In the rapidly evolving digital world, companies globally are looking to master the types of data a CDP works with. Today, your customers are continually on the move, jumping from one channel to another faster than you can even say customer data. That said, it’s natural to look towards a Customer Data Platform (CDP) to help you not only keep up with your customers, but also to create clear customer profiles so you can then provide them with experiences that will make them stick around.
If you’re wondering if a CDP is right for you then you’ve come to the right place!
In this blog post, we’ll explore what a CDP does along with some of the types of data a CDP works with to create a single view of your customer. To be clear, the types we will cover in this article are not the only kinds of data a CDP works with, but those that are specific to customer identification. This will help you envision how this powerful tool can play a role in reaching your business’ customer data goals.
Before we dive into the types of data a CDP works with, let’s back up and clarify what a Customer Data Platform even is.
Simply put, a CDP is a prebuilt system that standardizes and connects data from different touch points to create complete profiles of your customers. These touch points can be a variety of things from social media engagement to web searches and even in-person transactions.
From there, a CDP then provides you with actionable data that can be sent to essentially any other tool and used for marketing campaigns, customer service and all customer experience initiatives.
Sounds pretty sweet, right? And in today’s world where digital transformation has been heavily accelerated by COVID-19, a Customer Data Platform has become an even more central tool for many organizations across various industries.
Now that you understand what a Customer Data Platform does, let’s take it one step further and compare it against some other similar tools.
Similar Tools to CDPs
CDPs vs DMPs
There can be some confusion around the difference between a CDP and a Data Management Platform (DMP). To clarify, a CDP collects first-party data like names, phone numbers, email addresses, and so on to assist with identity resolution and ensure accuracy. Opposedly, DMPs heavily rely on third-party cookies or other anonymous identifiers with some limited ability to integrate first-party data, making recognizing customers difficult.
Additionally, CDPs use the data they’ve collected to build out complete customer profiles that showcase behaviors and preferences identified along the customer’s journey. On the other hand, DMPs only store data for short periods of time because so much of that data is anonymous and is typically used for specific and short-lived campaigns.
CDPs vs CRMs
Another type of technology that is often asked about in comparison to a CDP is a Customer Relationship Management (CRM) tool. The two are similar in that they both collect customer data but CRMs rely on manual input to capture offline data and only focus on sales data where a CDP can collect both offline and online data again to create a full picture of your customer.
CDPs vs Personalization Tools
While a CDP does help better personalize experiences, it should not be misclassified as a personalization-only tool. CDPs go beyond just tailoring experiences and help with overall data management.
More specifically, Tealium’s AudienceStream CDP unifies omnichannel data not only for the use of customer profiles, but also to help standardize data and make it accessible across your entire organization. AudienceStream is also known as a data-first CDP because we work with the data and tech you already have and optimize your entire tech stack by breaking down data silos.
The Types of Data a CDP Works With
First and Foremost – First-party Data
A CDP primarily collects first-party data which consists of insights obtained directly from your customers AND given with consent. For example, your customer has given you their email address through a direct channel of yours like by signing up for a loyalty program via your website.
On that note, first-party data has become even more important in today’s digital climate because third-party cookies are on their way out and new data privacy legislation is on its way in. In addition, first-party data is more accurate because it’s again collected directly from your customer and they have chosen to give it to you.
Looking at a bigger picture, four other types of data a CDP works with include:
- Identity Data which outlines who a person is at a high level or how they identify themselves to the outside world.
- Examples of this include: First and last names, age and gender, their location, phone number, email address, social handles, etc.
- Descriptive Data goes a little bit deeper than identity and revolves more around the person’s lifestyle.
- Examples of this include: the type of house they live in, the type of car they drive, their relationship status, where they’ve worked in the past, their income, their hobbies, etc.
- Behavioral Data is the next layer which reveals specific ways a customer interacts with a business.
- Examples of this align with conversion types so things like: cart abandonment, repeat purchases, click-throughs, social post engagement, etc.
- Qualitative Data gets even more granular than behavioral data and includes customer preferences and opinions.
- Examples of this include: product ratings, customer service ratings, why a customer chose to purchase a specific product, why a customer chose to purchase it from your brand specifically, color, pattern, or function preferences based on search words or filters, etc.
As you can see, these examples will change slightly depending on your industry but what remains the same is that a CDP can handle it all. Also, there are numerous types of data that a CDP works with, but these important five listed above help companies to create vivid customer profiles.
Discover why companies across various industries are choosing Tealium’s AudienceStream CDP to help them better manage their customer data and drive real-time, personalized experiences using the insights we shared in this post.
