Customer Data Platform and Data Management platforms are some of the components of a data driven, marketing technology stack. They provide tools for marketers to effectively target different segment of the population.
The Customer data platform is meant as a data store for all internal attributes and events related to a given customer. It is meant to provide a way to unify data across multiple data source, with potentially different types of customer identifiers and as such needs to offer a way to resolve identities.
Single Source of Truth: The aim of the customer platform is to act as the single source of truth for customer data, offering a 360 degree views of customer behavior across the different touch point and identities.
It enables to also structure and standardize the inputs and data models of customers, for instance with mParticle’s commerce events which structure different product action onto the same schema. Beside the standardization component, part of the CDP’s role during the data integration phase is also to provide better data quality by cleansing and de-duping the data.
Advertising: Since CDPs are able to collect data from the different touch points of customer interactions and resolving their identities. It is also able to harmonize the communication towards the customers across the different communication channels.
Empower Personalization: Personalization can be empowered to the highest level by the use of a customer data platform. Customer data platforms allows for the creation and utilization of data from a merged identity, through means of a) Attribute retrieval b) segment creation c) machine learning score. These data points can then be used to power advertising campaigns, website recommendation or to empower personalization across the full user journey.
Ease Integration: One of the role of customer data platforms is to facilitate the integration of different datasources both inbound or outbound. The customer data platform needs to be able to integrate data sources such as web analytics, e-commerce data, email behavior and export to the different end points that can make use of the data such as advertising platform, marketing automation tools or a data warehouse.
There exists quite a large list of CDP vendors out there, usually each with a different focus.
- CDPs originating from a Tag Management systems provider such as Tealium, or Ensighten. These systems tend to have pivoted into Customer Profile by leveraging their common data model used for tag integration.
- Pure Play Oriented: such as Segment, one of the few CDP offering a free developer trial version, mParticle, a CDP focused on providing data integration, offering an unified data model, ingesting different types of events such as commerce events onto a common data model and exporting it to different end-points.
- Campaign Management Oriented: Lytics is a CDP with a strong focused on campaign management, customer journeys and of enrichment of profile from 2nd party data , Agile One a CDP with both campaigns and analytics capabilities or SessionM a CDP focused on providing loyalty management as part of their offering.
- Personalization Oriented: Qubit, although it does not sell itself as a CDP, but rather as a personalization platform, it shares a number of functionalities with them, such as an ability to deduplicate customers across identities, storing of data at user level, ability to segment audiences and some possibilities for integration with other platforms (eg: Salesforce Marketing Cloud).
- Open Source: Unomi is an open source CDP, some of its draw back being the lack of UI, the need to have to host it and the lack of an extensive integration ecosystem.
Seeing a CDP as a golden records for Customer needs to be taken with a certain grain of salt, ingested data is usually persisted with attributes, for instance product information is usually persisted at the same time as the events triggered. The backend of most CDPs don’t usually allow for the kind of merging activities necessary to maintain dimensions such as a product category dimension.
What’s the purpose of a DMP — the purpose of a data management platform is the collection, enrichment of data and management of data for digital marketing purpose. One of the main value from a DMP is the ability to provide a consistent experience across different marketing channels.
The DMP collects data from a clients’ first party sources, for instance from the users visiting its websites. From second party sources, ie: data that is obtained through collaboration, this could be targeting settings for a Facebook campaign that can be identified when a user visit the website, and from third party sources, data that is obtained from other activities.
At the heart of the DMP is the notion of an anonymous user identity, typically identified through cookie ids, these cookies can be matched through rule base systems or through probabilistic matching.
Advertising : The main purpose of DMPs is to offer a a cohesive audience targeting. This is done through segment building and the creation of different segments for different type of personas. DMPs typically provide different type of segments:
- Static Segments: Segments are run once based on a snapshot of a visitors’ attributes.
- Adaptive Segments: Segments are constantly being updated based on the data being provided to the platform. For instance an adaptive segment can be “website visitors 30days”
- Segments obtained from Machine Learning models for Lookalike modeling.
These segments can then be exported to DSPs or other activation channels.
Audience Insight : DMPs also provide insights on the behavioral patterns of your customers, as well as learn more about who your customers are by leveraging informations provided by third parties.
- Salesforce DMP (Krux): Salesforce integrated Krux as part of their marketing cloud platform, offering a way to target “unknown” visitors on your websites, and enhance the information, you have on them with third party data.
- Adobe Audience manager: is Adobe’s DMP, well integrated into adobe marketing cloud, it enables marketeers to get a better grasps of the different audience segments, interacting with their ads or the website.
- Mediamath: an independent adtech vendor in between a DMP and a DSP solution, benefiting from over $600M of funding.
- Oracle BlueKai: Oracle’s DMP with a heavy data enrichment slant, it boast overs 200 media partners.
At their core, CDPs and DMPs have an overlap in functionalities, but also some difference, which mostly resolve from their treatment of identity. CDPs also have an overlap in functionality with other systems such as Tag Management, Master Data Management and Marketing Automation tooling.