Data quality vital signs: Five methods for evaluating the health of your data
It’s simple: Bad data quality leads to bad business outcomes. What’s not so simple is knowing whether the data at your disposal is truly accurate and reliable. This article highlights metrics and processes you can use to quickly evaluate the health of your data, no matter where your company falls on the data maturity curve.
Sollten Sie eine Kundendatenplattform aufbauen oder kaufen?
Kundendatenplattformen sind ein wichtiger Bestandteil der modernen Dateninfrastruktur. Erfahren Sie, was für den Aufbau einer Kundendatenplattform erforderlich ist und wie Sie feststellen können, ob der Aufbau einer eigenen Lösung oder die Zusammenarbeit mit einem führenden Anbieter der richtige Weg für Ihr Unternehmen ist.
Smartype Hubs: Keeping developers in sync with your Data Plan
Implementing tracking code based on an outdated version of your organization's data plan can result in time-consuming debugging, dirty data pipelines, and misguided decisions. mParticle's Smartype Hubs helps your engineering team avoid these problems by importing the latest version of your Data Plan into your codebase using Github Actions.
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.
Connected, by mParticle Episode 3: Leveraging emerging platforms with Miguel Navarro
In this episode of the Connected, by mParticle podcast we welcome Miguel Navarro, digital transformation leader and patented inventor.
How to implement an mParticle data plan in an eCommerce app
This sample application allows you to see mParticle data events and attributes displayed in an eCommerce UI as you perform them, and experiment with implementing an mParticle data plan yourself.
Should you be buying or building your data pipelines?
With demand for data increasing across the business, data engineers are inundated with requests for new data pipelines. With few cycles to spare, engineers are often forced to decide between implementing third-party solutions and building custom pipelines in-house. This article discusses when it makes sense to buy, and when it makes sense to build.
Three threats to customer data quality (and how to avoid them)
In this video, Jodi Bernardini, a Senior Solutions Consultant at mParticle, lays out three major threats standing in the way of customer data quality, and offers advice on how organizations can address them.
Ask an mParticle Solutions Consultant: What is data quality?
In this video, Andy Wong, a senior leader on mParticle’s Solutions Consulting team, discusses what data quality means, why it is important prioritize, and the benefits of creating a centralized data planning team to oversee data quality.
When to use a data lake vs data warehouse
Enabling teams with access to high-quality data is important for business success. The way in which this data is stored impacts on cost, scalability, data availability, and more. This article breaks down the difference between data lakes and data warehouses, and provides tips on how to decide which to use for data storage.
From spreadsheet to source code: Leveraging mParticle’s Data Plan Builder
Effective data planning is critical to ensuring that the data entering an organization's internal systems is accurate, reliable, and actionable. mParticle’s Data Plan Builder is available to help both mParticle customers and prospects with the key aspects of data planning: collaboration, implementation, and continuous iteration.
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.
Announcing the Pathways Partner Program and Partner Portal
mParticle is excited to announce our new Pathways Partner Program and Partner Portal, which will allow mParticle partners to access platform enablement and certification, co-marketing initiatives, co-branded collateral creations, and opportunity referrals in a central system.
How to prepare for your Customer Data Platform implementation
Implementing a Customer Data Platform at the infrastructure layer of your tech stack can transform the way in which you work with customer data—if you do it right. This article breaks down the steps you can take to prepare for your Customer Data Platform implementation and make the most of your investment.
What is data integrity and why does it matter for customer data?
Integrity is a good quality. Just like you want the people around you to have integrity, you also want the data on which you base strategic decisions to be of high integrity as well. That sounds good, but what does it mean for data to have integrity, and why is this so important? In this post, we’ll explore this broad and nuanced concept, define what it means in the context of customer data, and learn a strategy to ensure your customer data maintains high integrity throughout its lifecycle.
How do CDPs benefit engineers?
Customer Data Platforms (CDPs) have traditionally been thought of as tools that benefit marketers and product managers. But from simplifying data collection to enabling data-driven feature development, CDPs have far-reaching value for engineers as well. Learn more about the benefits of CDPs for technical teams.
