Marketers know that many of their objectives can be supported by harnessing and utilizing data across channels and each of these platforms has pros and cons. To start off, lets think about the problem many marketers are trying to solve, which prompts this question.

Your marketing department’s objectives are most likely some variation of the following: increase revenue, drive profitability and enhance guest experiences. Now think about how we typically attack each of these objectives (a sample will prove the point).

To increase revenue, we can acquire new customers and increase customer lifetime value (through loyalty, repeat purchases, increasing average order values, cross selling and upselling). This isn’t an exhaustive list, but you get the point.

Profitability can be driven through maximizing advertising efficiency (decreasing acquisition costs), driving conversion rates, optimizing merchandising to drive higher margin sales/activities and even process automation.

Enhancing guest experiences can be defined as how customers perceive their interactions with your company (Forrester 2010). Great customer experiences are valuable and useful, usable (easy, effortless, frictionless) and make your customers feel good (they are enjoyable). Knowing who your customers are, treating them well and making transactions wonderful and effortless (Starbucks) are some of the key elements to delivering great CX.

The common thread here is that harnessing and utilizing data is a key requirement across each of these objectives. Further, once the blocking and tackling is managed and you reach diminishing returns with your advertising investment and traditional activities – some version of personalization is sure to become a topic of conversation. For more info as to why, read my article on personalization. Personalization can lead to greater click through rates in paid media, greater conversion rates through dynamic merchandising and enhanced customer experiences by delivering more frictionless and meaningful interactions with your customers.

Personalization is about utilizing data, context and content to deliver timely, useful information to your customers in a format that they want. We live in an on-demand culture, where the new luxury is time, and convenience.

So…The increasing need for 1-1 marketing to drive optimization and experiences continues to drive marketers to ask…Do I need a CRM a DMP or a CDP?

First, lets explore the history of each of these systems.

CRMs were created to fulfill the specific purpose of collecting lead, account or customer information. CRMs collect clearly defined details for your data (1st party data) about known customers and prospects. Anyone who has actually deployed a CRM platform knows that they are great at managing tens of actions, thousands or even millions of times – but they aren’t that adaptable and the more you customize them, the more messy and unmanageable they become.

Recommendation: Please be clear about what you mean when you say “CRM”. It can be a solution (CRM Platform) or a strategy…As a strategy, think about it as a business’ philosophy about how relationships with customers and potential customers are managed. How will you talk to customers and potential customers across the entire customer journey and every touchpoint? What are the systems we will deploy to nurture and manage those relationships across the customer lifecycle? Your CRM strategy should enable your business to deepen its relationships with its leads, customers, service users, colleagues, partners and/or suppliers. Your CRM strategy should incorporate some mix of a CRM platform, a DMP and potentially a CDP as well. For the purpose of this article I will refer to CRM platforms as CRMs.

As the internet evolved and became the most trackable, efficient form of advertising, DMPs were created to exploit the benefits of internet-based marketing and are typically cookie-based, using anonymous IDs for profiles. Even as DMPs become more sophisticated, they were built on this foundation which makes it difficult if not impossible to create a 360-degree view of a customer – as they are mostly full of third party, anonymized data.

Additionally, back when CRMs and even DMPs were created, storage was expensive, slow and hard to manage as it was housed across multiple formats and machines. Enterprise Data Warehouses were coupled with Master Data Management solutions to store cleaned, structured data in a usable format for usage in CRMs.

I’m sure you can start seeing the problem this has created. A true 360-degree view of the customer is difficult when you have a CRM and a DMP. Why? because a CRM isnt built to know much about visitors to your website if they arent yet a customer and a DMP is full of anonymized data – you can see the gap here. If you don’t believe me, try to start adding advertising, social media and web behavior data to your CRM/DMP and deliver actionable campaigns then get back to me after your project reaches the double digit millions in a couple of years.

The limitations of CRMs (even when augmented by a DMP) are that they don’t have access to all the data (scope) and once you start customizing processes, they become a beast to manage, deploy against and upgrade (flexibility).

Treasure Data Blog did a great job at showing the evolution of CRMs, DMPs and now CDPs. The difference is all about scope and flexibility.

