Getting Started with a Customer Data Platform (CDP)

In this step-by-step guide, discover if your business needs a CDP, and learn how to implement one

Martin Kihn
SVP of Strategy, Salesforce Marketing Cloud
Chris O' Hara
VP of Data & Identity, Salesforce Marketing Cloud

What is a Customer Data Platform?

A CDP usually includes a customer database, marketing automation, multichannel campaign management, and real-time interaction management. Essentially, CDPs are for when you need a marketing database with user-level data. To best understand this category of software, let’s look at some of the underlying challenges in marketing that resulted in its prominence.

The Customer Data Platform (CDP) is the hottest new piece of marketing technology.  In fact, CDPs are becoming ubiquitous in marketing and seem to pop up in every marketing-related report or search. According to the 2020 State of Marketing Report, among marketers who say they use CDPs, 86% are increasing or maintaining their use of them. This leaves many companies wondering if they need one too, with some asking, what is a CDP, anyway?

That’s what this guide is for. It’s your step-by-step playbook to help your organization decide if you need a CDP and how to best select and prepare your organization for one. Read the chapters below in accordance with your needs.

Chapter 1

Getting started with a customer data platform (CDP)



We live in an era where the customer is in control. Amazon can predict what products we will buy next, Netflix recommends the shows we like with great accuracy, and Uber lets us customize trips right down to the type of vehicle we want to travel in. Customers expect companies to have an intimate understanding of their preferences, want personalized experiences, and demand fast service. It’s no longer a marketing advantage to deliver on this — it’s table stakes.

When it comes to marketing, customers expect the interactions they have on a company’s website to translate to their mobile app experiences and even in-store visits. The problem is that, for most companies, those environments operate off different datasets — even though the customer is the same. Customers also expect their experiences to be consistent, and “in the moment” as they move from channel to channel. Most customer journeys involve over three different channels (for example, e-mail, web, and mobile app), and customers tend to move seamlessly and quickly between these channels. Most companies, however, don’t have these data environments connected in real time.

The result is disconnected experiences for consumers and the lack of a single source of truth about customers for the marketer.

CDP Basics

The first thing CDPs need to do is connect all of a company’s customer data in a single place. That means not only stitching together a single customer ID from many different CRM instances, but also tying together databases that traditionally don’t share customer data, like marketing clouds, service software, and ecommerce engines. We call that customer resolution.

The next thing CDPs have to do is reconcile the identities we have about our known customers (like email and mobile numbers) with what we know about customers before they share their data with companies (anonymous cookies and mobile device IDs, as an example). This way, we can start to associate an interaction that started with an email campaign and continued onto the website with the same customer. We think of this as a cross-device identity.

Once the CDP has created unified profiles of customers, the system has to make that data available in real time so companies can deliver personalized experiences. That means connecting customer data to many different types of systems – email-send engines, demand-side platforms, and content management systems.

In a nutshell, CDPs are concerned with these primary tasks: data collection, data unification, data activation, and data insights.

Use Cases

So, what do companies use CDPs for? Here are a few examples, and they aren’t all related to marketing.

  • Personalization: Say you see a consumer come to your website, browse a product, and leave. Wouldn’t it be great if you could tie everything you’ve learned about that customer to a personalized offer via email or push notification? CDPs make the unified profile available to all addressable channels, enabling personalization and relevancy. Customers who see content tailored to their interests are five times as likely to engage with a brand.
  • Suppression: Sometimes the best use of data in marketing isn’t to better target consumers — but to not target them at all. A unified profile that connects marketing and purchase data enables marketers to optimize their addressable spend by suppressing consumers that have already made a purchase, and redirecting those dollars toward new customers.
  • Insights: Most analytics systems operate in silos. What if an outdoor retailer had a customer’s marketing interactions tied with ecommerce data (purchase history) and website interaction data (products viewed multiple times) — and made that information available to a service rep in the call center? This type of personalization can turn a $15 per hour call center rep into a $100,000 a year salesperson.

Different Types of CDPs

CDPs are really just an evolution of CRM, finely tuned for the high-scale, real-time requirements of the digital-first modern B2C marketer. They’re a natural extension of the kinds of tools Salesforce has been building for enterprises of all sizes, all around the world, for decades. CDPs share CRM’s goals of managing customer data to drive relevant and productive experiences.

Unfortunately, the CDP market is very cluttered, including over 100 vendors (at last count by the Customer Data Platform Institute) who call themselves a “CDP.” No two are the same. Rather than focus on vendor-driven definitions, we asked hundreds of marketers what they need from a CDP and quickly came to realize there are not one but two different types of CDPs.

  1. Insights CDP — Builds a “single view of the customer” by integrating data from multiple disparate sources, handling integration and data management, and enabling analytics and activation.
  2. Engagement CDP — Helps users with real-time personalization, for example, of websites and mobile apps, and powers real-time next-best-offer and action engagement.

The vast majority of CDPs on the market today are either insight CDPs or engagement CDPs — not both. We believe a true enterprise CDP must encompass both insight and engagement.

Next we’ll look at how companies leverage CDPs to go beyond marketing and advertising — and use connected customer data to tie together their organizations, create cross-company insights, and start to value customer data as something they can put on the balance sheet.

To learn more about demystifying the customer data platform, check out this blog post by Salesforce’s SVP of Product Strategy.

In the next chapter, we'll look at how to build a business case for data transformation and a CDP. We’ll look at how companies leverage CDPs to go beyond marketing and advertising — and use connected customer data to tie together their organizations, create cross-company insights, and start to value customer data as something they can put on the balance sheet.

Chapter 2

How to Build A Business Case for Data Transformation and a CDP

When starting a new data transformation, you need clear goals. This may sound obvious, but even some of the world’s biggest companies have stumbled by embarking on data transformation without clear goals in place. Even more, companies have mistakenly assumed that simply licensing a CDP will create tangible transformation. But it’s never that easy.

To make sure you’re ahead of the curve, establish clear goals, a KPI framework, and data alignment. This ensures your new digital transformation will be off to a great start.

Establish clear goals

Technology provides companies with great new tools, but these great tools need to be deployed with measurable goals and tied directly to the company’s business strategy.

Any company can say they’re licensing a CDP because they “need better tools for targeting online consumers.” That’s not a specific or measurable goal.

Clear goals like these will put you on the path to success:

  • We want to increase the amount of time customers spend on our website by 20%
  • We want to increase our video ad conversion rates by 30% through more granular customer segmentation
  • We want to serve personalized content to 100% of visitors we can match to an audience segment to drive 50% more conversions.

Consult the right stakeholders

When you set your goals, make sure that the right stakeholders are in control of the process. If your IT team is buying the software, but it’s going to be primarily used by your media team, then there’s a disconnect. IT teams know as much about advertising tactics as media teams usually know about writing Javascript. Get the right team on board and head into your data transformation with a clear set of KPIs that are tied directly to business success. Start by making sure you see ROI from the software and then align its function to your overall business strategy.

As you develop your strategy, make sure:

  • You can count or list all of your data transformation goals — this way, you can keep them organized and specific
  • Your goals are aligned to use cases or examples that have worked for others
  • Each of your goals has a statistic or measurable quantity associated with it
  • Everyone understands which goals are most important — and less important

Track performance to meet goals

Once you’ve established clear goals with measurable outcomes, you’ll need to consistently track your company’s performance as it works to meet those goals. To track the effectiveness of your data transformation, you’ll need a clear performance framework and KPIs to align with.

Sample KPIs include:

  • Expand addressable customer segments from 10 to 100 in three months
  • Reduce nonhuman digital ad traffic from 35% to 5% in six months to save $1.5 million
  • Reduce website bounce rate by 25% by delivering personalized content
  • Suppress known buyers of specific SKUs from being exposed to cross-channel messaging for those products to save money in addressable media spending 

Your team needs clear benchmarks for what success really looks like. This will allow them to align their work to precise metrics that prove your data transformation is working — which will let your investment continue.

It’s also essential to tie the success of your data transformation to your company’s overall business success. Vague goals like “better segmentation” aren’t relevant to your executive team’s success metrics. When you link data goals with higher-order business goals, you’ll increase the effectiveness of your data transformation project and garner more executive alignment and budget support.

An example of a clear data goal aligned with business success is:

  • We’ll increase marketing effectiveness by 15% by driving customer acquisition through more efficient digital channels (like Instagram) instead of expensive traditional channels (like television)

Make sure your executive team knows which use cases you’ve based your goals on, and understands the value of your data transformation goals. It’s essential for your data transformation to be fully aligned with your company’s overall goals.

In our next chapter we’ll discuss how people fit into the data transformation process. Once you’ve built a compelling business case for a CDP, you’ll need to identify key stakeholders to work with. This all starts with creating a data center of excellence.


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Chapter 3

How to Set Up a Cross-Functional Team for CDP Success

Over the years, we have seen hundreds of companies declare their commitment to using data to drive marketing strategy. The ones that find success are those that invest in the people and processes required to make it stick.

