Enhance Customer Data Initiatives with AI-Powered Personalization
Improving customer experience with Customer Data Platforms
Most organizations are looking to leverage their customer data and the insights generated from it in order to improve customer experience and drive value. Customer Data Platforms (CDPs) can be a key component of these initiatives, enabling clients to aggregate client data and make it available to solutions that generate client insights.
CognitiveScale has worked with numerous clients to improve customer experience via AI-powered applications, so any client assets that help with the aggregation, preparation and availability of data are obviously important. With the popularity of CDPs as well as other tools and initiatives (most clients have Customer 360 or “C360” initiatives and tools in the works), it is important to understand what CDPs offer, where there are gaps and limitations in terms of delivering actionable customer insights, and what else it takes to improve customer experience across the entire enterprise, not just in Marketing and Sales.
From customer insights to value
Customer experience initiatives require several key capabilities
Data Aggregation, Preparation and Availability: CDPs (and other solutions like master data management systems or “MDMs”) and various “Customer 360” initiatives are valuable components that set the stage for personalization
Hyper-personalized Customer Insights: Personalized customer insights can help accelerate sales, improve the call center experience, and hyper-personalize professional services (e.g. improve the care of patients by clinicians, or help wealth managers deliver personalized portfolio recommendations to investors). Customer insights also come from artificial intelligence (AI) applications that can deliver predictions, risk scores, propensity scores, etc. aimed at further improving customer experience.
Customer Profiles: Combining the data and insights specific to a customer needs to include the ability to attach declared and observed data plus personalized insights, model output, rules engines and more - and these profiles must be accessible across the enterprise. Because profiles will be used enterprise-wide, they should include identity resolution capabilities so that customer IDs, address, etc. are consistent across the organization.
AI-powered client-centric solutions: Data, insights, actions, goal-driven campaigns, learning and feedback must all combine in client-centric applications in order to deliver improved customer experience.
Value Attainment: Improvement of key performance indicators (KPIs) in customer experience - revenue, costs, satisfaction scores, industry-specific KPIs (e.g. improved outcomes, better investment returns), and many more - are the true indicators of success, and client-centric solutions need to be goal-oriented and demonstrate their return on investment (ROI).
While CDPs are an important component of client-centric solutions that improve customer experience, the skills and solutions needed across the enterprise in order to drive value from customer data necessitates an understanding of where CDPs fit in this ecosystem, their gaps and limitations, and how to augment them in order to deliver on the promise of realizing value from customer data.
Customer Data Platform Capabilities
What is a CDP?
A Customer Data Platform (CDP) is a collection of software which creates a persistent, unified customer database that is accessible to other systems. Data is pulled from multiple sources, cleaned and combined to create a single customer profile. This structured data is then made available to other marketing systems.
Gartner defines a CDP as “a marketing system that unifies a company’s customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages.”
Forrester defines a CDP as: A platform that centralizes customer data from multiple sources and makes it available to systems of insight and engagement.
Where CDPs are needed
CDPs can help marketers gain visibility into their customers’ behavior and drive personalization about individual customers with key capabilities such as:
Data Enrichment: CDPs have direct plug-ins to large 3rd-party data providers and are well equipped to fill out missing customer attributes in large batch offline mode.
Audience Development: CDPs also have the ability to select audiences for activation or engagement via low-code tools that enable marketers to do this work (not developers).
Multi-Channel Marketing Campaigns: CDPs have direct plug-ins to the largest multi-channel marketing hubs. This makes it easier for a marketer to select an audience and push into large multi-channel marketing campaigns.
Media Buys: CDPs have direct plug-ins to the largest demand-side platforms (DSPs) and offer a streamlined approach for a marketer to select an audience and utilize that audience for programmatic advertising
Challenges & Gaps with CDPs
Analyst research on CDP challenges
Only 1/3rd of CDP users achieve a 360-degree view of their customers
A 2021 Gartner Cross-Functional Customer Data Survey reports that although 43% of respondents of the survey report having a CDP, just 14% of respondents actually achieve a 360-degree view of their customer - roughly 1/3rd of CDP customers.
CDP projects take longer and deliver less value than expected
According to the 2021 CDP Institute Member Survey, Customer Data Platforms are hard. The survey found that just 23% of consumer marketers – the core group of CDP users – have completed their projects on time and on schedule, and only 58% of companies with a deployed CDP say it is delivering significant value. Most of the others are being improved, so they will probably deliver value in the future. Still, there is a gap between the CDP promise and reality.