What is a Customer Data Platform (CDP)?
The Customer Data Platform landscape has exploded with over 100+ vendors claiming to be CDPs in the last 12 months. The first step to finding the right solution for you is to understand what a Customer Data Platform actually is and does. This page is designed to help answer those questions.
Table of Contents
- How do you Distinguish an Enterprise Grade vs a Mid-Market CDP?
- Most Critical Capabilities of a CDP
- How Long Does It Take to Implement a CDP?
What is a CDP?
A customer data platform (CDP) is a prebuilt technology used by marketers and customer experience professionals to understand their organization’s customers and scale personalized experiences across marketing, sales, and service channels.
The CDP does this by:
- Collecting customer identities and real-time interaction data from all first- and third-party data sources (through prebuilt data connectors)
- Stitching them together and removing duplicates to form a single, persistent history for each customer
- Empowering marketers and other business professionals through a user-friendly interface to analyze customers, segment audiences, and predict next-best-actions
- Enabling automated orchestration of 1:1 personalized campaign journeys across all marketing, customer experience, and commerce channels, including test design and measurement
What isn't a CDP?
Because of its generic name, CDPs are sometimes confused with other technologies. Here is a sample of common misconceptions:
- It’s not a data management platform (DMP)— which is designed to plan and manage paid digital advertising that is conducted on 3rd party websites (e.g. espn.com), search platforms (e.g. google.com) and social platforms (e.g. twitter.com) for anonymous individuals
- It’s not a digital event distribution platform— which is designed for IT organizations to transmit data from one technology to another after a digital event has occurred (e.g. triggering content IDs from your content management system to your workflow management tool once new content has been created, or triggering your ESP that a frustrated customer just complained to the call center)
- It’s not a digital personalization engine— which is designed to personalize the user experience on an organization’s first-party website.
- It’s not a master data management platform (MDM)— which is designed for IT organizations within large, multichannel enterprises to resolve customer identities (PII only) into a single golden identity (which can then be used as an input into a CDP).
- It’s not a multichannel marketing hub (MMH)— which is designed to manage and deliver marketing campaigns within email, social, text, and push channels (note: they are sometimes called marketing clouds).
- It’s not a customer relationship management tool (CRM)— which is designed as a sales and service tool for logging direct interactions with customers (e.g. customer complaint, price quote on a product, customer questions) and updating basic customer information (e.g. name, phone, email).
- It’s not a data lake— which is designed for IT organizations to store any type of enterprise data (e.g. financial, product, store, service, transaction, HR, customer, marketing) to support enterprise analytics and data science. Data is accessible only via programming languages (e.g., SQL, Python, R, Java).
Separate the CDP posers
from the players
3 Key Benefits of a CDP
- Incremental revenue generation—By providing meaningful insight into customer behavior and content preferences, CDPs enable marketers to unearth new opportunities and act on them quickly.
- Saving marketing costs—By leveraging a CDP’s customer intelligence, marketers can reduce marketing costs through suppression and optimization tactics.
- Increased operational efficiency—By integrating customer data and empowering self-service operations to business professionals, CDPs eliminate operational bottlenecks between technical and business teams.
“With [ActionIQ], we were able to marry the usability of a typical campaign management solution with infrastructure grade architecture and scalability. Meaning, they know how to make a useful product for marketers, and build tech you can actually integrate into a modern infrastructure.
Nick Rockwell, Former CTO of the New York Times
Why a CDP?
“Personalization is impossible if marketers don’t have the means to understand the needs of customers on an ongoing basis. Setting up a centralized customer data platform (CDP) to unify paid and owned data from across channels is essential to these efforts."
Customer Data Platforms empower business users and analysts to leverage all available data and insights to make every customer engagement count. They consolidate data silos, create a 360-degree customer view, and democratize access to customer data for purposes of personalizing interactions across marketing, sales, and service channels. Ultimately, a CDP gives marketers and customer experience professionals the ability to provide real-time personalization to customers by consolidating data silos and creating authentic customer interactions.
Why is Customer Data Important?
Customer data is important for three reasons.
First, consumers expect organizations to serve relevant experiences whenever they interact (thanks to companies like Amazon), and customer data is the fuel that enables organizations to identify the types of engagements each consumer values most.