In all cases, change management requires clear leadership from the top and the middle. But who are the stakeholders in your company who must come together to create true change management around data? It all starts with the formation of a data center of excellence.

Developing a data center of excellence

A serious team approach is required to build what we call the data center of excellence (DCOE). The DCOE is usually composed of internal folks from the business, analytics, and IT teams; smart consultants for change management; systems integration partners; and agencies. The companies who adopt such an approach reap near-term value in the beginning stages of their journey, which more than funds all of their subsequent efforts.

We think of the pillars of organizational adoption as people, process, and technology. There is no partial credit: Getting one or two of those right and the other wrong leads to failure.

It starts with people. When looking across the thousands of data software implementations we have supported, the companies that get value the quickest have implicitly or explicitly created a DCOE that defines data strategy holistically and assigns ownership clearly across key stakeholders in the organization.

Four steps to establish a data center of excellence are:

  1. Take a team approach. To be successful, you’ll need to bring together internal and external partners. Gather their input on the types of data they want to capture and how they expect to use it, and build consensus on a common set of goals.
  2. Establish detailed processes. Assign clear ownership to every step, identify key handoff points, and enact definite rules for communication.
  3. Adopt technology to empower people and processes. With the right team and process in place, technology will power and scale their efforts.
  4. Start seeing value. Companies that start with a team approach, establish thoughtful processes, and adopt the right technologies quickly see value.

Aligning internal stakeholders

As we mentioned, a successful DCOE requires the collaboration of a full team of internal teams and external partners. Let’s focus on how to align internal stakeholders from your marketing business, analytics, and IT/CRM teams.

Marketing Business

CDPs in their initial incarnation are designed for marketers. Although we believe they will be used throughout the enterprise, marketers find the ability to integrate and harmonize data very appealing and will likely be a primary source of support (and challenge) for your CDP project.

  • Focus on supporting things that improve business value. Marketers are practical people, and their work includes more P&L-related items every year. To succeed, CDPs will have to help marketers execute business goals such as acquisition, conversion, and retention. Starting with major sources of value and the data required to improve marketing outcomes is a great beginning. Orient “success” around the marketers’ success.
  • Make sure the tool is useful widely across the business. CDPs should be flexible and useful to technical users, but they are primarily a business user-focused system. Integration and harmonization can be rule- or ML-based, but it should be intuitive. The same goes for segmentation and activation. Day-to-day users are important voices during planning.


Today’s analytics departments come to the table with a great deal of enthusiasm for data centralization and closer connections to the media team, which is a rich source of user intent data.

  • Understand and account for your analytics team’s top priorities. Many teams are tasked with combining rich, structured data they get from CRM, commerce, and offline sales data with newly available, fast-flowing media and unstructured data. Like their business counterparts, analytics teams have embraced many new technologies over the years for various use cases, and continually seek ways to make their insights easily digestible to management and other stakeholders.
  • Provide the tools and flexibility analysts need. The modern analyst needs flexibility to draw from a single source of organizational data to run custom reports, perform modeling, and drive deeper levels of analysis. The analyst is concerned with uncovering insights, using data to identify better customer experiences, model customer lifetime value, propensity to purchase, and richer segmentation.


The modern CMO cannot execute a data strategy without being conversant in the technology tools and tactics required to execute it. In a perfect world, the role of chief data officer (CDO) would oversee the functional areas of both IT and CRM and serve as the ideal partner to join colleagues in media and analytics in a DCOE. Because not every company has made that leap, we often see both groups represented as IT.

  • Remove any barriers between the business, analytics, and CRM to achieve alignment. IT departments are often charged with making sure the visions of the media and analytics teams conform to the overall corporate technology structure and segmentation strategy; they are responsible for aligning the investment goals of the group with the corporate technology and infrastructure budgets.
  • Empower IT/CRM to serve as strong stewards of their customer data. Technology teams ensure that projects proceed with strong data governance, privacy rules, and existing security protocols. This is especially critical in a world in which privacy laws like General Data Protection Regulation (GDPR)

Put stakeholders from these groups together around a common set of goals, and you have the framework from which true data-driven transformation can evolve.

In our final chapter, we'll discuss purchasing and implementing a CDP.




In this resource guide, we’ve unpacked what you need to know about CDPs and how to successfully begin the journey in preparing for a CDP. Learn more about Salesforce’s CDP, Customer 360 Audiences, as well as the latest on customer data management technologies in the resources section below.


More Resources

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