The customer data platform (CDP) may seem like a newer technology.
The reality is that the renowned solution has been around for more than a decade. And, during that time, the CDP has helped many mid-sized and large-scale organizations worldwide accelerate business growth — both in terms of revenue and operational efficiency.
Countless companies across various industries rely on the CDP to unify all their first-party customer data, gain a comprehensive single customer view, segment and analyze prospects and customers, and ultimately power their lifecycle orchestration efforts.
As BlueConic CEO Bart Heilbron noted for MarTech Outlook, a pure-play CDP — specifically, BlueConic — enables more efficient data liberation for companies.
In turn, the advanced business technology streamlines operations for all growth-focused teams and helps companies unlock new revenue opportunities and greater ROI.
"If you’ve always wanted to know what the CDP is all about — and how it can help you better understand and engage your customers — this guide is for you."
Continue on for answers to frequently asked questions about the customer data platform; a thorough overview of the past, present, and future CDP landscape; and in-depth insights into how your organization can make the most of the modern technology.
Key takeaways
The Single Source of Truth: A true, pure-play CDP is the only solution that reliably unifies all online and offline first-party customer data into a persistent, single customer view. This foundational capability is necessary for effective marketing, sales, and service.
Built for First-Party Data: With the decline of third-party cookies and the rise of data privacy laws, the CDP offers the ideal, proprietary hub for collecting, managing, and utilizing first-party data, thereby transforming it into a competitive advantage.
Agility Over Silos: The CDP acts as the central glue in a modern, best-of-breed martech stack. It breaks down data silos imposed by legacy systems (like CRMs or DMPs) and enables high-speed data flow and organizational agility.
Empowers the Marketer: Solutions with a Profile Database architecture empower non-technical users to execute advanced use cases—including multi-dimensional segmentation, lifecycle orchestration, and predictive modeling—without constant reliance on IT or Data Science teams.
What Is a Customer Data Platform (CDP)?
Let’s begin with the most obvious question on the minds of many business professionals today: “What is a customer data platform?” The answer depends on who you ask.
For starters, these are the CDP definitions from the well-known analyst firms:
Gartner: “A CDP is a marketing system that unifies a company’s customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages and offers.”
Forrester: “A CDP centralizes customer data from multiple sources and makes it available to systems of insight and engagement.”
CDP Institute: “A Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems.”
Unified customer profiles featuring all online and offline data, intricate audience and segment insights, and streamlined customer data activation (a.k.a. liberation).
That’s the fundamental functionality a CDP needs to be considered a true CDP today.
Having said that, the best-in-class customer data platforms today create operational efficiencies, mitigate consumer data risk, increase agility and flexibility, and — all in all — help business technology users achieve far more in their day-to-day.
(We’ll cover specific CDP use cases shortly.)
Aside from these distinct definitions, another common question posed by business professionals and leaders is, “Why was the customer data platform created?”
There are a few noteworthy trends that show why the pure-play customer data platform was such a necessary addition to the business technology landscape.
Why were CDPs created?
Aside from defining what a Customer Data Platform is, another common question posed by business professionals and leaders is, “Why was the customer data platform created?” The rise of the pure-play CDP was not a random occurrence; it was a necessary and direct response to several critical shortcomings in the existing marketing technology (martech) landscape. These noteworthy trends and persistent demands underscore why the customer data platform has become an essential addition to the modern business technology ecosystem.
#1: Unfulfilled Demand for a Single Customer View
Improved experiences for prospects and customers. Enhanced operational efficiency across the entire organization. Better strategic decision-making for marketing and leadership.
Those are just some of the biggest benefits companies (and, specifically, marketers) realize with a single customer view, per Experian Data Quality’s 2019 data management report.
Many martech vendors pitch prospective organizations interested in a single source of truth, their solutions offer the ‘complete’ 360-degree view of one’s customer base.
The truth is that only CDPs offer a full single customer view marketers need to understand their audiences and build successful lifecycle marketing programs (i.e., meeting buyers where they are through various customer touchpoints) based on consolidated customer data.
As BlueConic VP Marketing Michele Szabocsik noted, digitally native companies are successful with their strategies because of their first-party customer data access.
Access, which empowers their marketing, analytics, ecommerce, and data science teams (among others) to act on and react quickly to changes in customer behavior or preferences.
