Take mParticle for a spin with our new Free Trial and Growth Tier
mParticle's mission is to make customer data more accessible and actionable for the whole company, and this includes companies of all sizes. To that end, we're excited to announce our Free Trial and Growth Tier offerings.
You asked, we delivered. After surveying hundreds of companies, we learned that the demand for Customer Data Platforms (CDPs) is ubiquitous. The benefits of CDPs that focus on providing infrastructure-level solutions, such as mParticle, are clear, especially in a world where third-party data is disappearing. By leveraging CDPs, enterprise consumer brands are delivering one-to-one, personalized customer experiences at scale. There are two obstacles, however, that make CDPs inaccessible for many teams: timing and budget.
At mParticle, we are on a mission to make customer data more accessible and actionable for the whole company, and this includes companies of all sizes. What tends to be a nominal fee for many enterprises can be a significant expenditure for marketing, product, and data teams at smaller companies. To address these challenges, we are opening the doors to our product with an industry-leading, fully featured free trial. Our free trial gives teams time to evaluate mParticle with their current customer data strategy and ultimately prove business value. In addition to the free trial, we are excited to announce a new growth tier for growth oriented companies.
Unfamiliar with CDPs?
Let’s break down the customer data challenges companies of all sizes face and discuss how CDPs help.
1. Capturing data in real-time seems easy at first, but becomes hard as you grow
We’ve all heard the modern-day adage that data is the new oil. Treating data as a scarce resource, companies have been investing heavily in capturing all the data they can. Simply gathering data from a single source may not seem complicated; however, when you dig deeper, you begin to see more and more challenges, especially when you try to use customer data to drive business outcomes.
As you begin collecting data from multiple sources—mobile apps, websites, and data warehouses—bringing it all together and routing it to the right places at the right times is a prerequisite for powering personalized customer experiences in real-time. Without a CDP, instrumenting and maintaining downstream tools (messaging, analytics, data warehouse, etc.) and ingesting data from these tools to a central repository requires significant engineering resources. Now imagine when you need to implement new tools, track additional events, or add new data sources. Engineering is required to update or add to existing instrumentations. Furthermore, consider when inevitable integration (i.e., SDK) changes occur in downstream tools–engineering is called in yet again. With a CDP, you can avoid using valuable engineering resources on low-level work and reallocate that time innovating your core product.
2. Tying specific events and attributes to customers is essential but messy
To deliver digital customer experiences, data teams have to unify data from application stacks (e.g., mobile and web apps), downstream tools, and offline sources to single customer profiles. Consider when someone visits your website and starts browsing around. How do you tie the data you are collecting to the correct profile? What happens when customers make themselves known by signing in or purchasing an item? How do you include offline data from in-store purchases or other in-person interactions?
Customer Data Platforms that offer identity resolution solve these problems out of the box, relieving engineers from having to code and maintain the intricate rules required to build customer 360 profiles. Not to mention, there is an ever-growing set of regulatory requirements that govern how you can create profiles, especially with anonymous profile data. Infrastructural CDPs have built-in capabilities and expertise to address these challenges.
3. Avoiding garbage in, garbage out requires a lot of engineering effort
We work closely with data engineers, and one thing we hear repeatedly is that they are frustrated with the amount of time spent cleaning data. Even the best data teams can’t prevent bad data from entering pipelines. For example, consider an app developer that accidentally capitalizes a letter or misspells an event name. Once that app is in production, the data model will break, having severe downstream consequences.
Infrastructural CDPs have data integrity features that help teams build data models and represent those models both programmatically and within the user interface to automate data quality. As customer data flows through, CDPs can flag violations in real time and block/quarantine any non-conforming data for further inspection and replay. Automating data quality processes saves precious developer time and helps teams respond to bad data quickly.
4. Consumer privacy must be respected
The foundation of every customer relationship is centered around trust, and the responsible use of consumer data is critical to maintaining trust in a brand. As companies use more and more digital tools to connect with their customers, the risk of breaching consumer trust increases in kind. Furthermore, compliance with privacy regulations like GDPR and CCPA is not only a requirement for larger enterprises, but companies of all sizes. Privacy violations will not only damage your brand, but will also result in stiff fines.
CDPs offer built-in tools that let you control what data goes where (e.g., based on consent status) and give you the agility to make changes in real time. Customer Data Platforms minimize the likelihood of data breaches with end-to-end encryption, hashing and sharing minimal data. CDPs are typically hosted in multiple regions to comply with data residency requirements and can process data subject requests for stored data and on behalf of downstream tools.
5. Marketers typically don’t know SQL
Having clean data pipelines is not enough to enable marketers and other non-technical data consumers. To activate your data and get the most out of it, business users need accessibility and tools that allow them to create personalized, channel-agnostic customer experiences. Relying on engineering teams to procure data across your application and data stacks uses up precious resources and creates bottlenecks for business teams that need to move fast and adapt to changing business realities.
Customer Data Platforms have accessible user interfaces that make it easy for non-technical users to discover insights and optimize customer journeys across your brand’s customer touchpoints. CDPs eliminate data silos that downstream tools create by ingesting data from those tools to further optimize customer experiences across your stack.
Imagine a scenario where collecting data from all your apps, mapping it to customer profiles, making sure it’s clean and compliant, and then sending it to multiple downstream tools was made easy. Further imagine, non-technical business users like marketers self-serving real time customer data for advanced segmentation and insights. You can achieve this ideal state using mParticle.
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