Has your organization invested in a customer data platform (CDP) only to find that it's not living up to its promise?
You're not alone. In fact, Digiday reports that only 10% of marketers who have a CDP believe it’s fit for purpose while an even smaller amount (1%) feel certain their CDP will stand up to the requirements of tomorrow. And MarTech.org highlights that 45% of marketers report that their CDP has underperformed against business expectations.
Despite these disappointing statistics, a well-functioning CDP is still essential for tackling the top six MarTech challenges reported to the CMO Council. These challenges include nonintegrated MarTech, inability to integrate customer data sources, inability to link online and offline customer identities, poor data quality, lack of technical agility, and inability to track online behavior.
Results were similar on the business side, with low maturity rates reported to the CMO Council for critical customer experience capabilities that make up key CDP use cases. Less than 20% of marketers reported maturity in delivering real-time personalized interactions, turning customer insights into actionable outcomes, balancing personalization and privacy, and coordinating messages and interactions across all channels.
So, why is there such a gap and disconnect between the CDP’s promise and performance? One of the main reasons is the disjointed MarTech landscape.
A disjointed MarTech landscape
I have talked about the complexity of the CDP marketplace before. But it’s important to reiterate that there are currently more than 170 vendors, 60-plus different use cases and at least four different types of CDPs in play today. Delving deeper into the makeup of these vendors illuminates some of the issues marketers are experiencing with their CDPs.
CDP vendors can be roughly classified into two categories: large marketing cloud vendors and standalone CDP vendors. Each type of vendor may be either a good or bad fit for an organization depending on a variety of factors, including required use cases, existing MarTech capabilities, architecture and original purpose.
Let’s explore the two types of CDP vendors in more detail.
Large marketing cloud vendors
The CDPs included in these vendor offerings fall into the CDP Institute classification types of Campaign or Delivery. They provide a full set of multichannel marketing capabilities that go beyond basic CDP requirements of data ingestion, profile unification, segmentation and data provisioning.
These vendors are worth considering when marketers want to satisfy a wide variety of use cases, including more sophisticated analytics, journey orchestration and activation, which includes the ability to deliver marketing campaigns and communications directly to owned channels and third parties.
The downside of large marketing cloud vendors
However, there are several potential gotchas with many of these vendors that bear investigating before purchase. Many large marketing clouds have grown not through native product design, but instead through acquisition. Therefore, they use a “layer approach” where multiple clouds for various purposes are all required, where integration between clouds or acquired products is scanty, and where data must be duplicated into the CDP and sometimes also across clouds.
These applications can struggle with execution, particularly where capabilities such as real-time updates of segments, profiles or communications are required.
MarTech costs are higher due to data duplication, and feature overlap – both within the CDP/marketing cloud and across your MarTech stack – can be a significant issue.
Limited execution and higher costs are especially detrimental considering Gartner's findings that MarTech utilization has declined sharply, falling from a 58% utilization rate in 2020 to just 33% in 2023. To further compound the issue, Gartner also found that 75% of CMOs are being pressured to cut MarTech spending.
So it’s important to consider that you may be paying for similar features across different applications (due to feature overlap) or have difficulty incorporating emerging technologies such as generative AI into your marketing stack. Plus, it might be harder to react to changing customer demands or perform critical CX capabilities.
Another consideration is that these applications are often licensed due to incumbency rather than by doing a detailed fit analysis. They’re bought simply because other solutions from the vendor are present – as opposed to being sold on the actual merits of the solution or unique needs of the company. As a result, there’s great potential for the CDP to drastically underperform against business expectations.
Standalone CDP vendors
These vendors generally offer less extensive capabilities than marketing cloud applications, falling mainly into the CDP Institute classifications of Data and Analytics CDPs. They are typically focused on specific use cases (such as data processing) or business segments (such as small to medium businesses, aka SMBs). Organizations that don’t have consolidated customer information or do not need the extensive capabilities offered by a multichannel marketing hub may benefit from this type of CDP. However, as with the large marketing cloud vendors, these CDPs also have gotchas to look out for.
The downside of standalone CDP vendors
Many started out not as a CDP, but as a different type of application – such as tag management, identity resolution or a data management application. The problem here is that many of those applications didn’t have the basic four CDP capabilities (ingestion, unification, segmentation, provisioning) and some still don’t. Where those capabilities have been added, the same type of integration issues can arise as with the marketing clouds.
Most, if not all, of these solutions also require all the data to be loaded into the CDP to use them. This can introduce significant security, privacy, risk and cost concerns as data is duplicated numerous times. Additionally, the time to load each new data source can be extensive, dependent on IT time and resources, and can significantly lengthen the marketer's journey.
Another emerging issue with this type of vendor is that reverse ETL vendors are jumping into the CDP space as standalone vendors. Although these vendors term themselves as a CDP, that claim is questionable.
LXA highlights the differences between reverse ETL applications and CDPs: “Reverse ETL is focused on syncing data from the destination back to the source systems, while CDPs are focused on collecting and managing customer data from various sources. Reverse ETL is ideal for organizations with data scattered across various systems and a need to keep it in sync. CDPs, on the other hand, are ideal for organizations that want to create a unified customer profile and use it for various marketing and analytics purposes.”
As with the large marketing cloud vendors, if organizations don’t carefully map capabilities to required use cases, the standalone CDP solutions could also end up in the “not fit for purchase” category.
There’s no downside when it comes to SAS
SAS Customer Intelligence 360 is a customer engagement platform that provides organizations with the customer data platform, journey creation and activation capabilities that enterprise marketing cloud and standalone CDP vendors can't provide.
Being able to activate data in SAS Customer Intelligence 360 while applying AI and machine learning techniques, such as customer journey optimization, allows us to continue as customer engagement leaders. It’s truly an exciting time.
– Melissa Berscheid, Senior Director of Member Marketing and Technology, Ulta Beauty
Native architecture
Unlike cloud vendors who added CDP capabilities by acquisition, SAS has built a native architecture from the ground up – so there are no integration issues across the platform. It’s easy to connect to existing MarTech stacks because SAS provides out-of-the-box connections to cloud-based data sources, an extensive API connector framework, and bidirectional connectors to applications across and beyond the MarTech environment.
True composability
SAS offers true composability in both data and capabilities. Our native hybrid data architecture does not require organizations to move all the data into the CDP or marketing cloud in order to use it. Choose only the analytics, decisioning and channel activation capabilities that make sense for your use cases.
Real-time capabilities
Organizations will get real time that’s truly real time – plus a comprehensive customer view that tracks online behavior, synchronizes known and unknown identities, and links online and offline data.
SAS delivers real success
With SAS, The Nature Conservancy no longer needs to outsource to various marketing technology vendors. All data sources are organized in SAS’ customer data platform, which further enhances The Nature Conservancy’s ability to prioritize its supporters’ data privacy and security. With SAS Customer Intelligence 360 in place, The Nature Conservancy has seen its donor retention rate improve 10% and its year-over-year giving increase 30%.
Ulta Beauty turned to SAS to aid in transforming its abundant data sources into easily activated and comprehensive customer journeys with SAS Customer Intelligence 360. Automating and personalizing its marketing efforts has helped Ulta Beauty achieve an impressive 95% sales penetration, meaning 95% of sales come from returning guests.