The customer data platform is the technology that unifies first-party data from across various data sources and channels to construct a comprehensive customer view for these companies.
#2: Data Commoditization & the Rise of Walled Gardens
Third-party data used to be a viable business asset for companies.
But with so many organizations tapping into the same third-party data sets and increasing privacy concerns, it became increasingly difficult for businesses to rely on this data to reach unique audiences and gain any semblance of “audience insights.”
Similarly, the walled gardens of Google and Facebook have prevented marketers (two-thirds, according to Sizmek research) from accessing (or, at least, properly making the most of) vital customer data they need to meet their customer acquisition goals.
So, where have these organizations turned to solve their customer data dilemmas?
First-party data, which is now critical for all growth-focused teams’ success.
With the right data strategy in place, they can secure behavioral, transactional, geographic, demographic, and other data points and straight from customers with their consent and access a proprietary, trusted database (not share with competitors) for their activation needs.
“Sophisticated marketers understand that first-party data is differentiating (because it is proprietary), relevant (it directly relates to the company and its customers), and consistent and high quality (it comes from the source),” Boston Consulting Group execs recently noted.
And the CDP offers growth-focused teams, the perfect place to collect, manage, and utilize their first-party data, as individuals’ profiles update persistently (i.e., in real time) and enables tech users to segment, analyze, model, and activate data as needed.
#3: The Platformization of Business Technologies
Simply put, the days of narrowly focused business technologies (e.g., solutions that focus on solving just one particular problem or need for companies) are over.
The era of “platformization” is upon us, according to Scott Brinker, the mind behind the MarTech Conference and ChiefMarTec blog. And vendors are adjusting accordingly.
Some tech providers remain convinced that marketing, CX, digital product/experience, and other growth teams want a suite of systems in an insulated tech ecosystem featuring solutions solely from these providers to simplify and streamline their work.
Other vendors, meanwhile — including and especially customer data platforms — are focused on developing ‘open’ tech ecosystems. These integrate with all business and marketing software, not just tools offered under the umbrella of certain providers.
It’s become evident most businesses prefer a best-of-breed tech stack approach today that revolves around a central hub that syncs with all in-house solutions.
And the customer data platform has proven to be the perfect hub for this approach, as it helps many businesses build truly flexible technology stacks that improve, not hinder, their efforts to understand and engage their target audiences.
In essence, a CDP acts as the glue between systems that didn’t exist before and makes it easier to remove or consolidate systems as the business requires over time.
When the essential customer data lives in one place and doesn’t put onerous structures or limitations on it, the organization’s agility when it comes to tech goes up considerably.
How a CDP works: The customer data platform’s architecture
The customer data platform continues to grow in popularity among companies worldwide. But it can be hard to distinguish between the various CDPs available in the market.
It’s the underlying database structure of a customer data platform that will shape the agility, scale, and scope of your brand’s CDP initiative. In turn, this will dictate how much return on investment you’re able to realize from the CDP in the near and long term.
There are three distinct database architectures offered in customer data platforms today that businesses should carefully investigate before purchasing one.
#1: Relational Database
Flexibility is a marketer’s best friend. Unfortunately, the relational database schema provided in certain CDPs don’t offer any for modern marketing professionals.
In the plainest of terms, a relational database doesn’t allow digital marketers to define their own taxonomy. That’s due to the highly structured nature of its data framework.
For instance, a CDP with a relational database needs to pre-define the relationship between unknown site visitors and a campaign in order to store their anonymous info.
“The campaign is the organizing principle — which makes sense, as most CDPs with a relational database foundation are actually more like campaign management tools than built-for-purpose CDPs,” our team noted in our database architecture guide.
#2: Event-Stream Database
With an event-stream database, you get nearly the opposite structure. It’s a framework that allows for exponential amounts of raw, unstructured customer data to be stored.
But there’s a catch.
It may seem ideal to get all first-party data synced into a central system. But this type of big data construct will require you to arbitrarily get rid of data to keep costs low.
The alternative? Continually add customer data over time as needed — and continually fork over some serious business spend to your database provider in question.
Another downside with this particular database architecture is it offers little in terms of flexibility or the ability to scale.