What is a data tracking plan, and why should engineers care?
"Wait, why do we need this data again?" "Was that attribute supposed to use snake or camel case?" Data tracking plans keep everyone in your organization aligned on your data efforts, from the high-level strategy to the nittiest, grittiest details.
Leverage mParticle’s data quality developer tools to create, implement, and QA a data plan
mParticle makes it easy to create a robust data plan, implement it with ease, and seamlessly check incoming events to prevent bad data from making its way to downstream systems. Here, we walk through all three steps in a sample application.
Verbessert den Customer Lifecycle deiner mobilen App
Es gibt viele Frameworks zum mobilen Wachstum, die Teams nutzen können, um ihren Customer Lifecycle zu steuern. Nicht viele davon sind allerdings speziell für mobile App Marketing ausgelegt. In diesem Artikel erfahrt ihr, wie ihr die neue Marketing Master Map von Customlytics verwendet werden könnt, um euren mobilen Customer Lifecycle zu gestalten.
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.
Probabilistic vs deterministic: Which method should you be using for identity resolution?
The way in which you build your customer profiles can have big consequences on marketing strategy, data privacy, and customer relationships. Learn about the difference between probabilistic and deterministic identity models and how to determine which method you should be using.
Get ready for Apple’s App Tracking Transparency Framework
This week’s release of iOS 14.5 marks the beginning of enforcement of Apple’s App Tracking Transparency (ATT) Framework, announced last year. The ATT brings significant changes to the way iOS apps handle privacy and user tracking transparency. mParticle is continuing to roll out updates to help customers adhere to the new framework, as well as tools you can use to build a future-proof data strategy based on first-party customer data infrastructure.
How to set up your customer data team
In part two of our two-part series on making the most of your Customer Data Platform, we discuss how you can set up a cross-functional team of 'customer data excellence' to operate your CDP.
Relational vs. Non-Relational Databases
What are the key differences between these two main categories of databases, and how do you select the right type of database for different use cases?
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.
How to stop endless data shipping cycles
Engineers should ship products, not data. Product managers and marketers should experiment with data, increase personalization, and improve experiences. With a permanent data infrastructure, these goals are not mutually exclusive.
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.
Track User Events in Single-Page Applications
Owing to their fast load times and smooth user experiences, Single-Page Applications (SPAs) are now an extremely popular design pattern for developing websites. While building your site as an SPA offers clear advantages for your customers, it places challenges in the way of collecting robust analytics on user behavior.
Avoiding the growth trap
What do cattle farmers from the 1600s have in common with teams across modern companies? Both rely on shared resources that can quickly be depleted by an overzealous desire for growth, leading to the tragedy of the commons. Learn how you can avoid the growth trap by leveraging your customer data infrastructure and saving your engineering resources from depletion. Stop the vicious cycle, not the development cycle.
Modernize your audience segmentation strategy
Audience segmentation is key to delivering contextual experiences at scale. Learn more about how you can modernize your audience segmentation strategy and deliver experiences at the pace of your customers.
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.
Smartype Generate: Translate any JSON schema into data collection libraries for web, iOS and Android
mParticle’s Smartype is a platform-agnostic tool that can help every engineering team ensure data quality and consistency. Learn how to use Smartype to translate any JSON schema into custom data collection libraries for iOS, Android, and Web platforms.
COVID's impact on the financial services industry
In times of uncertainty, financial services companies are uniquely placed to enrich people's lives. Learn more about how the coronavirus pandemic has impacted personal banking and how financial services industry leaders are adapting.
How to use a CDP with your data warehouse
Data warehouses enable critical insights, and speed of data collection and stability of warehousing are important to their performance. Learn how you can use a CDP with your data warehouse to improve functionality and take action on business intelligence.
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.
Should you build or buy a Customer Data Platform?
Customer Data Platforms are a critical piece of the modern data infrastructure. Learn what it takes to build a Customer Data Platform and how to determine whether building a solution or working with a leading vendor is the right path for your organization.