Second, it’s more than just what experiences matter most, it’s also about being able to serve the customer a seamless experience no matter which channel they interact through. So if they were on the website last night but are calling into the call center today, the agent should have access to any frustrations the consumer was experiencing on the website last night to quickly provide assistance for their problem. The consumer should not have to re-explain their past behaviors each time they interact with a new channel/person.
The last reason why customer data is important is that marketing is expensive, and customer data helps you measure which types of mediums deliver the most ROI (e.g. display advertising, email, direct mail, etc.).
What is customer data?
Below are the types of customer data often managed by a customer data platform (CDP):
- PII info—Personal customer information such as name, address, phone, email, etc. (oppositely for anonymous users, CDPs will store device ID or cookie ID)
- Campaign and customer engagement info—Data reflecting the campaigns a customer received, the engagement within them, and other interaction data across marketing, advertising, sales, and support channels
- Transaction info—Examples include products purchased, channels transacted through, purchase prices, discounts used
- Metrics and scores—Examples include customer health scores, average click rates, customer loyalty status, lifetime value
- Demographic or firmographic Info—Examples include dwelling type, estimated income, company type, company industry, number of employees
- CSAT data—Examples include satisfaction scores from surveys and interactions with customer support associates
Customer Data Matters:
Supercharge Brand Loyalty With
Your Own Customer Data
9 Common Use Cases of a CDP
- Preventing Churn—Detecting at-risk customers and delivering automated messages across customers’ preferred channels to prevent churn
- Optimizing Prospecting—Identifying premier prospects via lookalike models and targeting them via channels like direct mail, digital advertising, or social
- Enabling Real-time Personalization—Eliminating one-size-fits-all campaigns and replacing them with 1:1 campaigns that include customers’ preferred products or preferred content
- Suppressing Customers—Suppressing customers in advertising channels who are already customers of their brand
- Eliminating Waste—Optimizing the frequency of touches to extinguish communications that don’t spark customers’ interests
- Modeling Propensities—Using customers’ propensities to target only those customers with a high likelihood of conversion for each type of content (while also minimizing discounts to those who don’t need them in order to convert)
- Democratizing Data—Enabling business users to determine the size of an opportunity themselves, instead of requiring technical resources to write SQL against a data warehouse
- Eliminating Dependencies—Enabling business analysts to adjust data definitions and data formats without having to submit a change request ticket to IT
- Increasing Agility—Increasing productivity and time-to-market by enabling marketers to design tests, measure performance, and iterate campaign setups, all without having to wait for technical assistance.
Reduce Costs & Drive Results
Across the Customer Lifecycle
How does a CDP fit my martech stack?
At a high level, CDPs are designed to improve the effectiveness of the martech stack. In more technical terms, CDPs often sit in the middle of one’s martech stack, acting as the intelligent command center that receives information from siloed systems (e.g. data warehouses, MDM, loyalty, marketing cloud, website, POS, etc.) and orchestrates a customer journey and next-best-action recommendations across downstream, customer-facing systems that deliver the final experiences to the customer (e.g. CRM, call center, POS, website, ESP, DSP, direct mail, apps, etc.).
For the benefit of the organization, CDPs enable a best-of-breed technology stack by being agnostic, i.e. seamlessly connecting to any source of customer data as well as any execution channel. This gives organizations the freedom and flexibility to plug and play innovative, best-in-class point solutions (such as a premier ESP or an innovative DSP) in place of expensive — and often outdated — marketing cloud suites that falsely claim to be great at everything.
Six Principles to Anchor Your
How do you Distinguish an Enterprise Grade vs a Mid-Market CDP?
Enterprise CDPs must cater to a distinct set of requirements, most notably around grander customer scale, increased data flexibility, greater technology interoperation, and more stringent data privacy. Read more to understand the details of each.
Fortune 500 organizations often have millions of customers (if not hundreds of millions). These companies often serve customers through multiple online and offline channels, meaning a CDP must be able to process petabytes of incoming data. If a petabyte of data is hard to grasp, consider that one petabyte is equivalent to twenty million four-drawer filing cabinets full of text. This means your CDP needs enormous horsepower to compute all of that data during ingestion, segmentation, predictive analytics, and activation exercises.
