Choosing the right Customer Data Platform (CDP) by understanding the history of the industry

Today we’re diving into the sometimes puzzling world of Customer Data Platforms (CDPs). If you’re a marketer you might find yourself asking "Do we really need a CDP?" or "Which CDP is right for us?". Let’s take a friendly stroll through the history of this industry to help you answer those questions by understanding how core features came about and the unique problems they solve.

The dawn of "event tracking"

Let’s roll back the clock. Around 2009, the concept of tracking customer behavior on digital platforms began taking shape. Tools like Mixpanel popularized this idea, allowing businesses to gather valuable insight into customer interactions online. It wasn’t just about data for data’s sake but how you could use this information to improve customer engagement.

From analytics to marketing automation and beyond

When Vero launched in 2012, we took the concept of "event tracking" from the realm of analytics to marketing automation. We imagined providing a rich stream of customer data that marketers could use to send targeted messages to users. It was a game-changer, allowing companies to leverage customer actions on websites, mobile apps, and more to create personalized marketing experiences.

By 2012 the concept of event tracking had become so useful that tools across the marketing stack were adopting this approach. Analytics tools like Mixpanel and Amplitude, customer engagement platforms like Vero, Braze and CustomerIO, support tools like Zendesk and more were all capturing data in this way.

This led to an explosion of marketing technology providers all demanding the same customer activity data, captured using on-site event tracking.

Enter CDPs: a unified approach

The challenges of managing multiple tools and the issues of data inconsistency led to the birth of Customer Data Platforms (CDPs). Segment, a trailblazer in this field, provided a neat solution by offering integrated SDKs that replaced the numerous SDKs required by all of the individual marketing tools.

Picture this: instead of juggling ten different libraries, you now have a single library that does the heavy lifting. Not only does this streamline data flow, but it also enhances data completeness and accuracy. Segment empowered marketers to add, remove or change tools with ease and provided features to ensure your business’ data continues to flow seamlessly into all of the marketing tools in your stack.

Beyond event tracking with Extract, Transform and Load (ETL)

But data tracking didn’t (and shouldn’t) stop at customer interactions captured on-site or in-app. There’s a wealth of information in other business tools. A classic example is your payment gateway (Stripe, Adyen, etc.). Capturing data from these platforms can provide crucial insights into customer behavior and preferences, offering a complete view of your customer’s journey.

That’s where ETL (Extract, Transform, Load) tools came into play. Initially designed for Business Intelligence, ETL processes allowed companies to pull data from various platforms, transform it for consistency, and load it into centralized data warehouses. This approach helped businesses create comprehensive, accurate dashboards, providing teams with all the insights needed for strategic planning and decision-making.

The role of Reverse ETL

But having data sit comfortably in a warehouse isn’t the endgame. The development of reverse ETL tools like Census and Hightouch recognized the potential of activating this warehouse data directly into your marketing stack.

These tools functioned as bridges, channeling rich data back into platforms like Vero, Amplitude, and Zendesk. For marketers, these integrations mean you can leverage a complete dataset for unprecedented personalization and engagement strategies. Reverse ETL closes the loop, ensuring that data collected from all sources can be utilized effectively across various business systems.

The warehouse-native approach

More recently, we’ve seen the emergence of the "warehouse native" approach. A warehouse-native version of a software product connects directly to data stored in data warehouses owned and managed by customers in their private cloud.

By reducing data duplication across platforms, this strategy can save costs and bolster data security. At Vero, we support both this method and the traditional approach to meet diverse business needs.

Final thoughts

When considering a CDP, it’s about more than just solving data challenges. It’s about choosing the right tools that integrate seamlessly with your business model, industry requirements, and technical capabilities. Hopefully, this journey through the evolution of CDPs provides clarity and assists in building a marketing stack that harmonizes with your operational needs.

Got questions? Feel free to reach out. This industry history is a roadmap for understanding the intricate world of CDPs, and we’re here to help you navigate it.

Thanks for joining us on this enlightening tour!