Customer data platform (CDP) vs. customer intelligence platform (CIP): differences, similarities, and symbiosis

A frequently asked question we get at Common Room: How is a customer intelligence platform (CIP) different from a customer data platform (CDP)?

It’s a fair question. They share two out of three words, after all.

Despite the name overlap, there are fundamental differences between them, from use cases to end users and everything in between.

Here’s how a CDP differs from a CIP—and why it matters.

CDP vs. CIP: deep dive into the differences

Implementation: technical vs. non-technical

Customer data platform
CDP implementation is generally performed by an engineering or product team. The main purpose of a CDP is to capture user “events” happening across a website or within a product via API call (see Segment’s implementation spec for an example).

Events captured by a CDP are most often implemented by writing code that’s executed via API when users take certain actions, like clicking a button or viewing a screen. This is commonly referred to as a track call.

Customer intelligence platform
CIP implementation is usually handled by someone in RevOps or a GTM team leader. Connecting to most signal sources only takes a few clicks and can be done in a few minutes—no code or engineering support required. For more complex signal capture (think product data), signals are commonly synced via reverse ETL platforms or direct integration with a data warehouse, which is handled by RevOps or engineering team members, respectively.

It should also be noted that signal accessibility and integration complexity vary depending on the signal. For example, capturing signals from a public source like Twitter or uploading a CSV for enrichment can be done by anyone. On the other hand, connecting to proprietary GTM signal sources, like a CRM or data warehouse, requires permissions and field mapping.

Data sources and signal collection: 1st-party vs. every party

Customer data platform
A CDP is generally used to gather data from first-party sources (think websites, software, mobile applications). Second- and third-party signals like LinkedIn interactions, GitHub contributions, job-change activity, hiring trends, and more are not typically captured by a CDP.

While CDPs can capture data directly from CRMs, email marketing platforms, chat tools, payment providers, and other data sources, their core competency is in collecting data points via code (like Javascript and Python).

Customer intelligence platform
A CIP is built to capture signals across first-, second-, and third-party sources. The types of first-party signals you’d find in a CDP—such as product usage and website activity—can also be captured by a CIP. You can even integrate your CDP with your CIP to unify those first-party signals with other signals, such as interactions across social channels, engagements in community channels, actions in open-source channels, and the hundreds of other signals not captured by a CDP.

Identity resolution and enrichment: limited vs. comprehensive

Customer data platform
Identity resolution is a core function of a CDP, but it’s only applicable to first-party clickstream data. With CDPs, identity resolution is architected via anonymous user IDs (think an unknown website visitor) that resolve when a user identity becomes known through, say, a form fill. On top of that, CDPs resolve user identification across web, mobile, server, and third parties using cookie IDs, device IDs, and custom external IDs.

Because CDPs include identity resolution functionality, it’s a great complement to a CIP. For example, product activity from a single user that occurs in two places—like a desktop browser and mobile app—can be unified by a CDP and passed into a CIP, which will then display it as a product activity signal.

Customer intelligence platform
A core requirement of a CIP is the ability to connect the dots between a signal and the person behind it, as well as fill in the blanks of their firmographics via enrichment. Without these capabilities, it would be impossible to filter contacts by criteria (think funding raised or tech stack configuration) and stack signals (think combining product usage with job-change activity).

Identity enrichment comes out of the box with a CIP. In other words: You don’t have to pay extra for an enrichment provider or call a provider via API.

Data and signal actionability: destinations vs. actions

Customer data platform
A CDP doesn’t act as a UI for GTM team members. Rather, it serves as a first-party data aggregator and translator to downstream “destinations.” Common CDP destinations include data warehouses, as well as tools for analytics reporting, A/B testing, feature flagging, advertising attribution, and a handful of other categories.

A CDP and a CIP may sometimes send information to the same destinations (like a CRM or marketing automation platform). In that sense, both CDPs and CIPs federate signals or events that can be used to trigger actions, like changing a lead status or sending an email.

Customer intelligence platform
CIPs have a built-in action and automation layer. That means they can perform last-mile actions like adding a prospect to an outbound sequence and even automating the end-to-end signal-to-action process. Think actions like triggering an outbound email based on a combination of job-change activity and buyer fit. While a CDP moves data from one place to another, a CIP allows you to aggregate signals, reveal the person and account behind the signal, and orchestrate prioritization and action all in one place.

Unlike a CDP, a CIP offers a prioritized view for GTM practitioners to reach buyers and customers, enrich profiles to filter for fit and context, and automate actions. This is why CDPs are typically used by technical teams, whereas CIPs are generally used by non-technical teams, like sales, marketing, customer success, and community.

Use cases: backend vs. frontend

Customer data platform

The fact that the core user of a CDP typically sits on the engineering or product team (and is usually focused on data or analytics) is reflected in its use cases. That said, sometimes a tech-savvy growth marketer will jump into a CDP and connect it to a GTM tool so they can access first-party data.

Examples of CDP use cases include:

• Sending first-party data to a data warehouse so it can be joined with other business data
• Standardizing and unifying first-party data before it’s federated to destinations
• Aggregating product data into an analytics platform to inform user growth (think sending product data to Amplitude or Mixpanel)
• Tracking attribution from first touch to last touch
• Sending first-party data to marketing tools to trigger actions for email, chat, and mobile

Customer intelligence platform
The core user of a CIP sits under GTM and typically has a customer-facing role of some kind. They log in regularly, they prioritize their efforts, and they conduct their work—all in the same place.

Examples of CIP use cases include:

How CDPs and CIPs can work together

CDPs and CIPs actually pair well together.

For one thing, CDPs commonly feed first-party website and product data as a source of signal into a CIP—if not through a direct integration, then by federating data to a data warehouse like Snowflake or reverse ETL technology like Hightouch or Census that is integrated with a CIP.

Also, since CDPs offer engineering and product teams flexibility, oversight, and consistency for tracking product data, they’re a preferred method for capturing product signals in a CIP—be it by direct integration, data warehouse, or reverse ETL.

From there, first-party data can be enriched, scored, and combined with other signals in a CIP to unlock more GTM use cases, like reaching out to economic buyers who are approaching product usage ceilings.

At the end of the day, a CDP and a CIP both exist to help you slice and dice your data. The difference is in what you can slice, who's doing the slicing, and what you can cook up with those ingredients.

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