Are there different types of CDP?

And what are the market trends affecting the CDP landscape?

With the number of CDPs exceeding 100 by some counts, the category has suffered from ill-defined specifics and boundaries around capabilities and outcomes.

The key themes, patterns, and questions that have emerged in conversations with business leaders across industries confirm no formal definition of a CDP.

To help better understand the CDP landscape, we will outline the key market trends underlying the industry and the resulting subcategories of CDPs that have emerged as a result:

Market trends that affect the CDP landscape

  1. DTC is king – Direct to Consumer brands are winning and are providing an elevated customer experience, raising the bar on what all brands need to deliver if they want to remain competitive.
  2. Scale and flexibility required – Organizations approaching a practical and modern cross-channel digital strategy have recognized the need for a data environment that is both channel-agnostic and able to handle significant data scale and complexity for diverse and unstructured data sets.
  3. Omnichannel → customer experience – Businesses can no longer strive to simply execute messaging in “every channel” as an end goal. Instead, successful marketers consider their communication strategy with customers and view the channels as a vehicle to communicate effectively.
  4. The walled gardens are winning – The dominance of Google, Amazon, and Facebook’s identity graphs and the decline of the third-party cookie drive a broad shift in targeting strategies. Advertisers are shifting their focus from buying cookie-based audiences on the open web to targeting individual customers.
  5. GDPR and data collection – Regulatory initiatives and consumer sentiment driving such regulations have driven advertisers to focus more heavily on first-party data collection and be more strategic in its use.

In summary:

  1. Successful brands are developing a closer relationship with their customers.
  2. That relationship is increasingly data-driven.
  3. The data requirements and sources to support these relationships are expanding in scope.

The CDP As A Solution to Evolving Needs

Some CDPs trace their origins to the dawn of the internet and digital advertising, while many are purpose-built to address the emerging needs and capabilities addressed above. As a result, the CDP space is an amalgam of different technologies, with varied origin stories and value propositions colliding at the intersection of data and marketing.

As marketing technology systems have felt pressure to become increasingly data-flexible, many non-CDP businesses have partially entered the CDP space or started marketing themselves as CDPs. Traditional marketing technology systems are fighting an uphill battle to build and/or acquire integrated CDP functionality for marketing.

These businesses can broadly be categorized into four buckets:

  • Utility CDPs
  • “Tag Manager” CDPs
  • Marketing Clouds (not actually a CDP
  • Marketing Orchestration CDPs

The Utility CDP

Origin Story:

The Utility CDP coincided with the rise of “Data” as a function within enterprise organizational structures. These CDPs arose as a reaction to DMPs — specifically that CDPs flexibly ingest raw data and apply schema-on-read rather than using a fixed schema-on-write like the DMPs.

Utility CDPs offer database storage solutions or sit on top of existing databases and power data utility workflows. These solutions may provide on-premise options and may not even have a user interface.

Utility CDPs excel at customer record management and integration into legacy databases. Many provide flexible “snap-on” API connectors out into a host of systems. These systems are built to de-duplicate customer records, create a marketing database or data store, and handle the complexities of relational data required for marketing and analytics. Some of these solutions suffer limitations around the use of real-time data for marketing use cases.

Today’s Goal:

Utility CDPs are endeavoring to create more powerful marketing capabilities to move closer to revenue. As such, Utility CDPs are increasingly offering data science solutions and services, and some are investing in marketing workflow capabilities. “Identity Resolution” is a newer term frequently repurposed for capabilities such as fuzzy matching, database cleanup, and probabilistic cross-device targeting, which is an area in which some Utility CDPs excel.

Best For:

  • Companies with “old data” or those seeking to get value out of customer records in legacy databases
  • Companies set on their marketing tech stack, looking for enhanced data capabilities
  • IT teams, or teams well-resourced by IT

The Tag Manager

Origin Story:

Tag managers were born during the rise of adtech with the desire to sync cookies and a host of associated web tags. Tag managers focused on the operational need to add and remove third-party pixels on a website and sync event streams into marketing and advertising platforms.

Over time, these companies worked to capture first-party authentication data and append it to CRM records, moving from the website into a more data-oriented architecture. These businesses are primarily focused on web and app data and anonymous customer records.

Tag managers generally sell to technical and product teams who want to quickly integrate data from one place to another at a low cost. They excel at a narrow scope of functionality with a massive scale.

