Current State of the Industry
The marketing technology (MarTech) landscape has exploded in the past eight years. In 2011, the amount of MarTech vendors numbered 150. Today, that number has surpassed 7,000. With such a large variety of vendors and tools it can be difficult to keep track of what is worth implementing and how to use it effectively. Two relatively new tools that have created some confusion are customer data platforms (CDPs) and data management platforms (DMPs). Both platforms obtain and organize data so that it can be activated to engage customers. The primary difference between them is the type of data collected and the focus of customer engagement. In short, CDPs are best utilized to target and grow relationships with existing customers using first-party data, while DMPs primarily use third-party data to help gain new customers. The following article contains a breakdown of each tool and details of how they fit into the current MarTech landscape.
MarTech Reference Architecture
Credera’s MarTech reference architecture (see below) highlights where CDP and DMP live within the overall MarTech landscape. While these tools have similarities, it is important for marketers to understand their differences.
“It’s important to use a holistic reference architecture to help understand their current state and develop an actionable roadmap. This helps identify clear long-term sequencing as well as immediate next best steps,” shares Credera partner, Phil Lockhart.
What Is a CDP?
CDPs are primarily meant to personalize the existing customer experience with the goal of improving customer satisfaction, retention and engagement. CDP’s leverage first-party data collected by the company. Examples of first-party data include customer data obtained from websites, mobile apps, point-of-sale, and company call centers. This data typically has some personally identifiable information (PII) like names and emails attached to it. Using the PII, the customer data is then organized into a new or existing profile. If an individual uses multiple emails or devices, the CDP should be able to consolidate them into a single profile. Profiles can then be divided into segments based on their personal (e.g., age, location, gender, etc.) and behavioral (e.g., purchase history, ad interaction, etc.) data. Once the profiles are placed in segments, analytics are used to predict future behaviors and determine the “next best action” for different segments. At this point, the CDP passes insights and predictions to be activated by another platform. Currently, most formalized CDPs are being provided through smaller specialized vendors such as Tealium, RedPoint, and Blueconic, though Adobe and Salesforce have recently announced offerings in this space with the introduction of their own CDP solutions.
What Is a DMP?
DMPs build audience segments out of potential customers for campaigns using anonymous third-party data. The data collected by DMPs is similar to the data collected by CDPs. However, unlike CDPs, the data collected by DMPs is primarily composed of purchased third-party data. The data is typically anonymous and is available for a limited time. This is what makes the DMP less suited for long-term customer engagement. The data collected is centralized and separated into segments based on demographic and behavioral data. The segments can then be sent to a demand-side platform where it can be used to create a campaign targeting the segment of interest. Typically, the goal of the campaign is to gain new customers. Many of the larger vendors including Salesforce, Adobe, and Oracle provide DMP solutions. Examples of smaller vendors with DMP solutions include LiveRamp and Lotame.
Use Case Comparison
Another helpful way to understand the differences between a DMP and CDP is to look at some sample use cases for each. The following use cases are some of the top value drivers for DMP and CDP usage.
|Dynamic Home Page||Lookalike Modeling|
|Evaluate web behaviors and purchase history to define personalized web content that is effective for a particular segment||Objectives:
||Find high potential prospecting audiences based on similarity to your most valuable audiences||Objectives:
|Dynamic Email Content||Audience Supression|
|Target a customer visiting clearance items on the website with emails with clearance items as the primary focus||Objectives:
||Exclude audiences from campaigns who have performed a desired action from misaligned messaging (e.g., visited a website or converted)||Objectives:
|Online to Offline Stitching||Audience Building|
|Use web activity to stitch online and offline data together for a full view of the customer||Objectives:
||Understand the profile of your target audience in terms of demographics, behaviors, and interests using first- second-, and third-party data||Objectives:
|Send emails to known customers that have signaled desire to purchase but haven’t after seven days||Objectives:
||Enable frequency capping across channels, campaigns and activation partners||Objectives: