The customer data platform (CDP) may seem like a newer technology.
The reality is 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 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 — at the end of the day — 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.
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.
#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 only CDPs offers 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.
And the customer data platform is the tech that unifies that first-party data from across data sources and channels to construct this 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 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.
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 types of distinct database architectures offered in customer data platforms today that businesses should investigate carefully before buying 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.
Look at the CDP Institute’s definition above: Modern CDPs need persistent profiles and a way to store that customer data persistently without exploding 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.
Comparing the CDP to Other Tech
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.
Examine the various categories — business intelligence software, marketing automation systems, customer experience management solutions, and the like — and you may even find it difficult to discern any differences among the numerous options.
And yet, the customer data platform diverges greatly from these solutions (and others) that, at first glance may seem the same, but actually fall short of the CDP in several areas.
As Gartner has said, CDP differentiation from other solutions comes from “productization of features and acknowledgment that marketers are still struggling to get value out of their enormous investments in both customer data and technology.”
With that in mind, let’s break down how the CDP differentiates from (seemingly) similar business technologies — and how it helps not just marketers, but every single growth-focused team, extract more value from all other systems in their 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 turned to claim they had a “customer relationship management strategy.”
But C-suites eventually realized the solution didn’t allow their teams to activate customer data in real time. Rather, the software was simply just another form of a customer record.
This led to the ascension of numerous other technologies to solve for this problem, including the rise of marketing clouds — as well as 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 has a role to play 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.
“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?
Our customer data platform RFP toolkit offers plenty more 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.