---
title: CDP Fundamentals and Use Cases — Customer Data Platforms Module 1 — RGM Training
url: https://realgrowthmatters.com/training/customer-data-platforms/cdp-fundamentals-and-use-cases/
updated: 2026-06-10
source_html: https://realgrowthmatters.com/training/customer-data-platforms/cdp-fundamentals-and-use-cases/
---

RGM° · Training

# CDP Fundamentals and Use Cases

A CDP unifies customer data and makes it available to marketing systems. This module covers what qualifies as a CDP, the categories, the alternatives, and the 90-day evaluation plan.

### What you will learn

1. What a CDP actually is (and is not)
2. The CDP Institute definition and the four required capabilities
3. Categories of CDPs and how they differ
4. Use cases: personalization, segmentation, identity, activation
5. The CDP vs DMP distinction
6. The CDP vs CRM distinction
7. How CDPs fit with data warehouses
8. Build vs buy vs composable
9. Vendor landscape
10. When you actually need a CDP
11. The 90-day CDP evaluation plan

## 1. What a CDP is

A Customer Data Platform unifies customer data from multiple sources, builds persistent customer profiles, and makes them available to marketing systems. Built for marketers, owned by marketing (in contrast to data warehouses, which are owned by IT/data).

## 2. CDP Institute definition

The CDP Institute's formal definition: "packaged software that creates a persistent, unified customer database that is accessible to other systems." Required capabilities:

1. Ingest data from any source.
2. Capture full detail.
3. Store indefinitely.
4. Create persistent unified profiles.
5. Provide access to any system.

## 3. Categories

- **Data CDPs:** Pure data unification (mParticle, Segment historically).
- **Analytics CDPs:** Data plus analytics layer (Adobe RT-CDP, Treasure Data).
- **Campaign CDPs:** Data plus campaign execution (Salesforce Data Cloud, Adobe RT-CDP, Tealium).
- **Delivery CDPs:** Data plus full execution stack (Klaviyo, Iterable, Bloomreach).

## 4. Use cases

- Cross-channel personalization.
- Real-time segmentation.
- Identity resolution across web, mobile, offline.
- Lookalike and audience activation.
- Customer journey orchestration.
- Privacy compliance (consent, suppression).

## 5. CDP vs DMP

DMP (Data Management Platform): anonymous, third-party data, for ad targeting. CDP: known, first-party, for marketing across channels. The DMP category has effectively collapsed with the deprecation of third-party cookies.

## 6. CDP vs CRM

CRM: customer interactions and pipeline, sales / service focused. CDP: behavioral and identity data, marketing focused. Many implementations integrate them, with CRM as source-of-record for accounts and CDP as source-of-record for behavior.

## 7. CDP vs warehouse

The biggest architectural debate. Two patterns:

- **CDP as primary:** Customer data lives in CDP, syncs to warehouse for reporting.
- **Warehouse as primary (composable CDP):** Data lives in warehouse, reverse ETL activates it.

## 8. Build / buy / composable

| Approach | Best for |
| --- | --- |
| Buy packaged CDP | Speed, marketing ownership, less engineering |
| Composable on warehouse | Data already in warehouse, engineering capacity, flexibility |
| Build from scratch | Unique requirements, large engineering org |

## 9. Vendor landscape

- **Enterprise:** Salesforce Data Cloud, Adobe Real-Time CDP, Treasure Data, Tealium, Twilio Segment.
- **Mid-market:** mParticle, Bloomreach Engagement, ActionIQ, Lytics.
- **Composable:** Hightouch, Census (paired with Snowflake / BigQuery / Databricks).
- **Vertical:** Klaviyo (e-commerce), Iterable (cross-channel).

## 10. When you need one

Signs you need a CDP:

- Customer data scattered across 5+ tools with no unified view.
- Email, web, paid, app have different identity logic.
- Marketing cannot self-serve audience creation.
- Personalization is limited by data access.
- Compliance (consent, deletion) is hard because data is everywhere.

## 11. 90-day evaluation

1. Weeks 1 - 2: Use-case definition and data audit.
2. Weeks 3 - 4: Vendor shortlist (5 - 8 options).
3. Weeks 5 - 8: Detailed evaluation and demos against use cases.
4. Weeks 9 - 10: Pilots with top 2 - 3.
5. Weeks 11 - 12: Decision, contract, implementation plan.

**How to use this module:** The CDP Institute capabilities (Section 2), the build/buy/composable table (Section 8), and the 90-day evaluation (Section 11) are the planning artifacts.

### Sources & further reading

- [CDP Institute](https://www.cdpinstitute.org/)
- [Gartner CDP reviews](https://www.gartner.com/reviews/market/customer-data-platforms)
- [Forrester Wave: Customer Data Platforms](https://www.forrester.com/report/the-forrester-wave-tm-customer-data-platforms/)
- [Segment recipes](https://segment.com/recipes/)
- [mParticle CDP](https://www.mparticle.com/customer-data-platform/)
- [Tealium resources](https://www.tealium.com/resources/)
- [Hightouch composable CDP](https://hightouch.com/blog/composable-cdp)
- [Census composable CDP](https://www.getcensus.com/blog/topics/composable-cdp)
- Books: David Raab, *Building a Customer Data Platform*; Martin Kihn, *Customer Data Platforms* (Salesforce)
- [Salesforce Data Cloud](https://www.salesforce.com/products/data/)
- [Adobe Real-Time CDP](https://business.adobe.com/products/real-time-customer-data-platform/rtcdp.html)
- [CDP Institute research papers](https://www.cdpresearch.com/)

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Part of the [Customer Data Platforms](/training/customer-data-platforms/) series · RGM Training