\n<\/p>\n
\u201cWho should the primary user of my CDP be?\u201d
\u201cWhat should the team look like supporting my CDP effort?\u201d
\u201cWho should own this initiative?\u201d<\/p>\n
Brands adopting a CDP often ask me a version of these questions over my 10+ years in the space. I\u2019ve trusted answers born of experience earlier in my career for a long while. However, a lot has changed in the marketing technology space. <\/p>\n
It\u2019s worth reconsidering who the user is for your CDP \u2014 especially in light of advances within \u201ccomposable CDP.\u201d Hint: It\u2019s not one person or one role. More to come on that.<\/p>\n
<\/p>\n
Let\u2019s recall what a customer data platform is. David Raab, the godfather of CDPs and the person credited with first recognizing its growing significance in marketing technology, deserves some recognition here. He founded the CDP Institute, which defines a CDP as \u201cpackaged software that creates a persistent, unified customer database that is accessible to other systems.\u201d\u00a0<\/p>\n
Many CDPs have tried to embrace marketing as the core user. MarTech published this article<\/a>, which calls out CDP as \u201cmarketer-managed.\u201d This fits with my recollection of history. <\/p>\n 2017 was a watershed year where I witnessed firsthand a massive influx of new clients to the Lytics CDP during my time there running customer success. At that time, it was accepted that CMOs would outspend CIOs<\/a> on technology.<\/p>\n My how things have changed. Fast forward from 2017 to 2024:<\/p>\n Marketers today are often confounded by these cataclysmic shifts in the landscape they operate. They need the owners of enterprise data to be a key partner in the journey. Thus, The CMO is a key influencer in the CDP decision that a committee \u2014 usually led by IT \u2014 makes. This is especially true in the composable paradigm, where IT-driven architectural paradigms govern marketing technology decisions.<\/p>\n There are exceptions to this rule \u2014 but let\u2019s accept that the CDP decision is no longer a \u201cmarketer-managed\u201d decision and accept the broad reality that CDP decision and usage have shifted as the buying dynamics have shifted over the last five years. Let\u2019s also accept that the buyer and the user of the CDP may be different.<\/p>\n Historically, I used to contend that semi-technical users supporting marketing operations were the ideal users of most CDPs. These users were focused on supporting use cases, marketing data and campaign reporting. Importantly, they interfaced with enterprise data, analytics and marketers.\u00a0<\/p>\n Yet, the CDP could not subsist on MOps alone, so this group required significant collaboration from engineers: data engineers to feed offline data to the CDP and front-end engineers to ensure key data, audiences and events were functional in marketing channels. Analysts and digital marketers rounded out the CDP center of excellence.\u00a0<\/p>\n The former was on tap for complex reporting and insights, supplementary data enrichments and often for simple data feeds that were a lower priority for the enterprise data engineering team. The digital marketer usually made decisions about marketing use cases, such as how audiences and customer attributes would be used in ads, email, site personalization, push notifications, etc.<\/p>\n This paradigm mostly worked with the decision-oriented CDPs I\u2019m most familiar with \u2014 Lytics, ActionIQ, BlueConic, Simon and Blueshift. But I noticed it breaking down with product-oriented clients where technical users were most commonly the CDP leads. We saw these more with clients on Adobe, mParticle and Segment \u2014 who have often courted CIOs and the technical organizations underneath them. With the more data and IT-focused platforms, we tended to see product engineers be the main users for data routing, with marketers as a secondary consideration.<\/p>\n Dig deeper: 3 points to consider before implementing a CDP<\/a><\/em><\/strong><\/p>\n There have been notable dialogue forced in the space by new entrants such as GrowthLoop, Hightouch and Census. Traditional CDPs such as Lytics and ActionIQ have responded by adding noteworthy reverse ETL capabilities in \u201cCloud Compute\u201d and \u201cHybridCompute,\u201d respectively.\u00a0<\/p>\n The composable paradigm<\/a> is here to stay. Working with pre-existing data in a data warehouse offers theoretically faster time-to-value, lower total cost of ownership (TCO) and improved data security since key data does not need to be replicated in another system.<\/p>\n Composable CDPs encounter several hurdles in reaching enterprise value. Technology changes much faster than the rate of human beings\u2019 ability to adapt to those changes. Political and organizational friction exists inside companies \u2014 even small ones. <\/p>\n Changing a process to incorporate first-party data better can be difficult \u2014 and a burden of proof of being the challenger to \u201cthe way we do things.\u201d But there are some things that adopters of composable CDP ought to consider.<\/p>\n Composable CDPs are the client\u2019s product. It\u2019s their database and the composable CDPs are working primarily to unlock key capabilities in the data warehouse to support first-party data-driven use cases, marketing analytics and new features in the database. <\/p>\n This person can highlight key missing data elements of the customer journey and organize internal workstreams to address gaps in capabilities.<\/p>\n Dig deeper: 4 CDP strategies to unlock the power of first-party data<\/a><\/em><\/strong><\/p>\n As CDPs have grown in prevalence in the enterprise marketing stack, so too have the focus of enterprise customer insights teams on first-party data activations. During the early days of CDP, the customer insights team was often a dubious detractor who focused on bespoke insights from customer data that didn\u2019t connect tightly to downstream, in-channel activations.\u00a0<\/p>\n By 2024, enterprises have determined that the customer insights team has better command of the data. The customer insights team can usually better interpret data nuances to business value in a way that today\u2019s marketers cannot. These teams now must support segmentation, real-time decisioning and journey orchestration in a manner not conceived in the \u201cmarketer-managed\u201d paradigm of yesteryear.\u00a0<\/p>\n A key component of this is AI-driven segmentation<\/a>. The customer insights \/ marketing analytics team sits in a great place to vet how to best leverage internal data science and capabilities associated with marketing technology tools or the CDP itself.<\/p>\n Composable CDPs, built directly on a client\u2019s cloud data warehouse, offer a unique ability to blend generative AI capabilities of the cloud with marketing campaigns in a seamless way.\u00a0<\/p>\n The barriers to creating good generative AI on top of the existing tools that OpenAI and Google Cloud provide are low. I can say, with firsthand experience, that one of my companies, Predictable, has built very good POCs of generative AI capabilities inside three sprints. <\/p>\n Composable CDP adopters should consider enabling business users to build segmentation using generative AI to democratize further segment-building to in-channel marketers.\u00a0<\/p>\n AI-generated customer-facing creative for marketing campaigns will face a tougher challenge. In the near term, generative AI in customer-facing applications will be confined to subject line testing, basic copy, call-to-action tests and subtle personalization of images for highly segmented campaigns. However, much of this may fall to the channels themselves. For example, generative AI in Google Ads, your ESP for subject line testing or your Adobe Creative Cloud for image assets.<\/p>\n Whether your strategy is to build a composable CDP of multiple complementary technologies or choose a CDP that provides all CDP capabilities in one package, it is a fundamentally cross-functional effort.\u00a0<\/p>\n Be intentional about your center of excellence. Build a complementary team with diverse skillsets and make sure you stay current with this rapidly evolving landscape.<\/p>\n <\/p>\n Get MarTech! Daily. Free. In your inbox.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n \n<\/div>\n Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here<\/a>.<\/em><\/p>\n\n
Who are the CDP users historically?<\/h2>\n
What about composable CDPs?<\/h2>\n
1. The product owner<\/h3>\n
2. The customer insights\/marketing analytics team<\/h3>\n
ML engineering for generative AI<\/h3>\n
What aspects of the center of excellence are the same with composable and traditional CDPs?<\/h2>\n
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