Users are stuck with the event-to-graph schema that comes with their event-stream platform of choice. Or, it falls on the marketing and/or analytics team to (painstakingly) map the customer data to a profile graph. (Which might not even be accurate.)
In other words? Companies will have plenty of attributes associated with their contacts using this kind of customer data platform. But they won’t be able to unify them into true, unified customer profiles easily, efficiently, or persistently. (A big problem, to say the least.)
Data scientists may prefer collecting and storing considerable amounts of audience data.
But the lack of practical, organized customer profiles — ones that only feature the most relevant data needed for efficient activation — can actually greatly hinder marketing.
“With an event-stream database, marketers end up collecting data they’ll never use, driving up the cost for data storage,” BlueConic CEO Bart Heilbron noted.
#3: Profile Database
With significant limitations of both the aforementioned database types, many brands have turned to (and continue to turn to) CDPs with profile-oriented databases.
The profile database falls somewhere in the middle of its counterparts.
This database constructs ideal customer profiles at an individual level (i.e., ones that feature solely pertinent data included, not every piece of PII and behavioral data available).
The unified profile provides you with the most comprehensive and up-to-date record of what you know about your customers. It is the proxy for the individual person.
The high quality of the profile data accounts for everything from individual consent status, to frequency of data updates, to identity resolution — all in support of your marketing programs: from lifecycle orchestration to behavioral segmentation.
Consider the CDP Institute’s definition above: Modern CDPs require persistent profiles and a method for storing customer data persistently without incurring excessive business costs.
Profile databases can translate attributes of an individual customer and store it persistently in the profile. This makes it possible to quickly and confidently query the data in support of a wide range of marketing activation use cases.
Not all CDPs can easily fit within each marketing organization’s unique ecosystem and martech stack. But some can easily adapt to any changes in that ecosystem.
In other words? A profile database scales for today’s goals and tomorrow’s ambitions.
Customer Data Platform Use Cases
What exactly is a use case? Ask a few members of a marketing team and you’ll probably get a different answer from everyone. Without an agreement on what a “use case” is, marketers can’t build out a CDP strategy or make the right technology selection.
BlueConic COO Cory Munchbach, defines a use case as such in her post for CMSWire:
“A use case describes the current state, target outcome, supporting activities and relative complexity required to successfully reach your [marketing or] business goal.”
Coming to a common understanding of your unique business use cases with your marketing team and leadership team will help you determine why you need a CDP.
For some inspiration, we previously held a customer data platform use cases webinar with some ideas on how you might leverage a pure-play CDP (And how many of these organizations have seen sizable increases in marketing ROI with one).
Here, we’ll cover a few high-level use cases that tie directly into the core functionality at the heart of CDPs — and how they facilitate far more effective work for growth teams.
Multi-Dimensional Segmentation & Segment Analysis
Advanced customer segmentation features within the CDP afford marketing professionals the ability to set up dynamic, multi-dimensional segments that can be based on any combination of attributes, and automatically add and remove customers based on their changing attributes or changing predictive behavioral scores.
“[Technology users] don’t simply want all of their data in one place,” BlueConic COO Cory Munchbach told AdExchanger. “They want it there for a reason, so they can do things like create cross-functional data segments and have the ability to distribute those segments to the systems they care about.”
Segmentation capabilities within a CDP enhance both marketers’ long-term lifecycle orchestration efforts and their short-term, integrated communications and campaigns.
Marketers, CX professionals, and other tech users can build, analyze, and take action upon segments without mandatory (or at least regular) involvement from IT or data science.
In turn, they can reduce customer data latency by eliminating the need to manually upload lists from various systems and sources across the technology ecosystem.
CDP Institute Founder David Raab noted leading CDPs are built for the purpose of “empowering non-technical users to extract segments and build predictive models and about delivering customer profiles and recommendations in real-time.”
Growth teams can also draw insights from analyzing their segments, discovering new segments, finding where segments overlap, and evaluating segment performance.
Consent Management Capabilities for Data Compliance
On top of segmentation capabilities, the top pure-play customer data platforms (see: BlueConic) have built-in consent management functionality that persistently stores individuals’ consent statuses and federates that data to other tools.
Ever worried you and your team may have included opted-out prospects from an email campaign (and, therefore, failed to comply with data privacy laws like the CCPA)?
