What data can a CDP handle?

What are the most popular types of data fed into a CDP? We tallied up Segment’s most connected sources of customer data to take a look.

By Geoffrey Keating

In the last few years, the customer journey has become incredibly fragmented.

Google reports that 90% of web users hop from one device to another to complete a task, and Cisco estimates that there are approximately eight networked devices per person in the United States.

Increasingly, businesses like Fox, Instacart, and IBM are turning to CDPs to help solve this, and connect all types and sources of customer data, whether that’s from websites, mobile applications, devices, servers, and more.

This raises an interesting question: what are the most popular types of data fed into a CDP?

So we tallied up Segment’s most connected sources of customer data to take a look.

What data can a CDP handle?

1. Website and mobile sources

JavaScript tops the list, with 34,203 connections, more than all the other data sources combined.

What data can a CDP handle 2

This isn’t *hugely* surprising, given that JavaScript is the ubiquitous data collection method for a clean, versatile, and actionable source of customer data.

Many, many tools (including Google and Segment) rely on JavaScript code snippets embedded within websites to collect data on who the users are, what they’re doing, where they’re doing it, and more. We can conclude from this that websites, both desktop, and mobile, are the number #1 place where businesses collect data.

After websites come apps. Android comes in at #2 (6,216), and iOS is close behind at #3 (5,702). Both of these data sources are used to collect in-app user behavior data. Such high rankings are a reflection of customer behavior as the world becomes increasingly mobile-centric, with 81% of the adult U.S. population owning a smartphone.

HTTP API comes in at #5 (1,716) thanks to it being a fairly broad category. If you don’t want to use a native source in Segment (like JavaScript, Android, etc.), you can use HTTP API to collect data on any website or app. You can think of it as a catchall for website and app data that’s not collected through JavaScript or mobile means.

Because users are online across multiple devices, data sources that are versatile and mobile-first dominate this list.

2. Server-side sources

Server-side data sources had a strong showing as well. This reveals that CDPs are used not just to help marketing, and product teams collect behavioral data, but also for technical work by development and engineering teams.

What data can a CDP handle 3

When businesses collect server-side data, they’re pulling data from the servers and databases they own. The alternative is client-side data, which is data pulled from web browsers. Businesses use server-side data to understand the data they own, such as user behavior data in their software. If you need to decide whether to use client-side or server-side data, we’ve got a guide just for you.

Python comes in at #7 (1,179), leading the pack likely due to its general-purpose nature and wide usage — it ranks as the most in-demand coding language.

Closely following Python is Node.js at #8 (1,179). Node.js a runtime environment for JavaScript that’s popular because it lets you run scalable, real-time applications.

After those two come PHP at #11 (967) and Ruby at #12 (935). These are also very popular general-purpose languages used to create applications.

All of these sources are used to create applications and to collect data on user behavior within them. Using these sources indicates that businesses are likely collecting data within a proprietary app or software to understand how it’s used. Again, versatile data sources dominate, meaning flexibility is most valued among server-side data sources.

3. Cloud sources

The rest of the top data sources are what we refer to as “cloud sources”, a wide variety of marketing tools focused on stages of the customer journey.

What data can a CDP handle 4

Segment’s Personas comes in at #6 (1,241). Using Personas as a data source means that the business collects data from the unified customer profiles that Segment creates. This data can provide an overview of the entire customer journey.

Facebook Ads is at #9 (1,106), thanks in part to Facebook’s domination of the advertising industry. Businesses that use this data source collect data from their ads to gauge their success at driving awareness and traffic.

Stripe comes in at #13 (737) and, similar to Facebook, this is likely thanks to its market domination. When businesses use Stripe as a data source, they’re collecting data at the point of purchase, which is the conversion stage of the customer journey

After that, a group of customer management and support software starts to take over: HubSpot at #14 (616), Intercom at #15 (570), and Zendesk at #16 (568). These tools specialize in the engagement and retention stages of the customer journey. When businesses use the tools as data sources, they’re collecting data on touchpoints such as customer support chats, emails, and more.

Besides Personas, these data sources eschew versatility in favor of a laser focus on specific stages of the customer journey. This data is collected at clearly defined touchpoints, like when an ad is clicked, an email is opened, or an item is bought.

Wrapping up

In times gone by, most companies would simply analyze what was happening on their websites and mobile apps.

But that’s just a fraction of the customer experience.

Customers today aren’t just using clicking around your website or app. They’re chatting to support via live chat, talking with your sales team via email, clicking on ads on Facebook, and much more.

The data above shows us that customers are bringing a wide variety of data into customer data platforms to give them a complete picture of all customer interactions with a business, not just what’s happening on their mobile apps and websites.

Thanks to the explosion (and fragmentation) of digital channels today, we predict that the adoption of CDPs will grow in tandem. Making sense of all these disparate streams of customer data will become ever more important.

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