Data Integration Methods to Expect from a CDP

CDP 101|[wtr-time]

Data Integration Methods to Expect from a CDP

Scott Brinker did it again. The 2019 edition of his Marketing Technology Supergraphic outdid the year prior with a staggering 7,040 martech companies represented:

marketing technology landscape

(Don’t worry: You’re not expected to be able to make out any of the brands from this reduced-size version. Suffice to say, there are most definitely 7,000+ companies featured — including BlueConic.)

In his speech introducing the 2018 edition of this graphic at the MarTech Conference in Boston as well as the accompanying blog post on ChiefMarTec, Brinker made this astute observation:

  • “We’re in a post-platform era in martech. The dream of one-suite-to-rule-them-all has been superseded by a vision of many open platform-like tools being woven together in a more dynamic fashion. Some will be big, foundational platforms; many will be small, specialized platforms. All of them will give more power to marketers to shape their craft in a digital everything world.”

Recently, I had the opportunity to visit the Vatican. I — along with thousands of other tourists — walked through a gallery of centuries-old tapestries I think are an apt reference point to what Brinker talks about when he says today’s marketing technology platforms are being “woven together.”

cdp customer data platform

Data integration distinguishes the CDP from other marketing technologies

The monumental shift the explosion of martech solutions represents isn’t just the sheer volume. It’s also about the fact marketers can now build martech engines powered by their own first-party data.

We’re talking about the assembly of what are essentially completely bespoke stacks with incredible diversity, complexity, and scope. If these stacks, like the Vatican’s tapestries, are going to stand up to the rigors of time, the strength of the weaving is critical.

The customer data platform (CDP) is designed to give marketers the breadth of data integration options she needs to liberate the relevant first-party data that exists in different parts of her marketing stack and also make it usable in other places through instantaneous activation across channels.

What kind of data integration is required, however, depends on a number of factors — most noteworthy, the particular use cases the data integration in question supports.

In BlueConic’s case, there are seven different data integration options, each with out-of-the-box support, for connecting data to support the full range of marketer needs.

We put together the table below to not only explain why there’s no one-size-fits-all model for data integration, but also to point out that you don’t need to custom-build every type of data integration you’re looking for — builds that often require lots of money and time.

In short, this table shows the CDP is marketing’s gateway to benefiting from the bounty of martech riches available, while right-sizing the perfect martech stack for you and your team.

customer data platform

Out-of-the-box data integration methods you should expect from your CDP

CDP Data Integration Method Benefits Caveats Sample Use Case

Server-to-server data integration

Examples: Salesforce Marketing Cloud, Google AdWords, Facebook Custom Audiences

  • Creates a deep integration between systems for extensive data transfer, which supports the broadest set of use cases
  • Stable and typically certified by the  other system that the CDP is integrating with
  • Can be unavailable or unsupported (i.e. walled gardens)
  • Scalability depends on the external system*Requires unique identifier
  • Send customer profile attributes and segments to an ESP, as well as remove individuals from lists
  • Customize email campaigns to web visitors with copy/creative that reflects their on-site interests and preferences, and customize their site experience based on which email campaigns they have interacted with

Client-side data integration

Examples: Universal Analytics, Krux, BlueKai, LiveRamp

  • Lighter weight to develop
  • Close-to-real-time data exchange
  • Doesn’t required a unique identifier
  • High scalability
  • Limited to in-browser activities
  • Exposes profile data that is sent to other system
  • Can be blocked by the visitor using browser extensions
  • Send segments in your CDP based on predictive behavioral data to web analytics solution
CSV and batch processing
  • Widely available and highly scalable regardless of the external system providing the data to the CDP
  • Easily managed by the marketer
  • Supports frequent but not necessarily real-time import/export
  • Manual set up of fields
  • Requires unique identifier
  • Import data to your CDP from systems without an API or an initial upload of tens of millions of records that will be updated continuously via an API or server-to-server connection on an ongoing basis
  • Import data from  in-house data warehouses/custom systems that you have built to your CDP
  • Target visitors on-site who were flagged in your database as high value prospects by your sales organization


Example: Slack

  • Widely available and used by different systems
  • Easy to test & implement
  • Close-to-real-time data exchange
  • Typically highly scalable
  • Limited to in-browser activities
  • Typically requires unique identifier
  • Update/retrieve data based on something that’s happening in the browser
  • Process newsletter subscriptions
  • Enrich profile with firmographic data based on IP address
  • Slack: announcing what someone is doing on the website in Slack

Data layer connection

Examples: Adobe Analytics, Google Tag Manager, BlueConic Data Layer

  • Use the data taxonomy and structure you’ve already got
  • Pre-packaged solutions to pick up data from those systems
  • Limited to the data in the data layer, which may not include offline or other relevant sources
  • Read and write data from/to any data layer
  • Surface information about product pages to determine individual customer affinity for brand and category interest level

Embedded connections

Examples: iOS, Android

  • Requires developers to place the script and/or add the SDK to apps
  • URL and pixel have a narrow scope of use cases
  • Place a tracking URL in your emails so that when a user clicks through to your website, their profile is linked
DIY data integration
  • Custom-built big data integration tool to be exactly what you need
  • Internal resources that are often hard to come by or creates a project in a long queue
  • Connect the CDP proprietary system with a lot of custom features

As you can see, when it comes to data integration, you’ve got plenty of options. The key is deciding which avenues to take to unify your data sets into a single, digital location.

Already know a customer data platform is the marketing hub you need? Learn how to write your CDP RFP for prospective vendors in our webinar.


See what BlueConic can do for you.

Whether you’re looking for operational efficiencies or improved marketing effectiveness through data activation, our customer data platform can help.