Or, have you and your marketing organization thought about how long it would take you to pull data on an individual customer from all your systems, should they request it?
You’re not alone. That’s why CDPs like BlueConic offer consent management functionality.
With this feature, tech users can rest easy, knowing the consent status for each contact (i.e., who’s opted in or out of receiving messaging and granted brands the ability to use their data for other marketing purposes) is correct and updated in real time when it’s adjusted.
This saves technology users substantial amounts of time, streamlines their daily promotional activities, and guarantees compliance with the major consumer data laws.
As Cory noted for CMSWire, companies that prioritize consented first-party data collection and utilization “have even better data, because it is transparently collected and used.”
That is to say, implementing a CDP with consent management functionality enables brands to more confidently engage their audiences and, in turn, provide a high-quality customer experience, knowing their consent status is always accurate.
Advanced Recommendation Engines & Predictive Models
Delivering personalized experiences and messages in a targeted, timely manner to high-value individuals and accounts is the ultimate objective for marketers today.
Thankfully, these professionals can use the CDP to employ innovative recommendation engines that suggest the most applicable content or products to customers across channels.
“The CDP premise is rooted in a very real marketing challenge that brands endure on daily basis,” including and especially the need for “more granular personalization,” according to Forrester VP, Principal Analyst Joe Stanhope.
And with the right CDP — like one with advanced artificial intelligence and machine learning capabilities — those personalized marketing challenges for brands can be eliminated.
On-site dialogues, social media ads, email newsletters, and other go-to activities are greatly enhanced with the ability to serve individualized messaging to each customer based on their browsing behavior, transaction history, geolocation and more.
A CDP with AI functionality can enable these hyper-personalized, high-converting activities.
What’s more, CDPs with predictive machine learning models can aid marketers’ efforts to forecast specific customer behaviors (e.g., likelihood to buy or churn). This can then enable tactics and techniques that ultimately boost audience engagement and customer loyalty.
The CDP can help marketers integrate AI by providing out-of-the-box customer scoring or predictive behavioral models that use their unified database, reducing reliance on data science or analytics teams and allowing immediate activation of the outcome of models.
One of the most powerful applications of a Customer Data Platform (CDP) is its ability to enable true omnichannel customer journey management. By unifying all data into a single, real-time profile, the CDP allows marketers to move beyond siloed campaigns and orchestrate seamless, personalized experiences across every touchpoint, including email, web, advertising, and mobile.
Manage customer journey across channels
One of the key advantages of a Customer Data Platform (CDP) is its ability to enable true omnichannel customer journey management. By unifying all data into a single, real-time profile, the CDP allows marketers to orchestrate seamless, personalized experiences across every major touchpoint, including email, web, advertising, and mobile.
Unified Context: The CDP consolidates all behavioral, transactional, and preference data into a single, comprehensive profile. This ensures that when a customer switches from the web to their mobile device, the system instantly recognizes their identity, intent, and history.
Real-Time Activation: Using persistently updated data, the CDP can instantly trigger the following optimal action in the journey. For example, suppose a customer browses a specific page on the website. In that case, the CDP can immediately push a relevant ad to a social media Advertising channel or initiate a personalized Email sequence.
Message Cohesion: The CDP ensures consistency and manages customer fatigue across channels. It applies frequency capping and prevents conflicting offers, guaranteeing that a promotion sent via Mobile push is not simultaneously duplicated or contradicted by an Ad campaign.
Next-Best-Action (NBA) Logic: Advanced CDPs leverage AI/ML on the unified data to determine the Next Best Action for each individual. Instead of following a rigid path, the CDP orchestrates customized communication, optimizing the timing and channel based on real-time predictive scores.
By functioning as the central intelligence layer, the CDP ensures that every marketing system operates from a single source of truth, delivering consistent, relevant, and timely experiences across the entire customer lifecycle.
The benefits of CDPs
The primary advantage of implementing a Customer Data Platform (CDP) is the profound increase in marketing efficiency. By serving as the centralized, authoritative hub for all first-party customer data, the CDP eliminates the friction and latency that plague siloed systems. This immediate access to a unified customer profile empowers marketing teams to shift their focus from time-consuming data preparation to high-value strategic execution. Instead of wasting resources manually compiling data or targeting irrelevant segments, the CDP enables surgical precision in every campaign. This operational streamlining leads directly to better performance, lower costs, and a significantly higher Return on Investment (ROI) across the entire organization.
