Since customer data platforms (CDP) emerged in the marketplace about five years ago, there has been debate about what roles they fill, especially within customer service organizations. They were originally developed by small software firms to provide marketing teams with a comprehensive view of customer records. Those records could be scattered throughout an organization, siloed by system and department. CDPs were an attempt to shortcut integration processes that are long, expensive and often custom-designed.
Customer service departments, primarily contact centers, collect considerable customer data, usually stored in a CRM system. That data is mostly transactional, but also includes interaction recordings and transcriptions that can be analyzed for insight into behavior and sentiment. CDPs represented the first true effort to unify contact center data with broader data sources. On the marketing side, CDPs play a role in personalization, journey analysis, orchestration and campaign design.
In my colleague David Menninger’s recent Ventana Research Analyst Perspective, he noted that a modern data platform must not only provide a way to manage big data but also must provide the functionality to analyze that data, run machine learning algorithms for forecasting, and share that data across various departments with minimal friction to make use of that data. Organizations cannot afford to waste precious time and resources tying together various, separate specialized platforms to meet different data processing and analytic requirements.
With a mix of use cases across departments, CDPs step in and provide that bridge, particularly between service and marketing, especially benefitting the latter teams. By allowing non-contact center teams to pull data from customer interactions themselves, a CDP can elevate marketing capabilities without requiring the heavy lift of a digital transformation project or custom data integration.
CDPs are attractive because they address some of the most important challenges and pain points in customer experience design: inconsistencies in interactions due to fragmented data, and complexity of data governance issues. As the amount of customer data grows, better experiences can be built using data-driven contextual cues. At the same time, data proliferation creates operational obstacles. CDPs provide a mechanism for tying each piece of data to a unique customer profile, and then acting upon it.
One of the key questions surrounding CDPs is whether they are a permanent fixture of the modern tech stack, or whether they are a transitional technology. Early CDP vendors correctly identified the pain points above as a gap that needed to be filled, especially since the existing tools for managing customer data (e.g., CRM systems) were not up to the task of ingesting and processing such diverse data sources.
Mergers and acquisitions activity over the last several years indicates that the marketplace believes CDP should be delivered as a feature embedded within a larger suite and platform, rather than as a standalone niche software. Some of the vendors of large CX platforms have acquired CDP technology providers and incorporated them into those platforms: Salesforce purchased Evergage, Informatica acquired Allsight, Segment was acquired by Twilio, Emarsys was acquired by SAP. Others, including Adobe and Oracle, have built their own CDP within their platforms.
The outcome suggests that the mode of purchase is transitional (e.g., niche or platform) but the functionality of a CDP is becoming an important component of CX and contact center suites. As the suite landscape evolves to incorporate digital customer interactions, it is likely that the next generation of digital experience platforms will incorporate CDPs as well. Ventana Research asserts that by 2023, one-half of organizations that have deployed standalone customer data platforms will transition to digital experience platforms for digital effectiveness.
This will in turn provide organizations with a technology framework around which to build processes that guide CX-related collaboration among departments that have been siloed both operationally and in data handling.
Looking forward, CDPs are already starting to evolve from engines of data ingestion and integration into more analytic tools that allow users to activate data. This will likely accelerate due to the CDP’s presence in broader platforms for interaction orchestration and audience creation. Today’s CDPs are as likely to appeal to analysts and data science professionals as they are to operations teams.
Buyers should be looking at their own customer processes to assess whether the data silos in place are hindering operational effectiveness, and questioning their vendor partners about strategies for making interaction data more accessible. CDPs should be considered as part of a broader plan for understanding who among CX stakeholders can use customer data, and what use cases can be surfaced. The standard for success in using a CDP has been how well the tool can gather and cleanse existing data. Going forward, buyers should look at richer outcomes like the ability to analyze data and visualize it based on the user’s role.
We expect that competition among CDP vendors will focus on the tension between niche solutions and platforms, with platforms winning most of the arguments. Vendors are already beginning to articulate the next stage of CDP evolution, focusing on enabling users to take action based on unified customer profiles. Vendors should be speaking to both IT and line-of-business professionals, and should start to move beyond existing marketing use cases. Instead, the CDP (and what evolves from it) should be positioned as a way of unifying sales, marketing, commerce and customer service across the entire customer set of processes.
And ultimately, vendors should enhance their CDPs with features for customer identity resolution, personalization, recommendation engines, and other functions that capitalize on unified data to create richer, more distinctive customer experiences.