Enter BIG DATA. Big Data was such an overused term for a number of years and is now the butt of a lot of jokes across the industry. However, a major benefit of the Big Data hype cycle was the arrival and adoption of Data Lakes – super-fast processing power and access to data in multiple structures stored in one huge database.

Now that it is possible to quickly and cheaply manage extremely large amounts of data combined with smart engineering, CDPs were developed to combine, clean and link 1st, 2nd and 3rd party data, creating a truly unified, single view of the customer across the entire customer journey, accomplished by including raw event level data such as anonymous web visit and advertising behaviors. Even better – CDPs were designed to give the power to marketers (making them citizen data scientists, while being supported by data engineers and data scientists) to create and deploy campaigns across channels, leveraging awesome things like predictive analytics and machine learning.

While CRMs and DMPs can both do segmentation, CDPs can generate them on-the-fly and with more sophistication. Can a CRM be tuned into becoming a CDP? Possibly, but think of your CDP as the central nervous system for your marketing ecosystem – where all data flows and identities are managed – even when you don’t know exactly who someone is yet.

Example: When somebody interacts with your company, you create an action like a confirmation email from the ecommerce platform via the CRM since it is likely already connected to an email campaign tool. It’s also the place that the call center can access past customer interactions. Your DMP is part of your ad serving/targeting network and is connected to your DSP (demand side platform). In an ideal world, these systems are all integrated. That’s the core idea behind a CDP – collecting, unifying and delivering data driven campaigns.

Confusion Between CDPs and CRMs

Despite the emergence and current interest in CDPs, there’s a fair bit of confusion as to what exactly a customer data platform is, how it is different from a CRM and where it fits in your marketing technology stack. This is because most legacy marketers see a CRM as the solution for “managing relationships with customers” and CRM solution salespeople have gotten very good at selling the idea that their solutions can do all the things that a CDP can do. This isn’t necessarily wrong, however a CDP is fundamentally designed to create flexibility and consume all types of data across many structures whereas a CRM is fundamentally not. Why use a rock for a hammer if you can buy a hammer?

A Gartner survey found that 47% of marketing leaders said they already use a CDP, with another 19% searching for one. However, 52% identified Salesforce Analytics Builder (a CRM module) as their CDP. It’s clear that since CDPs are relatively new, many marketers don’t know the difference between CDPs and CRMs.

Warning: Some CRMs claim to deliver this same capability as a CDP – and to ensure you are selecting the right solution for your needs, make sure you have a great marketing technologist on your team to help navigate the current marketing technology world. Also maintain the discipline to employ a proof of value/concept approach and resist the temptation to boil the ocean.

Gartner (2017) states:

To be considered a CDP, it must:

  1. Be manageable by a marketer and not an IT analyst.
  2. Focus on known customers and prospects who have opted in to something or anonymous visitors to your site.
  3. Unify *there’s that word again!) customer data from disparate sources, linking identity, behavior, purchase and demographics together in a single record.
  4. Activate data — not store it for posterity — by creating actionable customer segments.
  5. Support real-time data streaming to take immediate action such as enable site or app personalization or trigger emails.

A CDP is worth investigating if your organization:

  • Has a trove of customer data, names and contact information, purchase history and cross-device logins
  • Wants to model and activate that data through personalized multichannel experiences
  • Is not interested in or already has a DMP for third-party data integration and programmatic media
  • Has multiple point execution tools that are not easily integrated
  • Wants more (marketer) control than a CRM system provides

(Gartner 2017)

The following table should help illustrate the differences:

Bottom line:

  • Use your DMP if you want to only do a better job of advertising.
  • Use your CRM if your use cases are more aligned with a traditional “sales” approach.
  • Get a CDP if you want a marketer managed solution that stitches together 1st, 2nd and 3rd party data in a single place, creating a unified 360-degree view of your customers, that is tightly integrated with your campaign level solutions to drive real-time or ad hoc segmentation and 1-1 personalized experiences across all touchpoints while enabling your data science team to directly support marketing initiatives.
  • If you are lucky, you have all three and your CDP is the central nervous system to your marketing tech stack.

The following figure comes from the customer data platform institute, and helps illustrate the functionality of a CDP: