Uniphore Buys ActionIQ: What We Can Learn

Acquisitions of, or by, major CDP vendors have been vanishingly rare in recent years.  So news that ActionIQ  had been purchased by Uniphore generated an especially large amount of interest.  Let’s look at it from three perspectives.

1.    Significance for ActionIQ.  Although ActionIQ has been a significant CDP since its founding in 2014, the company was always a bit different from most other CDPs.  Rather than starting as a tag manager or messaging platform, ActionIQ’s roots were in big data technology: co-founders Tasso Argyros and Nitay Joffe were, respectively, the founder of big data engine Aster Data (purchased by Teradata in 2011) and a leading data engineer at Facebook.  Not surprisingly, the company’s approach to CDP was also driven by data technology: in particular, it used in-memory storage to support high volume, real time use cases.  In recent years, the company evolved its technology to offer component-based and warehouse-native options in addition to a conventional integrated CDP.

The company’s business results were less stellar than its technology.  It primarily targeted large enterprises that could most benefit from its sophisticated approach, and had reasonable success in that market.  But, despite raising a hefty $144 million (per Crunchbase), growth stalled in recent years.  Headcount, which stood at 208 in mid-2021 (per LinkedIn) has declined steadily since then and last week was 161.  We don’t know whether sales also fell; it’s likely that the headcount reductions reflected preemptive belt-tightening as new funding became less available, rather than tracking an actual revenue decline.  

Either way, it doesn’t seem that ActionIQ was on a path for substantial growth as an independent company.  So a sale to a friendly buyer like Uniphore makes good sense.  I’m told that the ActionIQ product itself will continue to be sold, supported, and developed, so it’s a good outcome for ActionIQ customers as well.

2.    Significance for Uniphore.  I’ll admit I wasn’t familiar with Uniphore before this deal, even though they are in fact a well-established, fairly large company (founded in 2008, 800+ employees, $621 million in funding).  Their specialty has been speech-related customer experience tech, such as self-service, phone agent and sales assistance and conversational analytics.  Like others in that industry, they are currently focusing on enhancing their products with AI to improve worker productivity and business results.  

What’s more interesting is where they differ with the competitors, which is a greater focus on the data infrastructure needed to support AI.  This is where the ActionIQ acquisition makes sense, since it will help to support what Uniphore calls the “Zero Data AI Cloud”.  As the name suggests, Uniphore’s vision is to provide AI systems with data without first exporting that data into a separate database.  This is the “zero copy” or “warehouse-native” approach that’s increasingly popular in CDP circles.  It’s also something that ActionIQ has evolved to support, so the acquisition is strategically sound.  As you’re probably aware, Uniphore also announced its acquisition of Infoworks at the same time as the ActionIQ acquisition.  Infoworks is an even more technical vendor, dedicated to managing cloud data migrations.  At 75 employees and $71 million in funding since it was founded in 2014, it's smaller than ActionIQ but still a substantial business.  Like ActionIQ, its head count has also fallen in recent years, from a recent peak of 112 in early 2023.

Uniphore’s pivot to AI data infrastructure seems like a good move, at least compared with the hugely overcrowded AI-based CX marketplace.  I think “pivot” is a fair term here, since Uniphore’s earlier acquisitions – Hexagone and RedBox in 2023, Colabor in 2023, and Emotion Research Labs in 2021 – all firms applied AI to more conventional CX use cases, such as emotion detection and conversation analysis.  Of course, the data infrastructure space itself is the playground of major cloud companies like Google and Amazon, as well as cloud data firms like Snowflake and Databricks.  Whether Uniphore can carve out a unique niche for itself as a tooling provider to connect those systems is uncertain but it seems worth a try.

