Customer Data Platforms (CDPs) are here to stay; the CDP Institute estimates that the industry revenue will reach $1.3 billion in 2020, a 30% increase over 2019. Although the term was coined in 2013 to describe several types of marketing systems that shared the ability to build a unified customer database, there are still some misconceptions of what a Customer Data Platform is.
But worry not, I will clarify 9 CDP misconceptions in today’s post.
Brace yourselves, it’s a long post but very enlightening.
Ready? Let’s dive in!
Table of Contents
Before we dive right in...
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#1 A Customer Data Platform is the same as a CRM
The first of the 9 CDP misconceptions is that a customer data platform is the same as a CRM. A Customer Data Platform (CDP) and a Customer Relationship Management (CRM) software share some similarities. However, their primary purpose and function have many differences.
A CRM stores data of customers who had some interaction with your business. It could be data about your business prospects and customers, their product needs, and purchasing history. Hence a CRM is critical for Sales and customer-facing roles to manage customer data.
On the other hand, a CDP is a database that consolidates useful customer data including personal identifiers, website visits, purchase orders, email responses, social media comments, audio recordings, customer service interaction, mobile app touch-points, and any other data related to the customer. The CDP pulls this data from different sources and then cleans and combines it to create a single and unified customer view. Thus CDPs are essential if you plan to execute scalable, personalized, and omnichannel campaigns.
It’s not about choosing between a CDP and a CRM. Rather, Marketers should know the difference between CRM and CDP in order to take the necessary action to the respective software for each use case.
Another one of the most CDP misconceptions is that Customer Data Platforms are the same as Data Warehouses/Lakes.
To store data you need a data storage system. Many companies today use a Data Warehouse to store data, while more and more are starting to use a Data Lake. Many companies need both. (If you don’t know what a Data Warehouse or a Data Lake is, no worries, just keep on reading to find out).
A data warehouse and a data lake both serve the purpose of storing data, but in very different ways.
A Data Warehouse is a system that pulls together data from different sources for reporting and analysis purposes. The reports are often used to make business decisions. A Data Warehouse stores processed and refined data according to the business logic. This means that you need to prepare the data by cleaning, transforming, and aggregating it before using it for analytical purposes.
A Data Lake is a system that stores data in its raw format. Basically, you can store your data as-is, without having to first structure it. Data stored in the Data Lake can be in a structured, semi-structured, or unstructured format. You can import this data to your Data Warehouse for adding more business value to it, or you can use that data in dashboards and visualizations directly from the Data Lake. Beware that the direct visualization of data from the Data Lake can be risky, as data is not cleaned and it might contain corrupt or duplicate records for example, that might affect the final figures quite a lot. By using a Data Lake you are building a strong data foundation for better decisions and a single source of truth.
A Data Warehouse focuses mainly on reporting, and the data modeling and format is very strict, which limits the data you can store. A Data Lake, on the other hand, is more flexible and can handle more sources of data with any kind of format. It will also give you patterns about your customers, instead of pure facts, which will help you to create an engaging and relevant customer experience.
What kind of data can you store within a data lake?
Relational data (rows and columns)
Semi-structured data (logs, XML, JSON and CSV)
Unstructured data (emails, PDFs, and documents)
Binary data (audio, images, and video)
If you’re looking to act on your data – a Data Lake is what you need. It’s the foundation for any data-driven company. And as you might have guessed, it is included and an essential part of a CDP!
Thus a CDP includes a Data Lake (and/or a Data Warehouse) but it does not stop there. The CDP is responsible for the orchestration of the omnichannel and personalized campaigns that you will run, as well as the analysis, predictions, and reporting of your data.
A CDP can be connected to your existing Data Lake or Data Warehouse, fueling your existing business data with insights from the Marketing activities.
Number three of the 9 CDP misconceptions on our list is: a CDP is the same as a DMP.
Let’s define the various data categories first before we clarify the difference between a Customer Data Platform (CDP) and a Data Management Platform (DMP).
What kind of data can you collect?
Any data that a customer intentionally and proactively shares with a brand is called ‘Zero-party data’. It can include preference centre data, purchase intentions, personal context, and how the individual wants the brand to recognize them. This differs from first-party data since while brands own first-party data, they do not own zero-party data. Instead, consumers grant a brand the right to use their zero-party data for the purpose of a particular intent or value exchange.
This is the best type of data because first-party data is the information you yourself have collected about your audience.
This is the next best thing. Second-party data is someone else’s data (usually a trusted partner who’s willing and has the consent to share their customer data with you).
This helps to complement the current data. Third-party data is usually provided by companies, also known as data aggregators, that sell user data. You should be very careful when using this type of data. Make sure that you can trust the source before you commit to a long-term contract.
