Customer Data Platforms: How Marketers Now Compile a 360-Degree View Profile of Consumers in an Always-On Database

By Lori Cameron
Published 05/09/2018
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Gone are the days when marketers have to gather data from multiple databases scattered in countless systems to find what their customers want.

A brand new technology called the “customer data platform” puts all that information in one place, allowing companies to develop more effective ad campaigns and offer better customer service.

“Customer data platforms (CDPs) aggregate data from many different sources to provide a 360-degree view of the customer. These platforms are designed to be managed and used directly by marketers, and they eliminate the need to access multiple systems to create customer profiles, develop marketing campaigns, test the effectiveness of marketing strategies, and predict customer behavior,” says Seth Earley of Earley Information Science, author of “The Role of a Customer Data Platform” (login may be required for full text) from the January/February 2018  issue of IT Professional.

Functions of a customer data platform (CDP).

What is a customer data platform (CPD)

A customer data platform is a relatively new tool for marketers that is designed to cull far-flung data about customers across silos and systems and then provide a unified view of a customer and his or her behavior into an always-processing profile, according to the Customer Data Platform Institute (CDPI), which was founded in 2016 and is financed by industry vendors. Earley cites this organization in his paper.

“The CDP acts as a centralized clearinghouse and repository for all sorts of data from various internal and external systems. Consider any place where a customer interaction is recorded, tracked, or managed. Past purchases constitute a big category of customer behavior, of course. But so do social media interactions and website visits, even when nothing is actually purchased. Collectively, this data produces signals that can be thought of as ‘electronic body language,'” Earley writes.

“Some data is reasonably straightforward (such as name, address, and demographic details). However, some information requires processing and interpretation. Clickstream data, for example, tracks part of the customer journey and can be very informative, but understanding what it means requires effort and human intervention. Data about website behavior can be stored in a CDP, but the dataset is large and has numerous components that are time- and context-dependent,” Earley says.

What a customer data platform reveals

Earley lists four basic functions of a customer data platform:

  • They can summarize and analyze hundreds of log lines from a customer’s website visit to detect interests and trends.
  • They can accommodate different data types and formats that might have varying structures and naming conventions. whether that data comes through a live feed via an API or web service layer, a batch basis through a file transfer, chat logs, Facebook conversations, tweets, and even Instagram images.
  • They can cleanse and process data by eliminating redundancy and reconciling missing details or incorrect data with another system.
  • They allow other systems to access data, which saves, for example,  constantly repeating your personal information or order number over and over to different departments.

Why a CDP is better

Earley says, “A CDP can provide some of the functionality of other marketing systems and customer engagement platforms, but it is fundamentally different in design and function.”

Earley describes older marketing automation systems that can integrate with other tools but usually in a limited way. CDPs gather far more detail from many diverse systems and analyze it in more extensive ways.

“CDP tools are designed from the ground up to talk to other systems. They also retain details from other systems that the engagement or automation tool does not. This is valuable for trend analysis, predictive analytics, and recommendations that can leverage large amounts of historical data,” he writes.

Customers can be described with explicit metadata from a variety of source systems.

How CDPs tell a story about customers

Earley asks what kind of details can be gathered about customers to create a more personalized experience.

“It might be the customer’s age, or whether they were active on social media, or whether they had children. The CDP stores data about the customer that can be leveraged by various downstream systems to predict and influence the customer’s behavior,” says Earley.

This data can be culled from many sources including account creation, browsing behavior, shopping history, social media activity, and restaurant ratings.

Implicit metadata about a customer is based on judgment and/or derived from other data sources.

Earley divides metadata into two kinds: explicit and implicit.

Explicit data is easier to gather and analyze because it is usually provided to the company directly from the customer. It includes customer type (consumer/business/nonprofit), age, gender, language, location, income level, account, name, address, contact phone, email, account details, and so on.

Implicit data is gathered in other ways and includes activity and profiles on LinkedIn, Facebook, Twitter, and Instagram. It also includes loyalty, length of relationship, purchasing history, and prior responses to marketing campaigns. This type of data is gathered in a unique way and can reveal what motivates customers to buy products and services.

“Clickstream tells us something about how customers are consuming content and traversing the website: whether they click through an offer, whether they respond to a promotion, or whether they are able to complete their purchase. The data tells a story—the question is how to understand that story,” says Earley.

How CDP metrics analyze customers

After data is gathered, analysts must know how to understand it and what to do with it. Earley says these things change over time, which is why the questions have to be asked over and over.

For example, when analyzing metrics that reveal how quickly a customer leaves a website, an analyst might say “When users browse to a certain point and then leave the site, they were unable to complete their task. What can be changed to impact this behavior?”

Earley says the goal is getting to know the customer well in order to meet their needs.

“In the physical world, this is what a great salesperson does—they know the customer and offer solutions based on that knowledge. Digital technology is the stand-in for the best salesperson in an organization,” he says.


Research related to big data platforms in the Computer Society Digital Library

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About Lori Cameron

Lori Cameron is a Senior Writer for the IEEE Computer Society and currently writes regular features for Computer magazine, Computing Edge, and the Computing Now and Magazine Roundup websites. Contact her at Follow her on LinkedIn.