As an aside -- I don't think a true "zero copy" approach to AI data is really possible.  We had this debate in the early years of the CDP industry, when companies including Salesforce and Adobe argued they could assemble customer profiles on the fly without a persistent database.  They ultimately learned that didn't work.  This doesn't invalidate Uniphore's strategy, even though the actual implementation will almost surely involve extracting, cleaning, and reorganizing data and storing the results somewhere that AI systems can use it.  That "somewhere" could in fact be a data warehouse -- the approach favored by composable CDP vendors.  This might more accurately be called "one copy" than "zero copy," although it wouldn't sound as appealing.

3.    Significance for the CDP Industry.  ActionIQ’s decision to sell to Uniphore obviously says something about the prospects for independent CDP vendors, but the implications are limited because ActionIQ’s technology was atypical.  In fact, since ActionIQ already supported the “composable” and “warehouse-native” approaches that are often touted as successors to traditional CDP systems, you could argue the deal indicates that prospects for firms taking those directions are more limited than their advocates believe.  

Given ActionIQ’s unique situation, I don’t think this deal presages a sudden burst of exits by mid-tier CDP vendors.  Even though growth has largely stalled for those firms, I think most can keep afloat long enough to find their footing in a new world.  This footing may well differ for different firms: for example, we’ve seen Lytics attempt to simplify CDP deployment enough to make it accessible to smaller businesses, while mParticle is moving more in the direction of combining customer data with analytics.  All need to dodge the giant cloud, cloud database, marketing cloud, and messaging vendors who are trampling the heart of traditional CDP territory.  Some will indeed take shelter within larger organizations like Uniphore.  Others may stay independent but retreat to niches such as data management tools or serving specific industries.  So even though the market for traditional, integrated CDP products is likely to shrink, I believe most of the vendors will survive in some form or another.  This is because the fundamental need driving CDPs – the need for unified, accessible customer data – will only grow stronger.  Companies that find a profitable way to meet that need will be able to thrive over time.

Composable CDP is Dead

Composable CDP is Dead. Sure, it’s a clickbait headline. But how else to gain attention on a topic that’s over-saturated with hype?

Of course, I would never say something untrue just to gain attention. So let me clarify exactly what’s deceased. It isn’t composability or CDP, or the vendors who have adopted the “composable CDP” label. What’s dead is “composable CDP” as a distinct category of software.

You might stop here to argue that “composable CDP” was never a meaningful category, and I wouldn't necessarily disagree. But the term did have a broad meaning along the lines of “software components that provide functions needed in a CDP.” What made it useful was the contrast with packaged (a.k.a. standard, conventional, traditional, integrated, or just plain “real”) CDPs, which, according to the CDP Institute definition, provide a complete set of CDP functions – specifically, the functions to collect, organize, and share customer profiles. Companies that wanted to build their own CDP, possibly using their existing data warehouse as a base, could use the “composable CDP” label to identify products that might help with their project.

What’s changed is that many of the packaged CDP vendors quickly caught on to the demand for CDP components and split their products into modules.  This let companies buy only the functions they needed and apply those functions to data in a cloud data warehouse. The repackaging is easier for some vendors than others, depending on how their products were originally built. But enough of the original CDP vendors now offer some flavor of CDP components that companies looking for components to build an in-house CDP should consider them as well. Thus ends the utility of “composable CDP” as a category. RIP.

The composable CDP vendors saw this day coming. Many have switched their positioning to "warehouse-native," which is more accurate and reduces the focus on point solutions.  But their main strategy has been to move beyond offering a single component for a single function – that is, their original product – to offer multiple components and a complete set of CDP functions.¹ The change to offering a complete solution weakens some of the composable vendors’ original sales arguments, including the superiority of “best of breed” solutions and the ease of swapping components from different vendors “like Lego blocks”. But it also allows new arguments, including the virtues of buying multiple preintegrated components from the same vendor and the value to end users of working with fewer tools. If any of the vendors feels embarrassed at switching from one side of the debate to the other, I haven’t noticed.

Then again, there’s no reason they should be ashamed. Products naturally expand their footprints: it’s a marketing truism that it’s easier to sell new products to existing customers than to sell existing products to new customers. And CDP buyers clearly prefer integrated solutions: according to the CDP Institute Industry Update, nearly three-quarters of CDP products extend beyond profile creation to include marketing execution. In practice, only very large companies can afford to build custom solutions by cobbling together “best of breed” products. I summarized this years before CDPs existed as “Raab’s Law”, which states that “Given a choice, most buyers prefer suites over best-of-breed solutions.” The pithier version is “Suites win.”

This doesn't mean that most companies actually use integrated marketing suites.  The majority clearly do not.  In fact, a recent Acxiom survey found just 17% of marketers plan to move to a suite in the next twelve months; the rest are using multiple products and 29% expect to add more.  Reasons companies don't adopt suites include cost, agility, and the lack of required functions.  Still, when you look at marketing software categories including campaign management, journey orchestration, analytics, and email execution, leading independent vendors have been acquired by suite owners and the remaining independents are largely relegated to niche segments or have expanded to become suites themselves.  This is what the composable CDP vendors are doing.

Wait, did I just say that an integrated CDP is a software suite? To some degree, yes: in the finest Alice-in-Software-Land tradition, words mean whatever I want them to mean.²  But the less flippant answer is that it depends on your perspective: in discussing CDP functionality, a single product that provides all necessary functions does look like a suite, while components for individual functions look like point solutions. But if you raise the perspective to marketing architecture, the CDP itself might be a single component alongside content management, marketing automation, email, and media buying components, while a marketing suite like Adobe would encompass them all. Go up to the enterprise level, and the marketing suite could be one component alongside finance, human resources, and operations, compared with an enterprise-wide suite like SAP. 

It’s possible that Raab’s Law begins to weaken above the departmental level, where conflicting managers are powerful enough to insist on their own systems rather than accepting the loss of control implied by a shared system. Feel free to explore this on your own. What matters here is that talk of components reintroduces the topic of composability. 

Although composable CDP only entered the martech discussion about two years ago, the broader label of composable architecture began to build momentum around 2020.³ Today it’s applied to nearly every type of software, and we see composable-oriented organizations like MACH Alliance expanding their scope accordingly.⁴  

There’s actually a good chance that composability has hit its peak on the hype cycle, as greater experience gives practitioners a better understanding of its limits. As with composable CDP, these primarily involve integration costs and support complexity.  They also include scaling challenges to move large volumes of data between large numbers of components, and problems when one weak component drags down performance across the entire structure. Call it the Revenge of Raab’s Law.

For composable CDP in particular, experience has also revealed high processing costs when everything is done within a cloud data warehouse.  (This is why cloud data companies like Snowflake and AWS are so enthusiastic about the warehouse-native CDP approach.)  Users have also discovered that the cloud data warehouses struggle with certain kinds of real-time processing, a core requirement for many CDP applications.

This more realistic understanding of composable limitations doesn’t mean that composability is dead. Marketers were never really all that interested to begin with: just 3% in the Acxiom survey said they plan to move to a composable strategy in the next 12 months, compared with 17% moving towards a suite.⁵  The people who really care about composability are the technicians: when Messagegears surveyed people interested in “data cleaning and quality control,” 56% said they prefer a composable architecture and 33% had no preference, leaving at most 11% in favor of packaged systems. 

But don’t get too excited, composable fans: preference isn’t the same as intent, let alone action.  You can bet many of those technicians won’t be able to make the changes they’d prefer.⁶  Still, the technicians’ views matter a great deal because growing use of customer data beyond marketing gives IT and data teams a larger role in selecting customer data systems.

Will technicians get over their infatuation with composability? Only time will tell.  But it’s likely their ardor will cool as they learn more about it and get distracted by whatever Big Thing comes Next. 

This doesn’t mean the the pendulum will swing back to favor traditional, integrated CDPs. Rather, as Hegel would have predicted, we can expect a synthesis where most customer data is assembled and remains in the warehouse, but some functions are executed outside of the warehouse in a CDP that reads the warehouse data directly. In this world, traditional CDP functions such as data ingestion and identity management become components that operate within the warehouse, while functions such as real-time response, analytics, and journey orchestration become part of a separate, internally-integrated component that can reasonably be labeled a CDP.

The composable CDP is dead. Long live the CDP components. 

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1. The definition of “complete” varies from vendor to vendor, and inevitably matches whatever components the vendor has available at any particular moment. But that approach is common throughout the software industry, so it doesn’t’ represent uniquely deceptive behavior by the composable CDP camp.)

2. See the previous discussion of “complete.”

3. The idea of building systems from components has been around much longer than the label, using terms such as micro-services architecture and headless CMS. CDP itself is also much older than four years. All these terms are much more widely used than composable architecture and composable CDP. 

 

4. I’ve never spoken with anyone at MACH Alliance, but surely they face the same struggles maintain consistent definitions and standards as the CDP Institute. Fun fact: while several of the traditional CDP vendors have met the rigorous standards required to join the MACH Alliance, none of the composable CDP vendors are members. 

5. The remainder intend to muddle through with their current crazy wall of loosely connected applications, while complaining about integration cost and feature overlap.)

6. How big is gap between preference and planning? Well, in the Acxiom survey where 3% of respondents said they plan moving to a composable approach, 36% said they thought a “modern sophisticated marketing stack” should have a composable architecture. Let’s call them composable-curious. Of the rest, 38% cited an integrated marketing suite, compared with 17% planning to move in that direction, and 34% chose a best of breed approach, compared with about 80% living that particular dream. 

CDP Round Table: Forget Composable, Are Cloud Databases a Threat to CDPs?

On July 16 and July 18 2024, the CDP Institute hosted a pair of online roundtable discussions for industry vendors. Here are summaries of the conversations.

 

July 16 Roundtable - U.S. and Europe participants.

We started with a quick list of trends that the Institute is watching. These include Composable CDP, CDP integration with advertising channels, third-party cookie deprecation, vertical (industry-specific) CDPs, and AI applications in CDP systems.

The discussion quickly focused on Composable CDP. Key points included:

•  Replacing the term “composable” with “warehouse native”. This is more accurate and resonates in particular with data and IT teams, who want to get the most use from their warehouse investments. “Composable” is still more commonly understood among marketing users.
• Composable CDP comes up most often at large enterprises, which have the most mature IT and data resources.
•  Composable also has appeal in healthcare and financial services, where regulatory concerns make companies reluctant to copy data into a separate CDP database. (Note: I have also heard the opposite, because IT and data teams don’t want to give business users direct access to their entire warehouse and would rather provide them with a limited extract.)
• Digital native companies are also good prospects for Composable because they tend to have well managed data already in place.
•  Composable promises a faster start than building a separate CDP, which is appealing to all potential users. Whether this really happens depends on the state of existing data sources and warehouses.
• Composable CPDs have an advantage because the company’s existing warehouse will include both customer and non-customer data elements tailored to company and its industry. Standard CDPs often must build a custom data model for each new industry, and may struggle to include non-customer information such as product data. Vertical CDPs are appealing because they have industry-specific data models already in place.

Other observations:

• The fast growth of cloud databases, and Snowflake in particular, is a threat to packaged CDPs because they make it easier for IT to build their own products. So far, the cloud databases haven’t built in key tools such as data quality and ID resolution, but there are indications that will change. Such tools are already available as pre-integrated applications in the cloud database vendors’ marketplaces. This is worth calling out as a separate trend from Composable CDP.
• The data engineers who buy cloud databases are not aware that CDP systems exist. They see the value when it’s explained to them, but are still likely to want to expand use of their warehouse systems to justify the investment. This is true even if the warehouse doesn’t already have rich customer data features and customer data has been a low priority. “Data-in-place” and “zero-copy” are strong selling points against putting data into a separate CDP.
•  Regulatory changes, such as anti-redlining rules for banks and Sunshine laws for healthcare marketing, have driven investments in customer data in the past. Privacy regulations may play a similar role in the nature future. This is also worth calling out as a trend.
• There is limited convergence between CDPs and privacy systems. Few CDP vendors have invested in privacy features beyond ingesting consent data, possibly because privacy is complicated so it would take a major investment. In addition, privacy systems have different buyers from CDPs, and privacy managers feel it’s safer to buy from OneTrust than lesser known vendors. But basic privacy and security always requirements in CDP RFPs.
• Journey orchestration is available in many CDPs, which means they overlap with existing journey orchestration systems. But very few clients will replace a mature journey orchestration system with a CDP, due to the effort involved in training staff and migrating programs. Most CDPs with extensive journey orchestration and messaging capabilities are vendors that started as journey orchestration and messaging products and added a CDP capability. Journey orchestration and messaging systems that connect directly with a warehouse may pose another threat to CDPs.
• Advertising integration is often the first CDP application in Italy and elsewhere in Europe.

July 18 Roundtable - APAC participants

Industry trends

• Overview: composable, cloud database, advertising integration, cookie deprecation, privacy & compliance, vertical industry CDPs, AI
• Seeing lots of requests for clean room and consent management, and how CDPs can merge those to streamline work for customers. Some parts of consent can be managed in CDP, others should be in separate platform. Privacy is often first use case.
• Among companies with CDP already deployed, often see extension beyond marketing to other departments. CDP often leads to teams within marketing working together that before kept separate.
• When a new CDP is deployed, people become aware of it organically and through analytic reporting that uses CDP data.
• Cloud databases and composable CDPs introduce new buyer personas from IT and CTOs, who have different use cases and technical concerns from marketers. 

Other items

• Understanding of CDP is relatively low in SouthEast Asia (SEA), compared with Australia, India and Japan.
• Composable is mostly raised by IT teams, who are looking for easiest path to moving data from one platform to another, without understanding the strategy behind the CDP project. Applies to both small and large organizations. Companies like Salesforce with a lot of installed products can co-exist with composable.
• Companies can easily identify many use cases for a CDP. Vendors spend time helping them to prioritize. The sales process is sometimes slowed because buying teams are overwhelmed by the number of use cases.
• Greatest interest among marketers is performance marketing use cases, where results can be directly measured, such as data activation, segmentation, and pipeline-to-paid. This is limiting because there are so many other use cases that don’t have immediate results, such as brand building.
• Advertising is often an early use case, since simple things like suppression and lookalike audiences from CDP can generate immediate, measurable result.
• It’s usually easy to build a use case for CDP looking at almost any part of the lifecycle, from acquisition through churn reduction.
• Confusion about CDP definition can slow down sales, because there are so many different vendors that are hard for buyers to differentiate. The products have changed over time, starting from data capture and now moving to integration with cloud data warehouses and activation in multiple engagement channels, including those outside of marketing.
• It’s not clear whether growth in composable and cloud databases has caused a drop-off in selling stand-alone CDPs. CDP Institute industry update report shows that growth has definitely slowed in the past 18 months, but we don’t know the reason. The slowdown might just mirror the general tech employment slowdown post-covid, and it’s possible that the companies buying composable and cloud databases would have built their own solution anyway, so they were never the companies fueling growth of stand-alone CDP.
• Composable in APAC is having more of an impact in the small to medium sector than with big enterprises.
• AI requires higher data quality.
• Companies feel competitive pressure to invest in AI but are moving slowly, in part due to privacy and security concerns. CDP vendors have added both predictive and generative AI to their systems. Predictive AI deployments are much further along and we’re now seeing initial deployments of generative AI.
• Generative AI is being used to automate existing tasks but not yet to transform tasks. Expect to see more impact next year in terms of benefiting system users, developers, and ultimately at touchpoints where it will change the customer experience itself.
• Generative AI will eliminate some jobs and create others, probably for a net positive impact. People can view AI as a centaur that helps them do their work or a cyborg that takes over their job completely. There are many issues to work out from an enterprise perspective before generative AI becomes widely adopted.