Here are the core benefits a CDP delivers:
Accelerated Time-to-Action: CDPs significantly reduce the time required to transition from a customer insight to an activated campaign (e.g., from days or weeks to minutes or seconds), enabling real-time responsiveness.
Optimized Ad Spend: By enabling highly granular, multi-dimensional segmentation, CDPs ensure advertising budgets are allocated only to the audiences most likely to convert, minimizing wasted ad impressions and improving overall campaign efficiency.
Enhanced Personalization and Relevancy: With a persistent, unified profile available to all downstream systems, marketers can deliver truly individualized messages and product recommendations across every touchpoint, boosting engagement and conversion rates.
Improved Data Governance and Compliance: The CDP centralizes and manages all customer consent and preference statuses in real-time, automating compliance with privacy regulations (like GDPR and CCPA) and mitigating legal risk.
Increased Agility and Flexibility: By facilitating a best-of-breed martech stack, the CDP enables organizations to easily integrate new tools or replace existing ones without disrupting the central data flow, ensuring the technology stack can evolve in line with business needs.
Deeper Customer Understanding: CDPs enable non-technical users to conduct advanced segment analysis and predictive modeling, resulting in a richer, actionable understanding of customer motivations and behaviors.
Comparing the CDP to Other Tech
The modern martech landscape is crowded, with thousands of vendors offering solutions across various categories—from business intelligence to marketing automation. This complexity often makes it difficult to discern how different platforms genuinely compare. The sheer number of technologies one can incorporate in their martech stacks is exhaustive. Just look at Scott Brinker’s Marketing Technology Landscape Supergraphic — now 8,000 vendors strong (and growing) — for proof of just how many tools there are.
However, the Customer Data Platform (CDP) diverges greatly from these seemingly similar technologies. As Gartner highlights, the core of CDP differentiation lies in the "productization of features" designed specifically to address marketers' struggles to extract value from existing data and technology investments.
With this crucial distinction established, we will now break down how the CDP compares to other common business technologies, illustrating how it empowers all growth-focused teams to gain more utility from their current tech stacks.
Customer Relationship Management (CRM) Software
Until just a decade ago, the CRM was the ultimate database. Put plainly, it was the primary tech businesses that turned to claim they had a “customer relationship management strategy.”
However, C-suites eventually realized that the solution didn’t enable their teams to activate customer data in real-time. Rather, the software was simply another form of a customer record.
This led to the emergence of numerous other integrations to address this problem, including the rise of marketing clouds and customer data platforms.
Raab explained to CMSWire how the CRM’s lacking (and dated) data architecture has led to lots of wasted business spend for large-scale organizations in recent years:
What’s really needed is systems that were designed from the start for multi-source data gathering, unification and sharing. That is what [the CDP] is promoting.
That said, CRM software still plays a crucial role in modern engagement programs.
Customer data recorded in a CRM can be synced into a CDP in real-time to help inform activation decisions. Data can flow back into the CRM as well when attributes for contacts from other martech connected with the CDP bolster those individuals’ profiles.
Data Management Platform (DMP)
We’ve outlined the myriad downsides of data management platforms. And we’ve officially concluded it’s (well past) time for companies to ditch the tech from their stacks.
The DMP is more or less an advertising-oriented solution for brands today.
It essentially offers marketers anonymized data based on third-party cookies (which will soon be gone altogether) with hashed or de-identified PII that’s available in the system for a limited time only (usually 90 days max).
Want to create segments in a CDP? You can construct them near-instantaneously.
In the DMP, however, segment-building typically requires a 24-hour processing window — a timeframe that can prevent real-time ad targeting and, in turn, deter conversions.
TL;DR: If you’re still relying on a legacy DMP to execute on various advertising use cases and develop custom segments, it’s time to retire the tech — and embrace a CDP.
Data Warehouse
“Marketer-owned and -operated”: That’s what the CDP is meant to be. Conversely, the data warehouse is an IT-centric database — and not marketing-friendly whatsoever.
As you might imagine, the “warehouse” name is apt.
The complex, specialized database technology is intended to host just about every data point acquired by a given organization (i.e., all data collected, aka “big data”).
From this monumental unstructured data set, IT pros can clean, arrange, categorize, and — eventually — share relevant customer data with growth-focused teams.
But this process takes time. (Lots of it.) We’re talking days or even weeks, depending on a given business technology user’s specific data-related request.
And that, of course, is a problem when it comes to taking action on the most recent updates to customers’ profile properties in one’s lifecycle orchestration strategy.
The customer data platform, meanwhile, has the means to handle the volume, variety, and velocity of first-party data from all systems in one’s tech stack.
What’s more, a pure-play CDP ensures it’s organized and structured in a manner that enables real-time unification (not to mention marketing activation).
Accessibility and flexibility: That’s what growth teams need from technologies today.
The data warehouse, while once advantageous for companies with mountains of customer data, simply doesn’t satisfy modern business and marketing requirements.
Why Marketing Clouds Are Adding CDPs
One other well-known martech category often compared with the customer data platform is the marketing cloud suite. (Many of which are adding their own versions of a CDP.)
Some clouds labeled the customer data platform as a “passing fad” just a few short years ago. Oh, how the times have changed.
Now, these vendors see the customer data platform has true staying power — and is only increasing in popularity, particularly among enterprise businesses.
Below are three reasons why the major marketing cloud players are officially entering the CDP space — and why they’ll always be inadequate compared to pure-play CDPs.
#1: Clouds (Finally) See CDP Isn’t Simply a Trend
The clouds have long prided themselves as being a “one-stop-shop” for marketers looking for an integrated suite of the core technologies they believed were required to thrive.
With suite adoption robust for many years — convenience being the main selling point to marketers — the clouds simply didn’t see the need to add CDPs to their collection of tools.
That is, until the clouds noticed adoption of customer data platforms — which offer true single customer views and more fruitful activation capabilities based on all-encompassing customer profiles regarding first-party data consolidation — was on the rise.
“Marketing clouds … have to grapple, all of a sudden, with the fact that the premise that they’ve been talking to the market really doesn’t measure up any longer,” BlueConic COO, Cory Munchbach, indicated in our webinar on why brands will abandon cloud suites.
#2: Cloud Vendors Fixing Self-Imposed Silo Issues
Many cloud executives don’t want to admit as much, but the nature of their suites impede tech users’ ability to truly reach and resonate with their audiences.
Why? Because even though there are plenty of powerful tools (e.g., email software, mobile tools, adtech, etc.) within their suites, none of them consistently “speak” with one another.
That means marketing and other growth-focused teams don’t have a legitimate single customer view to streamline their day-to-day engagement and analysis efforts.
Breaking down these data silos across the business requires a lot of resources, time, and energy on the part of marketing and/or IT — bandwidth few teams have today.
So, the clouds are now adding their own CDPs to help users unify their customer data.
But since they usually only allow customers to integrate data collected from tools in their suites, they’re forced to continue investing in cloud tech, not best-of-breed tools.
As long as this is the case, marketers like you will need a purpose-built solution (see: pure-play CDP) that unifies and activates data in a data- and technology-agnostic manner.
#3: Clouds Trying to Compete with Built-for-Purpose CDPs
Whether it’s through the addition of proprietary tools or acquisition of existing ones, Salesforce, Adobe, Oracle, and other leading marketing clouds will certainly continue to stake their claim to a portion of the martech marketplace (and, in turn, market share).
But the customer data platform is growing its footprint right alongside these suites.
43% of companies indicated they’d deployed a CDP in 2019, while 31% noted were in the process of doing so. — 2019 Gartner Marketing Technology Survey
50% of brands using a CDP stated their platforms have helped them achieve core business objectives. — 2019 The Relevancy Ring Customer Data Platform Buyer’s Guide
89% of B2B marketers said the most important CDP benefit was the ability to build a single customer view. — 2019 CDP Institute Member Survey
As long as built-for-purpose CDP adoption continues to rise at enterprise brands and mid-sized companies worldwide, the cloud providers will attempt to pitch their customer data platform offerings as just as capable as their pure-play peers.
The truth, though, many are just starting to understand what it means to build single view of the customer for tech users, while some pure-play CDPs have been at it for nearly a decade.
