November 2, 2020
Do you ever find yourself wondering where the marketers were when they were naming martech solutions?
Each solution is generally referred to by an acronym for words that feel computer-generated. It can be challenging to grasp the unique value propositions (UVP) (see what I did there?) and each category’s overlapping capabilities.
So now we present a brief-as-we-can-manage, shallow dive into how not to confuse CDPs with other acronyms. In case you already have one of the below solutions, we’ll also highlight how a solid CDP can collaborate with and amplify functionality through seamless integration.
Data Management Platforms (DMP)
How they differ
While DMPs can play a role in centralizing and organizing customer data to make it usable, they have a more narrow focus on anonymized third-party data specifically for managing paid digital advertising and marketing platforms. CDPs focus on first-party data that can use personally identifiable information (PII) for marketing functions.
How they work together
CDPs can push audiences with customer PII (name, email, phone, etc.) to DMPs to pass to demand-side partners (advertisers). If customers click on any downstream advertisements, a CDP will ingest that data for further segmentation and analysis.
Customer Relationship Management Tools (CRM)
How they differ
CRM tools were designed for sales and services to track direct customer interactions (e.g., purchases and customer service communications). While CRM tools have their strengths, they lack the necessary capabilities for being useful to marketing: integration with data sources is difficult; CRM tools are limited to basic automation; and use cases tee up to manual outreach, disconnected from adtech and other large-scale marketing efforts.
How they work together
CDPs can push audiences to CRM tools for downstream management. CDPs can also ingest data from CRM tools to support audience segmentation and personalization.
Multi-Channel Marketing Hubs (MMH)
How they differ
Most Multichannel Marketing Hubs (MMH) — aka marketing clouds — offer data orchestration and actionability elements. But these systems specialize in managing and deploying marketing campaigns to end channels, like email, social media, or SMS. MMHs can’t match a CDP’s ability to unify data across the marketing tech stack. Legacy MMHs rely on batched FTP-based data integration. Newer MMHs rely solely on an event-based data model, which doesn’t support complex manual aggregations of customer properties with all new events/attributes.
How they work together
CDPs can push audiences to MMHs to trigger downstream messages (email, SMS, push, etc.). CDPs can also ingest data from MMH tools to support audience segmentation and personalization. In many situations, a CDP can replace a lot of data and campaign orchestration that an MMH owns, but a CDP still relies on end channels to push messages. Clients moving from an MMH to a CDP can purchase best-of-breed, inexpensive end channels, while the CDP manages data centralization, segmentation, personalization, experimentation, and campaign orchestration.
Digital Personalization Engines (DPE)
How they differ
A DPE is a tech solution that identifies the best user experience for an individual and alters the online experience through visual presentation, recommendations, or triggered messaging. DPEs also pass insights along to the overseeing teams, who take action on personalization trends.
How they work together
CDPs can sync audiences to DPE tools for downstream management. For example, CDPs can sync audiences with a high LTV, and downstream DPE tools will show different content to those high-LTV customers.
Master Data Management Platforms (MDM)
How they differ
Master Data Management falls strictly in the domain of database management and IT to manage, consolidate, and optimize all critical data within an organization. Creating this master record aims for accuracy, consistency, and reliability across the full spectrum of business data — including business finances, company suppliers, pipeline, etc. In other words, it’s information overload for any marketer. A CDP focuses on customer data and keeps marketers in the driver’s seat.
How they work together
CDPs can ingest cleansed and verified customer data from MDM tools. CDPs can also perform last-mile transformations on customer data and support identity resolution.
Data Lake
How they differ
A data lake is a centralized repository for storing all your structured and unstructured data at any scale. If you are not a trained data-handler (IT professional, data scientist, database administrator, etc.), data lakes are scary, complicated places, and you should steer clear.
How they work together
CDPs can share all customer data to a client’s data lake. In some situations, a CDP can also manage a customer’s data lake as a service (DLaaS).
Chapter 6: What Outcomes Should a CDP Enable?