Today’s Goal:

Some tag managers offer — or are beginning to offer — segmentation and some basic marketing workflow. These businesses are building both toward data and marketing. They aim to increase their realm of available data beyond websites and apps while creating value through a marketer-friendly UI.

Because these companies have massive install bases and are viewed as essential utilities for product and technology teams, they stand a chance of expanding their capabilities within existing clients. Tag Manager CDPs frequently exist in addition to the other types of CDPs discussed here.

Best For:

  • Broadly, everyone
  • Businesses with lots of web/app traffic
  • Technical teams/buyers

The Marketing Cloud

Origin Story:

Marketing clouds were born in an era where sophistication (e.g., segmentation, testing, orchestration) lived in delivery systems (e.g., ESPs, DMPs, CRM tools). As a result, SaaS juggernauts went on a buying spree of technologies they could build into all-in-one marketing clouds.

Many businesses formerly branded as ESPs have branded themselves as “multi-channel messaging platforms” or even CDPs. Losing market share to Salesforce, Oracle, or Adobe’s multi-purpose “clouds” has been another driver behind the branding shift.

Separately, “new age marketing clouds” have emerged, touting their multi-channel capabilities and better user interfaces. Many of these businesses were born outside the email channel as app, push, or SMS targeting vendors. They have since expanded their scope through bolt-on delivery integrations and white-labeling. These businesses are built to win in the marketing cloud space, basically for any business that doesn’t require a built-in DMP (i.e., almost any non-media business).

The challenge with marketing clouds when it comes to capturing CDP market share is that their underlying data model struggles to handle the nuances and complexities of modern data environments (e.g., real-time, data science, relational data, scale, etc.). Further, they rely on APIs/SDKs, which puts the burden on IT teams to conform data to a specific schema and can’t scale well.

Today’s Story:

Marketing clouds are increasingly under pressure to deliver on the breadth of channels in which marketers want to engage their customers and the data demands of the modern enterprise.

It’ll be interesting to see what happens to this space as businesses continue to focus on centralizing data capabilities and increasingly view message delivery (once the remit of marketing clouds) as commoditized. Marketing clouds exist outside of the CDP realm and often exist alongside a Tag Manager CDP, a Utility CDP, or both.

Best For:

  • Teams who are well-supported by IT resources
  • Businesses with advanced marketing orchestration requirements
  • Businesses with existing data/CDP infrastructure supporting data requirements

The Marketing Orchestration/Smart Hub CDP

Origin Story:

Marketing Orchestration CDPs (aka Smart Hubs) are born out of marketing clouds’ inability to deliver against needs in the ever-changing data environment. In some cases, these businesses started as Utility CDPs and invested more heavily in marketing workflow or started as marketing clouds, but are architected on a different data infrastructure. They offer Utility CDP elements around consolidating data across businesses and generally focus on known customers. Their main limitations lie on both ends of the data-to-marketing spectrum: they don’t have all the features of a marketing cloud or a Utility CDP but offer 80% of the middle of the spectrum.

Today’s Story:

Marketing Orchestration CDPs will usually integrate into a Tag Manager CDP to access real-time or anonymous customer data. These CDPs excel at marketing workflow and may even look mostly like using a fully-fledged marketing cloud. They may also offer predictive capabilities.

Given their capabilities and offerings, Marketing Orchestration/Smart Hub CDPs should be evaluated as a replacement to outdated CRM technology and bolt-on to (or potentially even a substitute for) marketing cloud solutions.

Best For:

  • Marketers desiring data-rich environments for campaign orchestrations
  • Teams looking to cut down on IT/engineering support burden
  • Businesses with nuanced/complex data and use cases

Conclusion

The CDP vertical is fraught with buzzwords and feature creep — much like the broader marketing technology space where thousands of businesses claim to be a “true 1:1 omnichannel solution for marketers at scale.”

To better understand both where CDP companies fit within the space and which CDP is the best match for a given business — in addition to the high-level categorization above — teams should start with applications, business value, and use cases to work backward into technical requirements. This seems intuitive, but many teams are still trying to conform their CDP evaluation criteria into pre-existing requirements for CRM tools, database applications, etc.

It will be interesting to see how the space evolves (and it certainly will expand) over the coming years.

Ultimately, there’s significant value to businesses in making investments relative to CDPs. Still, it’s essential that the evaluation approach be outcomes-driven and that teams can cut through the buzz.

Chapter 8: Choosing the right solution for your business

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