A DMP is used when you want to build marketing campaigns for audiences that are unfamiliar with you. DMPs are best for this because of their use of third-party data. They can give you access to audiences that you don’t know. You can then use that new data to build a targeted marketing campaign.
CDPs are built for processing zero, first, and second-party data. If you plan to create highly personalized marketing campaigns based on your own data, use a CDP. Your CDP can gather website data and send it to any number of different tools, depending on your needs.
There is a high chance that you need both platforms in your marketing arsenal. Your CDP can handle the segmentation and creation of look-alike audiences, while you might use a DMP to target these audiences in your preferred advertising platform.
A CDP is a Marketer-managed system designed to collect customer data from all sources, normalize it and build unique, unified profiles of each individual customer. However, this does not mean that only Marketers should manage and work with it. This is one of the most ubiquitous CDP misconceptions.
Sure, Marketers should drive the implementation since they are the ones who have defined the use cases and will be responsible for proving the ROI. However, IT should be involved as well, at least during the partner selection and the initial implementation of the solution. That will ensure that major technical hiccups will be avoided or spotted early in the process. In addition, keep in mind that the CDP will be ideally connected to the existing Data Warehouse (or Data Lake) hence IT involvement is needed for a smooth project.
Once it is implemented, your Data Scientists, Database Developers, or Analysts might want access to either fetch some data or implement a machine learning algorithm, supporting your Marketing activities. Last but not least, the Finance department might want to double-check how much you have spent for a specific campaign in a specific channel since the invoice from the advertising vendor seems too high this month.
It is correct that your CDP should be able to connect many different identifiers from multiple platforms and devices in real-time to enable people-based targeting, personalization, and measurement.
Through deterministic and probabilistic matching, it should be able to create universal and persistent consumer profiles by solving the identity of customers and visitors across different states (known & unknown)
However, keep in mind that the Customer Profile Management described above is just one of the 4 core CDP capabilities, explained in more detail here. But in sum, the idea that a CDP ‘s main capability is identity resoultion is one of the biggest CDP misconceptions.
This is another one of the biggest CDP misconceptions out there. A CDP can handle zero, first, second, and third-party data! The sky is the limit on how you can leverage your CDP. However, most of the companies use a CDP to handle zero, first and second-party data while third-party data is being processed by their DMP.
#7 Implementing a CDP involves the replacement of our Marketing Automation or visualization software
That is a tricky one and depends on the vendor that you will choose to partner with. It might be the case that the vendor has already a full suite of products, hence yes, you should stop using your preferred Marketing Automation (MA) software or visualization software. However, there are vendors who are MA or visualization software agnostic.
Why is being that flexible a huge benefit?
Let’s say that you implement a CDP solution today and after 6 months, for whatever reason, you decide that the Marketing automation software (or your visualization software) does not meet your business expectations. Instead of throwing all of your CDP implementations out of the window, you can easily switch to your selected MA solution and the CDP partner will do the rest for you. Pretty cool, right?
This is a reasonable concern but this has made it on our CDP misconceptions list. So you know it’s not true. You read all this information online about the CDPs, you speak with a few vendors and you understand the complexity. On average, for an enterprise, it takes 6 weeks to build one integration. Given that you have 5-6 data sources, one Marketing Automation software, and a visualization tool to connect, that is about… well, no need to do the math. It seems like a never-ending project.
And that would be the reality in case you choose to build instead of buying a CDP solution.
So it is not hard to assume that the technical implementation will take years which you cannot afford; you need to show the ROI internally in a few months after signing the contract.
Well, I have some good news for you!
Basically, the integrations and the various connections are pre-built normally from the vendor which means that you will save a lot of time and money. Not to mention that you will not have to maintain these integrations once it is live.
Given that you select the right partner and that your stakeholders are committed to the project, the technical implementation does not last more than one month. Thus in a couple of months, you can have your first use cases up and running, demonstrating the return-on-investment.
Our final point in our list of CDP misconceptions is: CDPs are all the same. As you might have guessed, this is not true either. The CDP institute groups CDP vendors into four categories based on the functions provided by their systems. Each category includes functions provided by the previous categories. There are great variations among vendors within each category.
Bringing it all together, clarifying these 9 misconceptions above is one step further on uncovering a CDP ’s core value and the impact it can have on the bottom line. Therefore, it is important that you understand the nuances of the Marketing technology stack and especially the CDP features and capabilities. The more accurate the understanding, the better it will serve in selecting the right Customer Data Platform for your business.
Have I missed any other CDP misconceptions? So interested to hear from you if you have any questions or input!