Oracle CX Unity Looks Like a Real Customer Data Platform

I finally caught up with Oracle for a briefing on the CX Unity product they announced in October. Although it was clear at the time that CX Unity offered some version of unified customer data, it was hard to understand exactly what was being delivered. The picture is now much clearer. Here are straight answers to important questions:

It’s a persistent database. CX Unity will ingest all types of data – structured, semi-structured, and unstructured – from Oracle’s own CX systems via prebuilt connectors and from external systems via APIs, batch imports, or Oracle’s integration cloud.  It will store these in well-defined structures defined by marketing operations or similar lightly-technical users.  The structures will include both raw data and derived variables such as predictive model scores. Oracle plans to release a dozen industry-specific data schemas including B2B and B2C verticals.

It does identity resolution. CX Unity will support deterministic matching for known relationships between customer identifiers and will maintain a persistent ID over time. It will link to the Oracle Identity Graph in the Oracle Data Cloud for probabilistic matches using third party data.

It activates data in near real time. CX Unity can ingest data in real time but it takes 15 to 20 minutes or longer to standardize, match, run models, and place it in accessible formats such as data cubes. Oracle expects that real-time interactions and triggers will run outside of CX Unity.

It shares data with all other systems. Oracle has built connectors to expose CX Unity data within its own customer-facing CX Cloud systems. APIs are available to publish data to other systems but it’s up to partners and clients to use them.

It integrates machine learning. CX Unity includes machine learning for predictive models and recommendations. Results are exposed to customer-facing systems. This capability seems to be what Oracle has in mind when it contrasts CX Unity with other customer data management solutions that it calls merely “database centric”.

It’s not live yet. The B2C customer segmentation features of CX Unity are available now. The full system is slated to be available in mid-2019.

These answers mean that CX Unity meets the definition of a Customer Data Platform: packaged software that creates a unified persistent customer database accessible by other systems. The machine learning and recommendation features would put it in the class of “personalization” CDPs I defined earlier this month. This is a sharp contrast with the CDP alternatives from Oracle’s main marketing cloud competitors: Customer 360 from Salesforce (no persistent database) and Open Data Initiative from Adobe, Microsoft and SAP (more of a standard than a packaged system).

It's likely that CX Unity will be bought mostly by current Oracle CX customers, although Oracle would doubtless be happy to sell it elsewhere.  But even if CX Unity sales are limited, its feature list offers a template for buyers to measure other systems against. That will create a broader understanding of what belong in a customer management system and make it more likely that buyers will get a CDP that truly meet their needs.  So its release is a welcome development – especially as Oracle finds ways to present it effectively.

Purpose-Driven Marketing Comes to Town

“If you can fake sincerity, you’ve got it made” runs the old joke. The irony-impaired managers of the Association of National Advertisers (ANA) seem to have taken this as serious advice, last week announcing creation of a “Center for Brand Purpose” that will help companies publicize their social purpose. Confirming the worst stereotypes of marketers as cynical hucksters, the press release promotes its mission with the argument that “purpose-led brands grow two to three times faster than their competitors.”

The ANA’s grasp of causation may be no stronger than its sense of morality, but there’s no question it's in tune with the marketing herd.  Issue-based marketing is hot. Another announcement last week illustrates the point: a new program from a coalition of 2,600 socially-responsible “Certified B Corporations” such as Ben & Jerry’s aims to convince consumers to buy from companies that share their values.

Most of the B Corps have a legitimate history of activism. But the broader interest in taking social positions is intriguing precisely because the B Corps have been exceptions to the conventional wisdom that businesses should avoid controversial issues. Studies on the topic show mixed results¹ and that most people care more about practical matters². So why the sudden change?

The simple answer is Nike’s Colin Kaepernick ad, which was initially panned as hurting its image  but was later reported to boost sales.  Marketers being marketers, that was reason enough for many to try something similar.

But I think we can legitimately cite broader trends that have made marketers receptive to the shift. Fox News has demonstrated over the past twenty years that there’s a mass market for partisan bias. The growth of right-wing extremism has led to push-back in support of fairness, reason, and rule of law.  The recent election results can be read as a majority rejection of extremism, although other interpretations are possible.  If there is indeed an emerging consensus that American ideals are under threat, it’s now safer for companies to promote human rights, the environment, and fair employment practices: positions with broad public support despite attacks from the right.

There are other, more parochial reasons for some companies to take strong policy positions. Companies whose customers are concentrated on one or the other side of the urban/rural divide may benefit from polarizing choices: pro-Kaepernick for Nike, anti-abortion for Hobby Lobby. Industries with bad reputations may aim to change public opinion: oil companies touting their environmental concerns are a long-standing example (although this rarely extends to support for policies that would limit their profits).

The most intriguing current set of companies taking trying to change their reputations are the big tech firms which have quickly shifted from fan favorites to villains. Facebook has led the way, with seemingly endless privacy, hate speech, and election scandals  resulting in a huge loss of public confidence and threats of government regulation.  Other big tech firms haven’t been quite so widely criticized but broad concerns about the impact of tech on society are growing ever more common.

Tech companies are particularly susceptible to reputational damage because they need to recruit tech workers, who skew young, educated, urban, and immigrant. The best of those workers have many employment options and want to work at firms that agree with their values. Again, the problem is most severe for Facebook, whose own employees are increasingly concerned that it is doing more harm than good. But employee protests at Google , Amazon and Microsoft tell a similar story.  The recent walkout by 20,000 Google workers over sexual harassment is one more example – and was followed by changes in policies at other tech-driven firms including eBay, Airbnb, and Facebook itself. On the other side of the ledger, Apple has made privacy protection a core part of its own brand, both calling for regulation and resisting government requests to share data. Not coincidentally, Apple’s business isn’t as dependent on consumer data as many of its competitors.

Which brings us back to the original topic. If brands are taking political positions because that’s a good marketing tactic, the insincerity seems reprehensible. It also opens the door to brands supporting socially harmful positions if those are the most popular.  At best, expectations should be limited: no one expects a brand to support a policy that hurts its own business, and in fact we’re used to brands advocating policies that favor them. So any position taken by a business must be viewed with skepticism.³ 

On the other hand, businesses do have a fundamental self-interest in promoting healthy social, political and physical environments. Advocating policies that protect those environments is a perfectly legitimate activity. Publicizing that advocacy is part of the advocacy itself. That it’s now seen as good marketing isn’t new and it isn’t bad: it’s just how things are at this particular moment.

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¹ Edelman, Sprout Social and Finn Partners show consumers want brands to lead on social issues. Morning Consult, Euclid, and Bambu found the opposite.

² InMoment found 9% of consumers care mostly about brand purpose while 39% care mostly about functionality.  The remainder care about both. Waggener Edstrom reports that 55% of consumers say brands can earn their trust by delivering what they promise while fewer than 10% said trust is earned by supporting shared values.

³ Not to mention that brands have been known to attack legitimate research to support their preferred positions, to secretly fund supporters and attacks on opponents, and to say one thing while doing another. 

Why Are There So Many Types of Customer Data Platforms? It's Complicated.

I spend much of my time these days trying to explain Customer Data Platforms to people who suspect a CDP could help them but lack clear understanding of exactly what a CDP can do. At the end of our encounter they’re often frustrated: a simple definition of CDP still eludes them. The fundamental reason is that CDPs are not simple: the industry has rapidly evolved numerous subspecies of CDPs that are as different from each other as the different kinds of dinosaurs. Just as the popular understanding of dinosaurs – big, cold-blooded and extinct – has little to do with the scientific definition, a meaningful understanding of CDPs often has little to do with what people initially expect.

Let’s start with the big picture. I’ve for years divided customer management systems into three broad categories, which are best seen as layers in a unified architecture. Frequent readers of this blog can feel free to recite them along with me (throwing rice at the screen is optional): data, decisions, and delivery.

Refining this notion just a bit:, the data layer includes systems that create customer data and systems that store it in a unified customer database. Decision systems include several categories such as marketing planning and content management, but the most relevant here are analytics, including segmentation and predictive models, and personalization*, which selects the best message for each individual. The delivery layer holds both systems that send outbound messages such as email and advertising and interactive systems such as Web sites and call centers. An important point is it’s hard to do a good job of delivering messages, so delivery systems are large, complex products.  Picking the right message is just one of many features and often developers’ main concern.

A complete architecture has entries in each of these five categories. But many companies have multiple source and delivery systems that are disconnected: these are the infamous silos. The core technology challenge facing today’s marketers can be viewed as connecting these silos by adding the customer database, analytics, and personalization components that sit in between.

By definition, the CDP fills the Customer Database gap. Some CDPs do only that – I will uncreatively label them as “Data CDPs”.

I’ll also take a slight detour to remind you that the customer database must be persistent – that is, it has to copy data from other systems and store it. This is necessary to track customers over time, since the source systems often don’t retain old identifiers (such as a previous mailing or email address) or, if they do keep them, don’t retain linkages between old identifiers and new ones. There’s also lots of other data that source systems discard once they have no immediate need for it, such as location, loyalty status or life-to-date purchases at the time of a transaction. Marketing and analytical systems may need these and it’s often not possible or practical to reconstruct them from what the source systems retained.  This is especially true in situations where the data must be accessed instantly to support real time processes.

But I digress. Back to our Data CDP, which obviously leaves the additional gaps of analytics and personalization. Why wouldn’t a CDP fill those as well? One answer is that some CDPs do fill them: we’ll label CDPs with a customer database plus customer analytics as “Analytics CDPs” and those with a customer Database, analytics, and personalization as “Personalization CDPs”, again winning no prizes for creativity.  A second answer is that some companies already have chosen tools they want for analytics or personalization.  Like message delivery, those are complicated tasks that can easily be the sole focus of a “best of breed” product or products.

This variety of CDPs also addresses another question that some find perplexing: why one company might purchase more than one CDP.  As you’d expect, different CDPs are better at some things than others. In particular, some systems are especially good at database building while others are good at analytics or personalization.  It often depends on the origins of the product.  The result is that a company might buy one CDP for its database features and have it send a unified feed into a second CDP for analytics and/or personalization. There are some extra cost and effort involved but in some situations they're worth it.

Are you still with me?  I’ve presented three different types of CDPs but hope the differences in what they do and which you’d want are fairly clear.**  Now comes the advanced course: other systems that either call themselves CDPs or offer CDP alternatives.

These fall into many categories but can all be mapped to the same set of five capabilities. Let’s start with Marketing Suites, by which I mean delivery systems that have expanded backwards to include a customer database, analytics and personalization. Many email vendors have done this and it’s increasingly common among Web personalization and mobile app marketing products.   In most cases, these vendors now deliver across multiple channels. Adobe Experience Cloud also fits in here. 

To qualify as a CDP, these systems would need to ingest data from all sources, maintain full input detail, and share the results with other systems. Many don’t, some do. We could easily add another CDP category to cover them – “Marketing Suite CDP” would work just fine. But this probably stretches the definition of CDP past the breaking point. For CDP to have any meaning, it must describe a system whose primary purpose is to build a persistent, sharable customer database. The primary purpose of delivery systems is delivery, something that’s hard to do well and will remain the primary focus of vendors who do it. So rather than over-extend the definition of CDP, let’s think of these as systems that include a customer database as one of their features.


We also have some easier cases to consider, which are systems that provide customer analytics and personalization but don’t build a unified customer database. Some of these also provide delivery functions – examples include marketing automation, CRM, and ecommerce platforms. Others don’t do delivery; we can label them as Orchestration. In both cases, the lack of a unified, sharable customer database makes it clear that they’re not CDPs.  Complementing them with a CDP is an obvious option. So not much confusion there, at least.

Finally, we come to the Customer Experience Clouds: collections of systems that promise a complete set of customer-facing systems. Oracle and Salesforce are high on this list. Both of those vendors have recently introduced solutions (CX Unity and Customer 360) that are positioned as providing a unified customer view. It’s clear that Salesforce does this by accessing source data in real time, rather than creating a unified, persistent database. Oracle has been vague on the details but it looks like they take a similar approach. In other words, the reality for those systems shows a gap where the persistent customer database should be. Again, this makes CDPs an excellent complement, although the vendors might disagree.

So, there you have it. I won’t claim the answers are simple but do hope they’re a little more clear. All CDPs build a unified, persistent, sharable customer database. Some add analytics and personalization.  If they extend to delivery, they're not a CDP.  Systems that aren’t CDPs may also build a customer database but you have to look closely to ensure it’s unified, persistent and shareable. Often a CDP will complement other systems; in some cases, it might replace them.

Still disappointed?  I am genuinely sorry.  But if it helps bear this in mind: while simple answers are nice, correct answers—which in this case means getting a solution that fits your needs – are what matter most.




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*I usually call this ‘engagement’ but think ‘personalization’ will be easier to understand in today’s context. For the record, I’m specifically referring here to selecting the best message on an individual-by-individual basis, which isn’t necessarily implied by ‘personalization’.

**If you want to know which CDP vendors fit into each category, the CDP Institute’s free Vendor Comparison report covers these and other differentiators. Products without automated predictive modeling can be considered Data CDPs; those having automated predictive but lacking multi-step campaigns could be considered Analytics CDPs; those with multi-step campaigns could be considered Personalization CDPs. There are many other nuances that could be relevant to your particular situation: the report lists 27 differentiators in all.