and organizations.
COVID-19: Best practices and strategies for maintaining business continuity
With increasing calls to promote social distancing by enabling remote work, many companies find themselves at a loss when they consider how they will ensure that the quality and access to their data remains unchanged during this period of uncertainty. Maintaining business continuity during COVID-19—and any future global events—requires brands to invest in both process and infrastructure that can democratize data and access when the majority of the workforce is remote.
2020 Predictions: Customer data management practices
When it comes to customer data, much has changed in the past decade. With 2020 quickly approaching, learn about the predictions that will set the stage for the coming decade and what you should do to future-proof your business.
Money20/20: Innovation, AI, and data management
A recap of the need-to-know themes from Money20/20’s annual gathering of FinTech experts.
Amplify 19: Conference Recap
Your digest on the themes and announcements from Amplitude's annual product conference.
Opticon 19: Out-experiment. Outperform.
A recap of the need-to-know themes and product updates from Optimizely's annual conference.
The rise of big data in retail
The use of big data in Retail and eCommerce has opened up new possibilities for data-driven experiences, but few are leveraging engagement data to its full potential. Learn about the three fundamental data challenges retailers are racing to solve, their impact, and leading experts’ insight into the subject.
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.
19 Marketing Technologists to Watch in 2019
The 19 marketing technologists that are making an impact today and paving the path for the innovation of tomorrow.
Customer Data Platform use cases: Auto
This blog covers common use cases to help you determine which CDP features would most benefit your organization's business needs.
CDP use cases: Retail Banking
Retail banks need a customer data layer to meet customers' expectation for fast, flexible, personalized services. This blog covers common use cases to help you find the CDP that will help you meet current and future business needs.
Customer Data Platform Use Cases Guide: Media
Customers expect media brands to create seamless, contextual, and concurrent experiences across every device, which cannot be achieved with legacy systems unable to collect and activate data from every channel. Use these common use cases to help you determine which CDP features are relevant and find the CDP that will help them meet current and future business needs.
Customer Data Platform use cases: QSR
Meeting the QSR customer's expectation of fast, convenient, and tailored services requires a customer data layer able to collect and activate the right kind of customer data to drive initiatives and improvements. Read about the common CDP use cases QSRs are using to help you find the CDP that will help you meet current and future business needs.
Customer Data Platform Retail use cases
Retailers need a customer data layer able to deliver precise personalized engagements that don't break the marketing budget. This blog will cover common customer data platform retail use cases to determine which features are relevant and find the CDP that will help you meet current and future business needs.
Customer Data Platform use cases: Travel
Travel companies need a customer data layer as flexible and agile as their services. This blog will cover common use cases to determine which CDP features are relevant and find the CDP that will help you meet current and future business needs.
How to plan your integrated data layer
Learn how to develop an integrated data layer that aligns with your business and techical goals and provides you with a centralized source of clean customer data.
Why it's time to rethink your customer data strategy
Times are changing, and so should your customer data strategy.
Validity: The fifth V of Big Data
The Four V's of Big Data have been an industry standard since their introduction, but the increasing concerns about privacy recently have led to the need of a fifth V: Validity.
Postmates' user experience testing platform
Learn how Postmates uses mParticle to power their user experience testing platform, leading to increased insights, improved customer experience, and better product output.
4 Fundamentals for data-driven marketing
Maslow's hierarchy states that before catering you wants, you must ensure your needs are covered. Learn what your marketing needs are before embarking on your quest for data-driven marketing.
15 questions to evaluate CDP data preparation capabilities
Marketing technology analyst David Raab explains how customer data platforms can enable data transformations and how to ensure the right fit for your needs.
Overstock's machine learning personalization engine
Learn how Overstock implemented sustainable machine learning personalization systems to create seamless customer experiences and drive one-to-one engagement.
5 marketing attribution tips for eCommerce
Marketing attribution is one of the trickiest challenges online retailers face. Use these 5 tips to learn how your marketing affects your bottom line.
Plan your digital evolution
The marketing landscape is changing at a lightning pace. To take advantage of the martech boom, you need to plan your digital evolution.
7 lessons marketers can learn from Game of Thrones
David Spitz, CMO of mParticle, shares seven lessons from the seven kingdoms growth marketers can learn from Game of Thrones to take the Iron Throne.
Make audience data actionable with AudienceSync A/B testing
mParticle's A/B Testing capability helps make your audience data more actionable by providing a scalable approach to experimentation.
How the CMO of the world’s largest retailer approaches customer data
Chris Tung, CMO of Alibaba Group, describes the core tenets of his company's approach to customer data and how it's transforming consumer experiences.
The 10 commandments of mobile data strategy
We work with top app developers, marketers, and publishers every day. Here are some critical principles we’ve learned in the process.
Why thinking bigger about data strategy is your only real option
With every passing day the term “Big Data” seems to be going more out of style, but thinking big about data strategy is more important than ever.
Marketing data as a core asset
Data isn’t what matters, what you do with it is the important part. Conceive of and manage your data properly from the start to get the most out of your marketing data.
Stop your app journey from going off-course
Mapping mobile app data is not a once and done activity, it is a journey. This is true for many aspects of the app. So how can you avoid going off-course?