Real-time customer data platforms: The promise and the reality

Real-time customer data platforms (CDPs) promise to transform the way businesses collect, analyze, and utilize customer data to drive personalized marketing strategies and enhance customer experiences.

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Delivering relevant messages to the right audience at the right time is the mission of marketers. Being able to deliver messages tailored to specific individuals is the marketer’s dream.

But individuals change, of course. Someone in market for camping gear or scuba diving equipment in July or August may be looking for completely different products in February and March. Someone searching for flights and hotels in May might have already booked their trip by June.

In order for messages to be relevant, they need to be targeted using customer data that is updated in real time — or as close to real time as is practically possible. Can that be achieved using a customer data platform?

Real-time CDPs vs. traditional CDPs

A customer data platform is a marketer-managed system designed to collect customer data from a range of sources, normalize it and build unique, unified profiles of each individual customer. The result is a persistent (but updated), unified customer database that shares data with other marketing technology systems, primarily for the purpose of activation.

In theory, a real-time CDP is able to collect, integrate, standardize and activate customer data from multiple sources in — guess what? — real time. Of course, “real time” is an elastic term. Does it mean instantaneously? In minutes? In hours? By close of business? In practice, as we shall see, the various operations of a CDP typically run at different rates. In simple terms, not everything happens equally fast.

Few vendors in the highly competitive CDP space will tell customers that their offerings are not real-time CDPs. Adobe cut to the chase by naming its offering Adobe Real-Time CDP. Blueshift says that, with its CDP, “customer profiles update in real time with every new activity so you always access the most relevant customer data.”

It’s much harder, if not impossible, to find a CDP vendor that will talk about lag time or delays between customer activity and the updating of the customer profile.

Real time profile updates and data access

The ambiguities get deeper when you ask what is supposed to be happening in real time. A CDP may (indeed should) allow much quicker access to customer data than querying a data warehouse or data lake. It doesn’t necessarily follow that the customer profiles are being updated fast.

CDP and journey orchestration vendor RedPoint Global lists four different aspects of real time in the context of CDP use, arguing that the importance of each will depend on the client’s use cases:

  • Real-time updates. This refers to updating customer profiles in real time with data from source systems — and it relies on those source systems, external to the CDP, to be able to deliver real-time data.
  • Real-time lookup. This is the ability for external systems to access customer profiles in real time “even if it only updates the underlying profiles at intervals such as nightly.”
  • Real-time identity resolution. Updates or lookups are ideally based on a unique identifier that allows the CDP to easily match the input or the request to a single customer profile. Where this is not the case, it may be necessary to run an identity resolution process, attempting to match profiles based on data elements. “This sort of identity resolution can be difficult even without time constraints.”
  • Real-time interactions. Combining updates and lookups, this is the capacity to optimize for interactions while they are happening. For example, optimizing offers to a customer based on their real-time online behavior.

Regardless of whether they present as “real-time CDPs,” not all CDPs offer all these capabilities.

Harnessing real-time data for immediate action

The skeptical view is that the steps from customer data collection to action can rarely happen in anything one would literally call “real time.”

  • Real-time data collection. As already stated, this relies on the capabilities of systems external to the CDP. If those systems provide data in batches it’s going to include old data, even if the ingestion itself happens in real time.
  • Real-time data normalization and standardization. There are ways to do this fast, but it is a step in the process — and if it is set to run periodically, it won’t be running in real time.
  • Real-time AI. Yes, AI models can help with challenges like identity resolution, but again, reprocessing data through an AI model is another step in the process.
  • Real-time segmentation. A CDP may well allow users to segment audiences in real time, but is the segmentation based on real-time data? This may not matter if it makes no difference to a campaign whether data is an hour old or a day old.
  • Real-time activation. The final step of the process requires, again, the cooperation of external systems. No matter how real-time the audience segment, if it’s pushed into a system that then requires some kind of separate, manual triggering, the segment starts to get stale.

Leveraging real-time CDPs for personalization

The purpose of the “single” or “360 degree” view of the customer that a CDP seeks to provide is to allow a high level of personalization when it comes to messaging. Can that happen in real time? MarTech contributor Greg Krehbiel spells out the challenges.

He points out that use cases for real-time personalization can differ dramatically. If the need is to respond to in-session browser behavior, data will need to be ingested and the profile updated at very high speed. If the need is to send relevant messages to a customer who is interested in sports or camping or cooking, month-old data might be adequate.

Similarly, a restaurant might want to send in-the-moment offers to someone (with location services enabled) when they are in the neighborhood. Implementing for that use case will depend, again, on “how frequently the data is updated and how quickly the activation can be orchestrated.”

Dig deeper: Where should a CDP fit in your martech stack?

Benefits and limitations

While there can be no question that personalized messaging, based on data sufficiently recent that the messaging is relevant, is the best kind of messaging, both for the sender and the recipient, that does no more than set the scene for asking whether “real-time” data is required and what “real time” really means.

The CDP Institute defines a CDP as “packaged software that creates a persistent, unified customer database that is accessible to other systems.” Neither in that encapsulated definition, nor in its more expanded explanation, does the CDP Institute mention “real time” — except once, under the heading “Campaign CDPs”:

(T)hey can specify different treatments for different individuals within a segment. Treatments may be personalized messages, outbound marketing campaigns, real time interactions, or product or content recommendations. They often include orchestrating customer treatments across channels.

CDP Institute, “What is a CDP?”

In other words, to be a CDP is not necessarily to be a real-time CDP. Rather than ask whether any particular CDP is or is not a real-time CDP, it’s necessary to list out the tasks or processes it is required to accomplish and examine the speed with which it can complete each item on the list.

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About the author

Kim Davis
Kim Davis is currently editor at large at MarTech. Born in London, but a New Yorker for almost three decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Shortly thereafter he joined Third Door Media as Editorial Director at MarTech.

Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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