- Ability to ingest data in any format, which is necessary for two reasons: 1) the wide variety of data sources enterprises work with; and 2) the limited IT resources available to preconfigure them for insights and activation.
- Ability to resolve identities, given the probability that customers will represent themselves with small variations any time they interact (different email, different phone)
- Ability of marketers to configure data within the UI, eliminating dependency on technical resources
- Ability to connect with any system, since F500s have multiple channels across sales, service, and marketing.
- Ability to further organizations’ best-of-breed, hub and spoke strategies wherein they want best-in-class technologies at each corner of their tech stack, but with minimal overlap among them.
F500s are held to higher levels of scrutiny, given that they are often in the public eye (as publicly-traded companies) and possess greater quantities of customers to protect. This means they must hold certifications in areas beyond the GDPR and CCPA, extending into SOC Type II compliance.
Most Critical Capabilities of a CDP
- 360-degree view of customer (including sophisticated identity resolution)
- Customer analytics (descriptive, diagnostic, and predictive)
- Experience orchestration (including automation of multichannel campaign customer journey)
- User interface providing business-friendly access (removes dependency on IT)
Evaluate a CDP based on its ability to
unify data, analyze your customers, and activate personalized experiences
How Long Does It Take to Implement a CDP?
While CDPs are foundational technologies in your martech stack, they should not take an enormous effort to implement. Instead, CDPs should take anywhere from 4 to 12 weeks once the ink is dry on the contract.
If a CDP vendor suggests it should take longer, they likely do not have the flexible system architecture that streamlines implementation. By contrast, leading vendors accomplish such rapid implementation via a load-first, define-later architecture, wherein data is ingested in its original source format—saving the need to involve IT resources for data transformation before ingestion—and then modified later by a data analyst through the UI when it’s needed for use.
What’s most important when implementing a CDP is the change management needed to ensure its effective adoption. Organizations are doomed to disappointment if they think they can ignore humans’ tendency to resist change. Strategically, organizations need to invest in process iteration, skill adaptation, and sponsor-led accountability in order to be successful.
Step-by-step guide on Change Management
What is the History of CDPs?
Providing a 360-degree view of the customer has become increasingly important for marketers, most notably in the last 10 years as consumers engage through a growing number of channels, e.g. website, apps, call center, social, etc. This proliferation of channels means more interactions to keep track of and more customer records to resolve into a golden record.
CDPs arrived in 2015 to deliver the elusive 360-degree customer view. To appreciate what CDPs offer, let’s review the technologies that attempted such a quest before them—and the ways they would inevitably fall short of providing the single customer view:
Enterprise Data Warehouse (EDW)
- Biggest Weakness: Non-technical users could not access data (no user interface)
- Sample Vendor: Teradata
Customer Relationship Management (CRM) tool
- Biggest Weakness: Could not store data from all marketing , sales, and customer service channels
- Sample Vendor: Salesforce Sales Cloud
Multichannel Campaign Management (MCCM) tool
- Biggest Weakness: Could not store full depth of data, nor reduce reliance on IT for data and query iterations
- Sample Vendor: IBM Unica
Email Service Providers (ESPs)
- Biggest Weakness: Could not store depth or breadth of data
- Sample Vendor: Salesforce ExactTarget
Master Data Management (MDM)
- Biggest Weakness: Could not store data from all sources
- Sample Vendor: IBM Infosphere
Customer Identity & Access Management (CIAM)
- Biggest Weakness: Only stored ID’s, not engagement or transaction data
- Sample Vendor: SAP Gigya
Data Management Platform (DMP)
- Biggest Weakness: Could not store PII data, nor breadth of data sources
- Sample Vendor: Lotame
- Biggest Weakness: Non-technical users could not access data (no UI)
- Sample Vendor: Hortonworks
Multichannel Marketing Hubs (MMH)
- Biggest Weakness: Could not store data from all sources (no scale), nor deduplicate customer records (no resolution)
- Sample Vendor: Adobe Marketing Cloud
Digital Event Distribution Platforms (DEDP)
- Biggest Weakness: Could not store data from all data sources nor deduplicate customer records
- Sample Vendor: Segment