Analysts on the Customer Data Platform
You can tell where we stand on the customer data platform — both in terms of its efficacy for organizations across industries and how it stacks up to other business technologies.
But what do the prominent tech industry analysts have to say about the CDP? More specifically, just how valuable do they think the platform is for organizations today?
Here’s what a few chief analysts at some of the most renowned consultancy firms and industry groups have to say about the current state of customer data platforms.
Forrester: CDPs Must Continually Evolve to Aid Marketers
“Adapt or die” is already a common expression among marketers. Routinely modifying their marketing to better meet customers’ demands is a must to survive, let alone thrive.
The same mantra applies to martech as well. Specifically, the customer data platform, according to Forrester VP, Principal Analyst Joe Stanhope and Analyst Stephanie Liu.
Their 2020 CDP guide for B2C marketers explores how platforms must adapt to marketers’ ever-changing needs to remain relevant and worth the investment:
“To remain competitive … CDPs must deliver clear value to B2C marketers. They need to achieve functional competency and extend their automation and intelligence capabilities to drive better business outcomes for marketers.”
And they’re right. Providing capabilities like predictive machine learning models, customer journey analytics, and advanced segmentation is how the CDP can not only improve marketing KPIs, but also drive revenue and increase operational efficiency for brands.
It’s also how leading customer data platforms can separate themselves from the pack of competitors who lack this now-essential functionality for marketing professionals.
Gartner: CDP Enables Real-Time Customer Engagement
Gartner Senior Director Analysts Benjamin Bloom and Lizzie Foo Kune detailed in their 2020 Market Guide for Customer Data Platforms why the CDP doesn’t have to be the sole database in companies’ stacks, pointing to executives’ satisfaction with similar tech.
But the duo did note the CDP is the one type of tech that makes real-time marketing based on real-time data a real possibility — and no longer a pipe dream — for brands:
"The CDP is not necessarily a substitute for an enterprise’s database of record, but it can effectively ensure that customer profile data, transactional events and analytic attributes are available to marketing when needed for real-time interactions."
The analysts stated other solutions offer real-time marketing features.
They added, though, it’s the “packaging” and “productization” of these features in the CDP that compel many brands to invest in the martech to execute real-time marketing.
CDP Institute: Platform Provides Complete Customer View
Raab, meanwhile, has noted businesses in need of a single source of truth now grasp just how much the customer data platform can help their marketing teams achieve their goals:
"CDPs have become popular because they … give users open access to complete customer data. Buyers understand this to mean all data, with full detail, stored over time, presented in a unified customer view, and available to any system that needs it."
This insight shouldn’t come as much of a surprise, given the name of Raab’s group.
But his point is valid nonetheless: Business leaders are becoming increasingly aware of the CDP’s superior functionality, particularly data unification, compared to other tech.
Raab acknowledges there are certain customer data platforms that offer some, but not all, of the features and capabilities of CDP. He added that makes it especially important for marketers and their leadership to carefully evaluate the CDP landscape to find the best fit.
Speaking of which …
Finding the Best Customer Data Platform
Before you can build a CDP business case, you need to conduct a thorough examination of the existing customer data platform landscape to investigate all your options.
As with other tech tools your team onboards and implement in your stack, you’ll need to prepare an extensive CDP RFP that outlines your precise needs.
Additionally, you, your team, and your C-suite will need to list the most critical questions you have about the platform, including (but certainly not limited to):
What data does your CDP collect from other systems and channels? And what information and identifiers is it able to store about customers?
How many people should operate the CDP? Do we need train existing in-house staff or hire an outside specialist to handle our tenant?
What kind of customer support does your team offer? Do they only help users onboard, or do they provide ongoing assistance as needed?
How do your customers ensure their CDPs sync seamlessly with their other solutions (e.g. email service providers, CRMs, marketing analytics tools)?
What is the average time to value for your customers’ main use cases with your CDP compared to the typical time to value of other martech?
How quickly can customer data be ingested from and pushed to other business and marketing technologies? Do you offer real-time processing?
Does your CDP help ensure compliance with regulatory measures like General Data Protection Regulation and the California Consumer Privacy Act?
