- How mParticle Came to Be
- The Need for Customer Data Platforms (CDP) Arises
- A New Era of Data Platforms
- Unifying Data Silos Helps Teams Make Better Decisions and Provide Better Customer Experiences
- Data Warehouse Ecosystem vs. CDP
- Brands Are Built on Trust, and It’s a Big Responsibility That We Take On
- Lessons Learned
How mParticle Came to Be
Interclick’s success was due in part to the data platform it built, which helped its customers unify data sets and operationalize them faster than the next best alternative. That innovation caught the attention of Yahoo, who bought the company in 2011 for $270M.
Two years later, Michael and brother Andrew joined forces again to modernize the data platform and how teams use customer data. This mission led them to create mParticle, a Customer Data Platform that provides brands with the infrastructure needed to unify data across all consumer touchpoints and optimize the customer experience.
The Need for Customer Data Platforms (CDP) Arises
The pains remedied by Customer Data Platforms were being experienced for some time before the acronym ‘CDP’ existed. While building my last company, Interclick, I realized that it was the way we used data to create successful flywheels that differentiated us from our competition. Our customers achieved value realization in part due to the treatment of data and the speed by which data could be operationalized.
After our acquisition by Yahoo in 2011, I was running a product team focused on personalization and insights. I found that accessing user-level data beyond web data was incredibly frustrating. I recognized that there was an incredible opportunity to leverage customer data originating from mobile and other connected devices and that legacy web solutions were unable to address these needs.
For mParticle, we were making a bet that there would be a platform shift from web-only to multi-channel digital experiences. The fragmentation that would emerge due to this shift would need to be addressed via a unified data layer. We saw the emergence of point solutions, but there was no data infrastructure.
We had to make a series of non-obvious bets that are now clear in hindsight but were somewhat contrarian at the time. Back in 2013, the conversation was app vs. web. Even Facebook went all-in on HTML 5 before walking that back and building native. So what everyone was predicting was that one form factor had to win and the other one had to lose.
We bet that it wouldn’t be an “either-or” scenario but rather an “and” scenario. The thing we underestimated originally was the universal nature of the problems we were solving.
A New Era of Data Platforms
mParticle is a Customer Data Platform, part of this newly emerging category of data infrastructure that helps brands address the nuances associated with the treatment and organization of customer data across different touchpoints and endpoints to improve the quality of the customer experience. It’s built on real-time streaming architecture to help teams ensure that latency doesn’t slow them down.
The platform vision is to help customers accelerate time-to-data-value. The value a platform like mParticle provides is getting data out of the platform and to a set of integrated applications and systems as fast and reliably as possible. From documentation to workflows, to troubleshooting, helping our customers accelerate time-to-value is mParticle’s North Star.
Part of accelerating time-to-data-value is solving the foundational aspects of customer data management. mParticle helps teams simplify their infrastructure by protecting data quality, providing integrated governance controls, and ultimately improving data connectivity to an expansive ecosystem of third-party tools and applications.
By streamlining the flow of customer data to and from various systems and applications, mParticle offers an end-to-end pipeline, which helps ensure data integrity so that teams can avoid garbage in/garbage out and integrated privacy controls teams support GDPR and CCPA compliance.
Unifying Data Silos Helps Teams Make Better Decisions and Provide Better Customer Experiences
Let’s start with the basic premise that companies are in business to create customers and create value for them.
Every interaction with your customers, thereby, creates data. Many teams are collecting customer data directly into multiple third-party tools to power certain use cases. This approach isn’t wrong, but it’s not optimal, as it leads to data silos that limit scalability.
When teams want to break through those ceilings, they need to think about managing customer data more holistically. But this requires teams to collaborate cross-functionally on central data infrastructure and systematize their businesses.
If you think about how teams work in any company with more than a handful of people, everyone is connected. No team can be successful without the help of other people and other teams. This means that the relationships across teams need to be underpinned by sound processes and high-quality data. Every interaction will have compounding effects, either positive or negative.
