Enterprise Customer Data Platform for Dummies

The Dummies Guide to Enterprise Customer Data Platforms

Marketing technology has been shown to increase lead conversions and average deal sizes as well as improve forecasting and customer segmentation. But a martech stack is only as good as the data going through it. A critical foundation of the martech stack has emerged from big data best practices – the enterprise customer data platform. It focuses on uniting, analyzing and activating customer and prospect data in a totally holistic way.

This eBook demystifies in straightforward terms customer data platforms and how they can empower marketers – to leverage valuable data and handle the segmentation that will enable better, more efficiently targeted marketing. Learn to integrate data from all sources, segment a buyer profile, create optimal buyer models, and much more. This guide:

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  • Covers working with data that historically has been tough to unify
  • Describes how marketers can control the data themselves without IT help
  • Gives strategies for automation to reach buyers in optimal ways to make a brand loved by customers
  • Includes case studies that prove the value of a customer data platform

Enterprise Customer Data Platforms For Dummies is the ideal guide to get you up and running on the critical foundation to activate data for cutting edge marketing campaigns and ultimately enhance your competitiveness.

The Power of the Enterprise Customer Data Platform

The use of data for personalization in marketing seems straightforward and simple, yet has eluded us for years. Creating a unified view of the customer has been a challenge for even the most advanced companies. One major reason for this is that existing solutions weren’t designed to hold the diverse data held in today’s cross-channel marketing operations.

The resulting explosion in marketing tech has arguably made the problem worse for the vast majority of companies trying to engage with their customers in this time of fragmentation of channels, increased number of datasets and (finally) significant focus on consumer privacy.

A very small set of companies have figured it out, though. These truly innovative and disruptive companies—Amazon, Facebook, Google, Netflix—are changing the way they do business by getting to know their customers as individuals by creating, using and constantly refining one unique profile that drives long–term engagement. We love these brands, and we are constantly finding new ways to engage with them (translation: spend more time and money). This small handful of companies continues to account for a large share of consumer attention. The question is: How can the vast majority of brands who have limited resources and tech talent compete?

Using data to drive every customer interaction, these digital disruptors inspire loyalty by personalizing our experiences in new ways that keep us coming back for more. This focus on the customer as an individual coincides with a resurgence in disruptive technologies like artificial intelligence (AI), natural language processing, and computer vision. All of these technologies are maturing—going from game–changing ideas to mainstream, foundational business tools.

That’s where the Enterprise Customer Data Platform (CDP) comes in. This sophisticated data–first platform allows marketing and product teams from any company to personalize and create relevant experiences for every customer, regardless of the data source—today’s Enterprise Customer Data Platform—and has the potential to grow revenue faster, connect internal teams across shared priorities and inspire customer loyalty. Teams who use an Enterprise CDP find that they rely on fewer fragmented tools in the quest for data-driven personalization that increases engagement, purchase and brand loyalty, and allows companies to better understand their customers as individuals; their desires, preferences, behaviors and intents.

The Enterprise CDP is finally a reality, and it’s just in time as today’s customers expect a whole new level of experience, personalization, and convenience—while the deluge of data we need to sift through continues to grow.