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In a relatively short time, customer data platforms (CDPs) have become default components of the contact center tech stack. This is an important development for contact center practitioners because it reflects the fact that customer data is essential to maintaining productive customer relationships. It also provides an on-ramp for organizations to establish a sensible data strategy if they have not done so already.
A CDP is a software application that ingests first-party customer data from multiple sources in real time (or near-real time). It may be used to cleanse the data, which is then available to other applications to use for activities like personalization, predictive analytics, proactive outreach for selling or support, and any other function that requires up-to-date customer information.
It is no accident that most of the existing use cases for CDPs come from marketing, which was where the technology first found a home in most enterprises. Marketers found the CDP an effective way to hurdle some of the endemic silos around customer information that exist in the multi-headed customer experience (CX) environment. The technology can make it faster and easier to segment customers for advertising and promotions, measure sentiment and predict behavior.
It has found a home in the support environment as well because service processes themselves have become more complicated in recent years: adding contact channels, automating self-service and optimizing agent behavior all add new applications to the standard contact center stack, sometimes creating new places for data and processes to silo. Contact centers are finding that traditional CRM tools, which function as the system of record for many firms, are not up to the challenge of gathering, enriching and analyzing data at the scale or speed needed for modern CX management. It is likely that by 2027, CRM systems will have been effectively replaced by CDPs (or their successor technology) as the primary mechanism for capturing customer histories.
The CDP is in some sense then a transitional technology that arose to fill a gap (too many data threads that aren’t consistent). Five years ago, the only effective way to deploy a CDP was through a point-solution vendor. What has changed since then is that there is widespread recognition of the need for clean, copious data about customers in service contexts and the willingness of contact center vendors to tackle the problem by building out CDP functionality in their existing Contact-Center-as-a-Service (CCaaS), analytics and CRM-like tools. Examples of this include Content Guru’s storm CKS, Twilio’s Segment and Salesforce’s Data Cloud.
So, the marketplace has essentially transitioned into offering two modes of CDP: one places the CDP squarely into a vendor’s larger CCaaS or CX management suite as the data management layer, and the other remains a point solution, but with capabilities more oriented towards marketing and advertising use cases.
Contact center management must still grapple with some challenges in making a CDP a key part of the infrastructure. Primary among them is the issue of data quality and consistency. If your CDP is ingesting data from various sources that is incorrect, outdated, or merely differs between systems, having a central repository is not going to be of much value. If you truly expect a CDP to provide an accurate picture of customers (individually and in aggregate), then you need a data strategy to oversee the ingestion and cleansing of the inputs. For that reason, it makes sense for contact centers to lean into CDPs that are part of the existing data collection system, including their ACDs and CRM systems.
Addressing these challenges requires a combination of robust data management systems, efficient processes, training and education for agents, and continuous collaboration with IT and data teams.
Despite the challenges, contact centers benefit in several ways from better organizing their data resources. With the proverbial “single source of truth” available to agents and self-service systems at the moment of interaction, support can be personally tailored to the individual customer with awareness of purchase history, past interactions, and a contextual awareness of how the overall journey is unfolding. Along the same lines, use of a CDP can surface issues that lend themselves to proactive outreach — an open support case, for example, or a promotion aimed specifically at a segment of buyers. It can also help make sense of customer feedback and sentiment signals.
Many of the activities enabled by a CDP extend beyond the traditional interaction-handling activities of contact centers, in a good way. As the industry slowly transitions away from the reactive stance typified by basic call handling towards a more proactive CX stance that emphasizes long-term customer value, centers need to be better at collaborating in their applications, data and analytics. Adopting tools with a distinct marketing lineage like CDPs can help boost the perceived value that the contact center contributes to an organization, which in turn helps the center justify resources.
Vendors in this space should be alert to the fact that contact center buyers look at CDPs through a different lens than marketers, and the two groups will respond to different value propositions. Much of the messaging around CDPs for contact centers still comes directly from the marketing viewpoint, emphasizing aspects of audience segmentation and targeting for outreach rather than the direct value of improving interactions in the moment.
It is also important to draw clearer distinctions between the core capabilities of a CDP as added to a contact center platform and the functions of adjacent tools like CRM systems and data lakes, which complement CDPs but don’t substitute for them.
Solution providers have done a good job identifying the market need — customer data that is fresh, accessible and consistent across applications — and have built systems that map well to those market needs. The next step in the evolution of CDPs (for CX and contact centers, at least) is for those vendors to zero in on clarifying business cases that emphasize rapid ROI and non-disruptive deployment.
Regards,
Keith Dawson
Keith Dawson leads the software research and advisory in the Customer Experience (CX) expertise at ISG Software Research, covering applications that facilitate engagement to optimize customer-facing processes. His coverage areas include agent management, contact center, customer experience management, field service, intelligent self-service, voice of the customer and related software to support customer experiences.
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