Tag

Data Planning

mparticle-ivee

Growth

How ivee built a universal source of truth for customer data

Learn how ivee established a cross-functional data planning process and improved customer data quality across their marketing stack with mParticle.

September 16, 2022

Engineering

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.

Sean Ryan – March 21, 2022
Sollten Sie eine Kundendatenplattform aufbauen oder kaufen?

Growth

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.

Joey Colvin – February 15, 2022

Engineering

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Implementing tracking code based on an outdated version of your organization's data plan can result in time-consuming debugging, dirty data pipelines, and misguided decisions.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.

Sean Ryan – February 11, 2022

Engineering

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.

Sean Ryan – December 15, 2021

Growth

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.

November 30, 2021

Engineering

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.

November 16, 2021
building-data-pipelines

Engineering

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.

Joey Colvin – November 10, 2021

Engineering

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.

Sean Ryan

Engineering

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.

Sean Ryan
data-lake-vs-data-warehouse

Engineering

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.

Joey Colvin – November 04, 2021

Growth

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.

Sean Ryan – November 03, 2021
reverb-data-workflows

Engineering

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.

Sean Ryan

Engineering

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.

Sean Ryan – October 20, 2021
mparticle-pathways

Company

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.

September 28, 2021
customer-data-platform-implementation

Growth

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.

Andy Wong – September 16, 2021

Engineering

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.

September 14, 2021

Engineering

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.

Sean Ryan – August 24, 2021

Engineering

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.

Sean Ryan – August 20, 2021

Data engineering

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.

Sean Ryan – August 20, 2021
mparticle-customlytics

Growth

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.

Anna-Theresa Priester – August 10, 2021
customer-data-platform-tracking-plan

Growth

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.

Glenn Vanderlinden – June 29, 2021
probabilistic-vs-deterministic

Growth

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.

Joey Colvin – June 16, 2021
iOS 14.5 will bring significant changes to the way iOS apps handle privacy and user tracking transparency.

mParticle Product

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.

Kale Bogdanovs – April 27, 2021

Growth

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.

Joey Colvin – April 19, 2021
Relational vs. Non-Relational Databases

Engineering

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?

Sean Ryan – March 16, 2021

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.

Sean Ryan – February 23, 2021

Engineering

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.

Sean Ryan – February 17, 2021

Growth

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.

Sean Ryan – February 02, 2021

Data strategy

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.

Joey Colvin – January 28, 2021

Engineering

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.

Sean Ryan – January 26, 2021

Growth

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.

Michael Katz – January 14, 2021
audience segmentation strategy

Growth

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.

Joey Colvin – December 21, 2020

Engineering

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.

Sean Ryan – December 15, 2020

Engineering

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.

Sean Ryan – November 30, 2020
covid 19 financial services

Growth

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.

Joey Colvin – November 24, 2020
cdp data warehouse

Engineering

CDP vs Data Warehouse: What's the difference?

Data warehouses enable critical insights, and speed of data collection and stability of warehousing are important to their performance. Learn the differences between a CDP vs data warehouse and how you can use both to improve functionality and take action on business intelligence.

Joey Colvin – August 18, 2022
single-customer-view-cdi

Growth

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.

Michael Katz – November 03, 2020
building a data platform

Growth

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.

Joey Colvin – October 15, 2020
block-data-quality

mParticle Product

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.

Niko Stahl – October 14, 2020
data enrichment platform

mParticle Product

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.

Abril McCloud – July 15, 2020
high growth data strategy

Growth

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.

Abhi Seeth
democratize data

mParticle Product

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.

Rashel Shehata – January 29, 2020
Ensure data quality

mParticle Product

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.

Rashel Shehata – November 19, 2019

Engineering

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

Abril McCloud
looker partners

mParticle Product

Connect your Looker Data Actions to mParticle

Take action on your Looker insights by connecting data to mParticle with Looker Data Actions.

Kale Bogdanovs – November 05, 2019
identity resolution platform

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.

Michael Katz – November 01, 2019

mParticle Product

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.

Craig Kelly – October 09, 2019
Mobile tag management

mParticle Product

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.

Shabih Syed – July 17, 2019

Growth

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.

Abril McCloud – June 12, 2019
finance data management

Growth

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.

May 29, 2019
mParticle product feature: Data Master

mParticle Product

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.

Rashel Shehata – January 30, 2019
cdp travel

Growth

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.

Abril McCloud
integrated data layer

Growth

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.

Andy Wong – August 28, 2018
The Customer Data Platform magic quadrant vendor landscape

Growth

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.

David Spitz – August 03, 2018
Learn how mParticle helps our customers not only support GDPR compliance but embrace it

Growth

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.

Tim Norris – May 24, 2018
Customer data strategy fundamentals: Business strategy and discovery

Growth

Customer data strategy fundamentals: Business strategy and discovery

Jillian Burnett – August 16, 2017
7 ways the top quick-serve restaurant apps engage their users

Growth

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!

Abril McCloud – November 27, 2017
7 lessons marketers can learn from Game of Thrones

Growth

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.

David Spitz – November 02, 2017

Growth

The role of mobile app data in driving revenue

Dave Myers – November 03, 2014
Make audience data actionable with AudienceSync A/B testing with mParticle

mParticle Product

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.

Tricia Prashad – October 19, 2017
15 questions to evaluate CDP data preparation capabilities

Growth

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.

David Raab – September 26, 2017
Customer Data Platform ROI: Risk management

Growth

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.

David Spitz – March 13, 2018
user activity

mParticle Product

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.

Rashel Shehata – October 18, 2018

Engineering

The App Gap: Why Customer Data Platform installations fail

David Spitz – February 14, 2017

Engineering

Make the right mobile architecture decisions

David Spitz – August 30, 2016
mParticle and Venmo Case Study Hero Background

Growth

How Venmo increased user engagement by 30%

Tricia Prashad