The most effective teams are the ones that create and implement a holistic customer data strategy, rather than operating with a siloed mindset in which each only thinks about their job and the tools they need.
For example, NBC Universal has dozens of different brands. With different digital experiences and properties across various screens and devices, they have unified all of their customer data into mParticle.
This gives them complete control over how data moves across systems and much better leverage over their data. The result is that it’s much easier for their team to model behaviors, drive the right type of personalization for their customers, and support data privacy.
Creating a Customer Data Strategy and Commitment to Continual Iteration
The data platform by itself is not a silver bullet. Customer data infrastructure like mParticle is about transforming processes that would otherwise be difficult, cost-prohibitive, or impossible. The problem is that many of these processes have been in place for some time, and there is a certain gravity that teams must overcome.
This inertia is the biggest limiting factor to teams becoming successful. So although there are a number of solutions out there, all with great features, it’s critical to remember that it’s not only the tech but also the process built around using technology that’s important.
To help our customers along this journey, we establish the KPIs, customer journeys, key strategies that businesses need to enable, customer segmentation strategies, the types of rich engagement triggers, what the technology stack looks like, and how it evolves.
Despite what some may advise, teams don’t have to (and shouldn’t want to) capture everything, so start with what matters. Over time, you may add more data sources, connect more integrations, or try a different approach to data flow orchestration. The goal for any team is to do as little work as possible for the greatest amount of impact.
Something exciting happens by starting with the finish line–how data will be applied and what tools will consume it. Teams naturally develop that 360° view of their customer. This is an important point: a 360-degree view of the customer results from a sound data infrastructure strategy, not the goal.
More importantly, it’s not really a 360° view. It’s a view based on the most relevant set of events, identities, and attributes. Creating that view and then figuring out what to do next will almost always backfire.
Data Warehouse Ecosystem vs. CDP
There is a popular dialogue happening right now about consolidating the data stack around the data warehouse. The argument for some is that the Snowflake ecosystem will subsume everything in its path. It will win, and everything else will lose.
Similar arguments have been made around other technologies in the past. We typically find room for fast and slow pipelines, generic data infrastructure, and customer data infrastructure.
The primary role of the CDP is to facilitate real-time data movement. It’s very different from what you get with a Data Warehouse, which is often used as the final resting place for your data.
Data warehouses typically will be used for all of a company’s data, not just its customer data; they are not built to be bi-directional and do not have real-time connections for live data. Nor do they address the idiosyncratic nature of customer data required to drive customer experiences. mParticle provides the necessary capabilities for the proper treatment of customer data.
Alternatively, there are a lot of companies calling themselves CDPs now, and it’s important to distinguish them. Most sit at the application layer focused on reporting, segmentation, and engagement. The data ingested by application CDPs is primarily used to power their application for a single channel, like email delivery or marketing output.
Brands Are Built on Trust, and It’s a Big Responsibility That We Take On
As mParticle’s primary job is to connect data to various systems to drive personalized customer experiences, we also have to protect our customers’ customer data. If brands are built on trust, we believe that inadequate data protection destroys that trust.
This belief is designed into the fabric of our entire platform. Our commitment to data security and governance allows our customers to sleep well at night, knowing that they aren’t exposing themselves to unnecessary liability.
If you violate things like General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), these are expensive mistakes. It’s critically important to integrate privacy frameworks and to be able to prevent certain data points from corrupting your stack. Application CDPs don’t address this, and neither makes an unbundled approach centered around the data warehouse.
We look at data as energy, and our job is to transform potential energy into kinetic energy by connecting customer data to various systems and applications in real-time.Michael Katz, CEO and Founder of mParticle
- Businesses are systems consisting of a set of connected teams and processes. Every interaction either strengthens the system or weakens it, making data the lifeblood of the system.
- Customer Data Platforms should simplify the flow of customer data between tools and applications, breaking down data silos and helping teams deliver the best experiences to their customers.
- The 360-degree view of the customer is the result of a sound data infrastructure, it shouldn’t be the goal.