Leading Customer Data Infrastructure Company Delivers Solutions to Improve Data Quality; Establishes Industry Standard for Data Planning Best Practices

mParticle, the largest independent Customer Data Platform, today announced new Data Planning tools and best practices to help marketers, developers and product managers realize the full benefit of customer data by simplifying data plan implementation and mitigating dirty data.

Only 3% of companies’ data meets basic quality standards leading to inaccurate and inconsistent information that leads to wasted marketing budgets, poorly executed customer experiences and hours of tedious debugging for developers, all of which restricts business growth. Ultimately, no matter how much data a company has, it’s useless if it’s not accurate or teams don’t trust it.

“Data Plans have enabled our teams to collaborate on identifying and resolving data quality issues early on in the development process,” said Jeremiah Mercury, VP Data Science at EPIX. “Since adopting data plans, quality violations have dropped significantly. We’re spending less time fixing data downstream and more time building new capabilities.”

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Data planning helps guide developers’ and marketers’ data-related tasks while also promoting cross-org collaboration and data minimization. mParticle’s Data Planning features enable this with several capabilities, including:

• Data Planning: Data planning serves as an interface for marketers, product managers, developers and analysts to collaborate on defining the customer data that is important to the business. By building this plan with mParticle, customers can alleviate data quality issues in downstream systems that data consumers (i.e., marketers) rely on, such as Amplitude, Braze, Snowflake and more.
• Data Validation: Data validation resolves data quality issues in real-time, enabling visibility of data quality by monitoring conformance to data plans in Live Stream. This saves developer hours and shortens the time to implement mParticle. It also increases the confidence in the data’s integrity across all stakeholders.
• Data Activation: When creating audiences, it’s helpful for marketers to know which attributes are available for each event in their data set, as well as what those data points mean, so that they can create compelling customer experiences and optimize spend.

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Frequently, for marketers, there’s inadequate support from technical resources and they have been burned in the past by bad data. This leads to mistrust given lack of transparency into the data to understand why campaigns are not performing well. On the engineering and developer side, building trust and alignment across data stakeholders is challenging as different teams use disparate tools and methods. Plus, for app developers there’s no indication that the data model is implemented correctly and cycles are spent debugging, testing and fixing broken implementations. All of this means lots of time and money lost cleansing bad data.

“The old adage for data of ‘garbage in, garbage out’ has only increased as more companies attempt to realize the value of their data,” said Chee Chew, CPO of mParticle. “mParticle’s Data Plans enable companies to trust their customer data, build rich profiles and personalize customer experiences.”

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