Explore BlueConic’s CDP today
Our customer data platform RFP toolkit provides additional questions you can ask prospective vendors. But it’s these kinds of Qs that can help you get going with your request for proposal outline — and on your way to getting the best-fit CDP for your organization.
Let’s fast forward to when you pinpoint the ideal CDP to take your business growth to the next level. Now, you can work on making the case to your leadership team to get it.
Downloading our CDP business case eBook is your best bet to crafting a compelling sales pitch to deliver to your executive team with growth-focused colleagues.
But there are several must-include details and insights you need to incorporate in your pitch deck to persuade decision-makers at your business to invest in the desired CDP:
Pinpoint your initial business use cases: You now know how world-class companies use the CDP to achieve their growth goals. Now’s your chance to relay how you’d use yours in the period immediately following onboarding (e.g., first three, six, and 12 months) to extract value from it and upgrade your lifecycle orchestration, predictive modeling, multi-dimensional segmentation, and analysis efforts.
Assess the CDP’s organizational impact: Beyond the engagement objectives you’ll achieve, explain how the solution can enhance operational efficiency companywide. Note which growth teams will “own” the system and data that goes in and out.
Detail existing tech shortcomings: No CEO wants to hear the (typically high-cost) tech they invest in doesn’t provide the desired ROI. But you can justify the allocation of spend for a CDP by pointing to other businesses’ successes with the platform — including competitors — to illustrate the platform’s efficacy.
Itemize the (presumably) numerous questions you have about the CDP for your RFP, continue to research the market in the meantime, chat with sales reps at potential vendors, and — ultimately — decide which one works best for your particular business needs.
That’s how you end up with a best-in-class CDP that can take your strategy to new heights.
FAQs on CPD
What does CDP stand for?
CDP is the acronym for Customer Data Platform.
What is a CDP in marketing?
A CDP is a packaged software system designed to unify a company’s first-party customer data from all online and offline sources. It creates a persistent, unified customer profile that is then made accessible to other marketing, advertising, and service systems. Its primary role in marketing is to provide the intelligence and data consistency needed to execute personalized, real-time engagement and lifecycle orchestration.
What is the difference between a CDP and a CRM?
The fundamental difference lies in their function and data focus. The CDP focuses on data unification, activation, and real-time customer behavior across the entire journey and is primarily used by marketing teams. The CRM (Customer Relationship Management) focuses on managing sales processes and service interactions, primarily storing known, structured data about sales leads and service cases. The CDP builds the complete customer view, while the CRM manages the relationship history.
Is a CDP the same as a data warehouse?
No, a CDP is not the same as a data warehouse (DW). They serve different organizational roles. The Data Warehouse is an IT-owned system designed for mass storage, querying, and reporting of all organizational data (raw, unstructured, and often slow for marketing). The CDP is marketer-owned, designed for the real-time unification, profile creation, and activation of customer data specifically.
How does a CDP create a single customer view?
A CDP creates a single customer view through identity resolution. It collects data from every system and touchpoint, using various identifiers (such as email, phone number, and cookie IDs) to match and merge fragmented, siloed records belonging to the same individual into a single, persistent "golden record." This record is updated in real-time, providing the most current and comprehensive profile available.
Do I need a CDP if I already use a marketing automation platform?
Yes, you most likely do. Marketing Automation (MA) platforms excel at campaign delivery (e.g., sending emails) but generally struggle to unify customer data from external, non-native sources (like your website or ads). A CDP acts as the intelligence layer above your MA system, providing the necessary unified and segment-ready data to effectively power the MA platform's personalization features, which would otherwise operate on incomplete data.
What are the main CDP use cases?
The core CDP use cases focus on activation and intelligence:
Multi-Dimensional Segmentation: Creating precise, dynamic audiences based on any combination of behavioral, profile, and predictive data.
Omnichannel Journey Orchestration: Managing and personalizing customer touchpoints across all channels (web, email, ads, mobile) from a single system.
Real-Time Personalization: Delivering individualized content, product recommendations, or offers instantly based on a customer's current behavior.
Advanced Predictive Modeling: Using unified data to forecast behaviors like churn or purchase likelihood, and activating those scores across the stack.
Consent and Data Governance: Centralizing and enforcing customer consent statuses across all integrated technologies for regulatory compliance.