Introducing Block Data: Diagnose, quarantine, fix, and backfill bad data
Bad data leads to bad decisions, but most teams are unable to address their data quality problems proactively in real time. Today, we are excited to announce Block Data, a new early access feature that helps teams automatically identify and drop unplanned data before it’s forwarded downstream, review and quarantine suspected bad data for investigation, and replay quarantined data once it’s been inspected and modified.
Seamless first- and third-party data enrichment
The newly debuted Data Partners Program is a group of enrichment data partners that meet the highest standard of data integration with mParticle’s CDP; these integrations allow third-party data to be collected and connected to the first-party persistent customer profiles existing within mParticle to provide a complete, real-time view of the customer which can then be used to seamlessly connect insights to a growing ecosystem of 250+ outbound integrations.
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.
Empower your team with better access to data
Put your team’s trust back into your data. Create a Data Plan to build and maintain context around your data and involve the right people in data decision-making.
Data Master 2.0: Ensure data quality
New Data Master features, now in Early Access, provide teams with an easy way to stop bad data at the source with data frameworks, data validation, and data quality enforcement.
How JetBlue improved their mobile customer experience
Learn how JetBlue uses mParticle to understand how customers experience the app on an individual basis, identify points of friction that affect customers' satisfaction, and test and deploy tools efficiently without adding third-party code that could impact end-user functionality
Connect your Looker Data Actions to mParticle
Take action on your Looker insights by connecting data to mParticle with Looker Data Actions.
When identity resolution goes wrong
mParticle CEO and Co-founder, Michael Katz, discusses why identity resolution is so critical for brands today, where mistakes can be made, and how mParticle can help.
Data is a team sport: Q4 feature announcements
Bad news for the rogue product manager, the lone wolf data scientist, the intransigent head of infosec, and the obstinate engineering manager: Data is a team sport. Learn about the forthcoming releases designed to help your whole team do more with more of your data.
Google Tag Manager: Scalable web and mobile tag management
The new Google Tag Manager integration from mParticle helps product and marketing teams easily launch pixels and trackers without pre-built connectors across web and mobile applications and collect customer data consistently and compliantly, at scale.
Mayur Gupta on marketing as a growth engine
At Acceleration 2019, Freshly CMO Mayur Gupta discussed how brands can thrive in a consumer-driven world by re-positioning marketing as a growth engine, one that is adaptable and in sync with the preferences and needs of consumers.
Consumer finance data management with a CDP
Leading consumer finance brands know that they need to deliver the best experiences to customers wherever they are, be it in-branch, on the web, or on mobile. Learn how Venmo, Quicken Loans, Paga, Stocktwits, and Abra leverage the mParticle platform as their consumer finance data management foundation.
Data Master: Great data, easier than ever.
Instrument and maintain a unified data strategy that is flexible, extensible, and fully transparent to everyone in the organization with Data Master.
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.
The Customer Data Platform vendor landscape
The customer data platform vendor landscape is confusing, but can be segmented along three dimensions: business model, data sources, and customer type. This post explains each one, so you can separate signal from noise and identify the right CDP for your business.
4 Ways a CDP helps customers embrace the GDPR
The GDPR is finally here. Learn how mParticle helps our customers not only support GDPR compliance but embrace it.
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.
Tag managers and CDPs: What’s the difference?
Both tag managers and CDPs help marketers collect customer data without relying on engineering, but that's where the similarity ends.
CDP ROI: Risk management
This blog is part three of a five-part series detailing how using a customer data layer can help brands comply with data privacy standards and mitigate risk across their portfolio of martech investments.
Bring your customer journeys to life
Understand customers' journeys to purchase in real time with User Activity VIew; access detailed customer profiles including identifiers, history, and beyond.
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.
7 ways the top quick-serve restaurant apps engage their users
Quick-serve restaurants lead the pack when it comes to engaging with customers via mobile apps. Read about how seven of the most successful QSR apps do it!